Introduction to anamiR
2017-11-25
Contents
- 0.1 Installation
- 0.2 General Workflow
- 0.3 Data Source
- 0.4 Usage Example
- 0.4.1 Example Data Source
- 0.4.2 Format of Input Data
- 0.4.3 Normalization (Optional)
- 0.4.4 SummarizedExperiment class
- 0.4.5 Differential Expression Analysis
- 0.4.6 Convert miRNA Annotation (Optional)
- 0.4.7 Correlation Analysis
- 0.4.8 Heat map (optional)
- 0.4.9 Intersect with Databases
- 0.4.10 Functional Analysis
- 0.5 Function Driven Analysis Workflow
- 0.6 Usage Example
- 0.7 Other Functions
This document guides one through all available functions of the anamiR package. Package anamiR aims to find potential miRNA-target gene interactions from both miRNA and mRNA expression data.
Traditional miRNA analysis method is to use online databases to predict miRNA-target gene interactions. However, the inconsistent results make interactions are less reliable. To address this issue, anamiR integrates the whole expression analysis with expression data into workflow, including normalization, differential expression, correlation and then databases intersection, to find more reliable interactions. Moreover, users can identify interactions from interested pathways or gene sets.
0.1 Installation
anamiR is on Bioconductor and can be installed following standard installation procedure.
source("http://www.bioconductor.org/biocLite.R")
biocLite("anamiR")To use,
library(anamiR)## Loading required package: SummarizedExperiment## Loading required package: GenomicRanges## Loading required package: stats4## Loading required package: BiocGenerics## Loading required package: parallel##
## Attaching package: 'BiocGenerics'## The following objects are masked from 'package:parallel':
##
## clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
## clusterExport, clusterMap, parApply, parCapply, parLapply,
## parLapplyLB, parRapply, parSapply, parSapplyLB## The following objects are masked from 'package:stats':
##
## IQR, mad, sd, var, xtabs## The following objects are masked from 'package:base':
##
## Filter, Find, Map, Position, Reduce, anyDuplicated, append,
## as.data.frame, cbind, colMeans, colSums, colnames, do.call,
## duplicated, eval, evalq, get, grep, grepl, intersect,
## is.unsorted, lapply, lengths, mapply, match, mget, order, paste,
## pmax, pmax.int, pmin, pmin.int, rank, rbind, rowMeans, rowSums,
## rownames, sapply, setdiff, sort, table, tapply, union, unique,
## unsplit, which, which.max, which.min## Loading required package: S4Vectors##
## Attaching package: 'S4Vectors'## The following object is masked from 'package:base':
##
## expand.grid## Loading required package: IRanges## Loading required package: GenomeInfoDb## Loading required package: Biobase## Welcome to Bioconductor
##
## Vignettes contain introductory material; view with
## 'browseVignettes()'. To cite Bioconductor, see
## 'citation("Biobase")', and for packages 'citation("pkgname")'.## Loading required package: DelayedArray## Loading required package: matrixStats##
## Attaching package: 'matrixStats'## The following objects are masked from 'package:Biobase':
##
## anyMissing, rowMedians##
## Attaching package: 'DelayedArray'## The following objects are masked from 'package:matrixStats':
##
## colMaxs, colMins, colRanges, rowMaxs, rowMins, rowRanges## The following object is masked from 'package:base':
##
## apply## Setting options('download.file.method.GEOquery'='auto')## Setting options('GEOquery.inmemory.gpl'=FALSE)0.2 General Workflow
The general workflow can be summarized as follows,
Basically there are six steps, corresponding to six R functions, to complete the whole analysis:
- Normalize expression data
- Find differential expreesion miRNAs and genes
- Convert miRNA annotation to the latest version
- Calculate the correlation coefficient between each miRNA and gene
- Intersect with prediction and validation of miRNA- target gene interactions databases
- Functional analysis with interested genes
0.3 Data Source
As shown in the workflow, not only samples of paired miRNA and mRNA expression data, but phenotypical information of miRNA and mRNA are also required for the analysis. Since anamiR reads data in expression matrices, data sources are platform and technology agnostic. particularly, expression data from microarray or next generation sequencing are all acceptable for anamiR. However, this also indicates the raw data should be pre-processd to the expression matrices before using anamiR.
0.3.1 mRNA expression
Columns for samples. Rows for genes
GENE SmapleA SamplB ...
A 0.1 0.2
B -0.5 -0.3
C 0.4 0.10.3.2 miRNA expression
Columns for samples. Rows for miRNAs
miRNA SampleA SampleB ...
A 0.1 0.5
B -0.5 2.1
C 0.4 0.30.3.3 phenotype data
Cloumns for samples. Rows for feature name, including two groups, multiple groups, continuous data.
Feature groupA groupA groupA ...
SampleA 123.33 A A
SampleB 120.34 B C
SampleC 121.22 A B0.4 Usage Example
Now, we show an example using internal data for anamiR workflow.
0.4.1 Example Data Source
To demonstrate the usage of the anamiR package, the package contains 30 paired miRNA and mRNA breast cancer samples, which are selected from 101 miRNA samples and 114 mRNA samples from GSE19536. As for phenotype data (hybridization information), there are three types of information in it, including two-groups, multi-groups, continuous data.
The mRNA data was conducted by Agilent-014850 Whole Human Genome Microarray 4x44K G4112F (Probe Name version) platform and the miRNA data was generated from Agilent-019118 Human miRNA Microarray 2.0 G4470B (miRNA ID version).
0.4.2 Format of Input Data
First of all, load the internal data and check the format.
data(mrna)
data(mirna)
data(pheno.mirna)
data(pheno.mrna)Basically, the format of input data should be the same as the internal data. For mRNA expression data should be like,
mrna[1:5, 1:5]## BC.M.014 BC.M.015 BC.M.017 BC.M.019 BC.M.023
## TRIM35 8.725157 8.699302 9.864870 8.986249 9.253038
## NR2C2AP 10.973569 11.318088 11.212974 11.803147 11.823159
## CENPO 7.404785 8.417221 8.272822 8.670029 9.392538
## ADCY8 5.785176 6.066669 6.240934 6.345486 6.037214
## RGS22 8.828413 7.844503 7.712051 7.078598 8.712837As for miRNA expression data,
mirna[1:5, 1:5]## BC.M.014 BC.M.015 BC.M.017 BC.M.019 BC.M.023
## hsa-miR-139-5p 3.301236 4.072743 3.476371 3.957260 6.662144
## hsa-miR-575 9.525705 10.097954 10.790396 9.365697 9.289803
## hsa-miR-33b* 4.089836 4.297618 4.051852 3.842798 3.044545
## hsa-miR-335 4.146060 5.615910 6.274007 5.655296 9.309553
## hsa-miR-16-2* 3.407055 4.023072 3.052135 4.208022 4.572399And the phenotype data, (NOTICE:users should arrange the case columns front of the control columns.)
pheno.mrna[1:3, 1:3]## Subtype Survival ER
## BC.M.014 "breast cancer subtype: Lum A" "126.611842105263" "case"
## BC.M.015 "breast cancer subtype: Lum A" "126.513157894737" "case"
## BC.M.017 "breast cancer subtype: Lum A" "80.9868421052632" "case"pheno.mrna[28:30, 1:3]## Subtype Survival ER
## BC.M.221 "breast cancer subtype: Basal" "115.197368421053" "control"
## BC.M.318 "breast cancer subtype: ERBB2" "110.526315789474" "control"
## BC.M.709 "breast cancer subtype: Basal" "15.2960526315789" "control"Actually, the phenotype data of miRNA and mRNA share the same contents,but in this case, we still make it in two data to prevent users from being confused about it.
0.4.3 Normalization (Optional)
Secondly, we normalize data. (If you use the normalized data, you can skip this step.)
se <- normalization(data = mirna, method = "quantile")For this function, there are three methods provided, including quantile, rank.invariant, normal. For more detail, Please refer to their documentation.
Note that internal data have already been normalized, here is only for demonstration.
0.4.4 SummarizedExperiment class
Before entering the main workflow, we should put our data and phenotype information into SummarizedExperiment class first, which you can get more information from .
mrna_se <- SummarizedExperiment(
assays = SimpleList(counts=mrna),
colData = pheno.mrna)
mirna_se <- SummarizedExperiment(
assays = SimpleList(counts=mirna),
colData = pheno.mirna)0.4.5 Differential Expression Analysis
Third, we will find differential expression genes and miRNAs. There are three statitical methods in this function. here, we use t.test for demonstration.
mrna_d <- differExp_discrete(se = mrna_se,
class = "ER", method = "t.test",
t_test.var = FALSE, log2 = FALSE,
p_value.cutoff = 0.05, logratio = 0.5
)
mirna_d <- differExp_discrete(se = mirna_se,
class = "ER", method = "t.test",
t_test.var = FALSE, log2 = FALSE,
p_value.cutoff = 0.05, logratio = 0.5
)This function will delete genes and miRNAs (rows), which do not differential express, and add another three columns represent fold change (log2), p-value, adjusted p-value.
Take differential expressed mRNA data for instance,
nc <- ncol(mrna_d)
mrna_d[1:5, (nc-4):nc]## log-ratio P-Value P-adjust mean_case mean_control
## NR2C2AP -1.0712486 2.316469e-04 5.312839e-04 11.556393 12.627641
## CENPO -0.8558411 2.682517e-04 5.748560e-04 8.349869 9.205710
## RGS22 1.6894848 2.039121e-05 1.631297e-04 8.398516 6.709031
## KIF3C -0.5848147 4.541900e-05 2.270950e-04 8.279248 8.864063
## SENP5 -0.7626540 8.630361e-07 1.917858e-05 10.737840 11.5004940.4.6 Convert miRNA Annotation (Optional)
Before using collected databases for intersection with potential miRNA-target gene interactions, we have to make sure all miRNA are in the latest annotation version (miRBase 21). If not, we could use this function to do it.
mirna_21 <- miR_converter(data = mirna_d, remove_old = TRUE,
original_version = 17, latest_version = 21)Now, we can compare these two data,
# Before
head(row.names(mirna_d))## [1] "hsa-miR-575" "hsa-miR-150*" "hsa-miR-198" "hsa-miR-342-3p"
## [5] "hsa-miR-342-5p" "hsa-miR-134"# After
head(row.names(mirna_21))## [1] "hsa-miR-575" "hsa-miR-150-3p" "hsa-miR-198" "hsa-miR-342-3p"
## [5] "hsa-miR-342-5p" "hsa-miR-134-5p"Note that user must put the right original version into parameter, because it is an important information for function to convert annotation.
0.4.7 Correlation Analysis
To find potential miRNA-target gene interactions, we should combine the information in two differential expressed data, which we obtained from differExp_discrete.
cor <- negative_cor(mrna_data = mrna_d, mirna_data = mirna_21,
method = "pearson", cut.off = -0.5)For output,
head(cor)## miRNA Gene Correlation( -0.5 ) logratio(miRNA)
## [1,] "hsa-miR-198" "NR2C2AP" "-0.60749521052608" "1.434328524"
## [2,] "hsa-miR-198" "SENP5" "-0.54646311346452" "1.434328524"
## [3,] "hsa-miR-134-5p" "SENP5" "-0.508211941696094" "1.0180378"
## [4,] "hsa-miR-198" "AKAP1" "-0.540628213927599" "1.434328524"
## [5,] "hsa-miR-342-3p" "PIF1" "-0.565476513859015" "2.19495706"
## [6,] "hsa-miR-342-5p" "PIF1" "-0.621317621065092" "2.115864648"
## P-adjust(miRNA) mean_case(miRNA) mean_control(miRNA)
## [1,] "0.0287086140383543" "4.963163064" "3.52883454"
## [2,] "0.0287086140383543" "4.963163064" "3.52883454"
## [3,] "0.000137286128508541" "8.14071616" "7.12267836"
## [4,] "0.0287086140383543" "4.963163064" "3.52883454"
## [5,] "1.07192166300769e-09" "11.34977766" "9.1548206"
## [6,] "9.42861994530635e-11" "7.135666308" "5.01980166"
## logratio(gene) P-adjust(gene) mean_case(gene)
## [1,] "-1.071248568" "0.000531283948592135" "11.556392652"
## [2,] "-0.762654017199999" "1.91785808708134e-05" "10.7378403228"
## [3,] "-0.762654017199999" "1.91785808708134e-05" "10.7378403228"
## [4,] "-1.2822530884" "0.000659175618505387" "12.1560164316"
## [5,] "-1.5501717548" "0.00020239427080686" "8.5069645972"
## [6,] "-1.5501717548" "0.00020239427080686" "8.5069645972"
## mean_control(gene)
## [1,] "12.62764122"
## [2,] "11.50049434"
## [3,] "11.50049434"
## [4,] "13.43826952"
## [5,] "10.057136352"
## [6,] "10.057136352"As the showing list, each row is a potential interaction, and only the row that correlation coefficient < cut.off would be kept in list.
Note that in our assumption, miRNAs negatively regulate expression of their target genes, that is, cut.off basically should be negative decimal.
0.4.8 Heat map (optional)
There is a function for user to see the heatmaps about the miRNA-target gene interactions remaining in the correlation analysis table.
heat_vis(cor, mrna_d, mirna_21)
0.4.9 Intersect with Databases
After correlation analysis, we have some potential interactions, and then using database_support helps us to get information that whether there are databases predict or validate these interactions.
sup <- database_support(cor_data = cor,
org = "hsa", Sum.cutoff = 3)From output, column Sum tells us the total hits by 8 predict databases and column Validate tells us if this interaction have been validated.
head(sup)## miRNA_21 Gene_symbol Ensembl Gene_ID DIANA_microT_CDS
## [1,] "hsa-miR-342-3p" "ATF4" "ENSG00000128272" "468" 0
## [2,] "hsa-miR-342-3p" "PKP1" "ENSG00000081277" "5317" 1
## [3,] "hsa-miR-342-5p" "ITPRIP" "ENSG00000148841" "85450" 1
## [4,] "hsa-miR-342-3p" "LRP8" "ENSG00000157193" "7804" 1
## [5,] "hsa-miR-134-5p" "SIN3B" "ENSG00000127511" "23309" 1
## EIMMo Microcosm miRDB miRanda PITA rna22 Targetscan Sum miRecords
## [1,] 0 0 0 0 0 0 0 0 0
## [2,] 1 0 0 1 0 1 0 4 0
## [3,] 1 0 0 1 0 0 0 3 0
## [4,] 1 0 1 1 0 1 0 5 0
## [5,] 1 0 0 1 0 0 0 3 0
## miRTarBase Validate Correlation( -0.5 ) logratio(miRNA)
## [1,] 1 "TRUE" "-0.53495895225322" "2.19495706"
## [2,] 1 "TRUE" "-0.597546840711108" "2.19495706"
## [3,] 0 "FALSE" "-0.58001171396371" "2.115864648"
## [4,] 0 "FALSE" "-0.699212107696958" "2.19495706"
## [5,] 0 "FALSE" "-0.549533374374203" "1.0180378"
## P-adjust(miRNA) mean_case(miRNA) mean_control(miRNA)
## [1,] "1.07192166300769e-09" "11.34977766" "9.1548206"
## [2,] "1.07192166300769e-09" "11.34977766" "9.1548206"
## [3,] "9.42861994530635e-11" "7.135666308" "5.01980166"
## [4,] "1.07192166300769e-09" "11.34977766" "9.1548206"
## [5,] "0.000137286128508541" "8.14071616" "7.12267836"
## logratio(gene) P-adjust(gene) mean_case(gene)
## [1,] "-1.007603132" "1.70115709649906e-05" "15.556558828"
## [2,] "-1.49107022" "0.00020239427080686" "6.694310296"
## [3,] "-1.12346218" "0.000311769820018285" "9.41393342"
## [4,] "-1.8819269508" "0.000574855984019839" "7.6078690312"
## [5,] "-1.0848951548" "0.000324178247302931" "8.4875415732"
## mean_control(gene) de novo
## [1,] "16.56416196" 0
## [2,] "8.185380516" 0
## [3,] "10.5373956" 0
## [4,] "9.489795982" 0
## [5,] "9.572436728" 0Note that we have 8 predict databases (DIANA microT CDS, EIMMo, Microcosm, miRDB, miRanda, PITA, rna22, TargetScan) and 2 validate databases (miRecords, miRTarBase).
0.4.10 Functional Analysis
The last, after finding reliable miRNA-target gene interactions, we are also interested in pathways, which may be enriched by these genes.
path <- enrichment(data_support = sup, org = "hsa", per_time = 500)Note that for parameter per_time, we only choose 500 times, because it is for demonstration here. Default is 5000 times.
The output from this data not only shows P-Value generated by hypergeometric test, but Empirical P-Value, which means the value of average permutation test in each pathway.
head(path)## Database Term
## [1,] "KEGG_hsa" "Adrenergic signaling in cardiomyocytes"
## [2,] "KEGG_hsa" "Alcoholism"
## [3,] "KEGG_hsa" "Aldosterone synthesis and secretion"
## [4,] "KEGG_hsa" "Amphetamine addiction"
## [5,] "KEGG_hsa" "Apoptosis"
## [6,] "KEGG_hsa" "cGMP-PKG signaling pathway"
## Total Genes of the Term Targets in the Term
## [1,] "148" "1"
## [2,] "166" "1"
## [3,] "64" "1"
## [4,] "61" "1"
## [5,] "133" "1"
## [6,] "157" "1"
## Targets in Total Genes of the Term(%) Raw P-Value
## [1,] "0.00675675675675676" "0.0211173573494353"
## [2,] "0.00602409638554217" "0.0236611563367605"
## [3,] "0.015625" "0.00917609139003062"
## [4,] "0.0163934426229508" "0.00874747254557706"
## [5,] "0.0075187969924812" "0.0189934770386644"
## [6,] "0.00636942675159236" "0.0223899187544135"
## Empirical P-Value
## [1,] "0.00998003992015968"
## [2,] "0.0149700598802395"
## [3,] "0.00798403193612774"
## [4,] "0.00499001996007984"
## [5,] "0.00898203592814371"
## [6,] "0.0119760479041916"0.5 Function Driven Analysis Workflow
This package also provides another workflow for analyzing expression data.
Basically there are only two steps with two R functions, to complete the whole analysis:
- Find related miRNAs and genes in the possible enriched pathways.
- Find potential interactions from the above result.
0.6 Usage Example
Now, we show an example using internal data for anamiR workflow.
0.6.1 Example Data Source
To demonstrate the usage of the anamiR package, the package contains 99 paired miRNA and mRNA breast cancer samples, which are selected from 101 miRNA samples and 114 mRNA samples from GSE19536. As for phenotype data (hybridization information).
The mRNA data was conducted by Agilent-014850 Whole Human Genome Microarray 4x44K G4112F (Probe Name version) platform and the miRNA data was generated from Agilent-019118 Human miRNA Microarray 2.0 G4470B (miRNA ID version).
0.6.2 Format of Input Data
The same as the format in the first workflow.
require(data.table)## Loading required package: data.table##
## Attaching package: 'data.table'## The following object is masked from 'package:SummarizedExperiment':
##
## shift## The following object is masked from 'package:GenomicRanges':
##
## shift## The following object is masked from 'package:IRanges':
##
## shift## The following objects are masked from 'package:S4Vectors':
##
## first, secondaa <- system.file("extdata", "GSE19536_mrna.csv", package = "anamiR")
mrna <- fread(aa, fill = TRUE, header = TRUE)
bb <- system.file("extdata", "GSE19536_mirna.csv", package = "anamiR")
mirna <- fread(bb, fill = TRUE, header = TRUE)
cc <- system.file("extdata", "pheno_data.csv", package = "anamiR")
pheno.data <- fread(cc, fill = TRUE, header = TRUE)transform the data format to matrix.
mirna_name <- mirna[["miRNA"]]
mrna_name <- mrna[["Gene"]]
mirna <- mirna[, -1]
mrna <- mrna[, -1]
mirna <- data.matrix(mirna)
mrna <- data.matrix(mrna)
row.names(mirna) <- mirna_name
row.names(mrna) <- mrna_name
pheno_name <- pheno.data[["Sample"]]
pheno.data <- pheno.data[, -1]
pheno.data <- as.matrix(pheno.data)
row.names(pheno.data) <- pheno_namemrna expression data should be the same format as,
mrna[1:5, 1:5]## BC.M.002 BC.M.003 BC.M.014 BC.M.015 BC.M.017
## FAM174B 11.933085 12.336716 11.316612 12.897171 11.202400
## AP3S2 6.594222 6.782256 6.686422 8.184705 6.873914
## SV2B 9.507788 7.785795 6.931555 8.069596 8.076411
## RBPMS2 7.043462 6.432242 6.287466 7.160961 6.637851
## AVEN 10.858463 10.310998 10.218271 10.054989 10.924755as for mirna,
mirna[1:5, 1:5]## BC.M.002 BC.M.003 BC.M.014 BC.M.015 BC.M.017
## hsa-let-7a-5p 13.265629 15.638350 13.895478 14.093235 13.073778
## hsa-let-7a-3p 2.655024 3.458061 3.773592 3.849688 1.625209
## hsa-let-7b-5p 12.896871 15.462644 14.169578 14.373066 12.913365
## hsa-let-7b-3p 1.805261 3.562475 3.441661 3.514808 2.697695
## hsa-let-7c-5p 11.920269 13.777391 12.585502 12.696483 11.707704and phenotype data,
pheno.data[1:5, 1]## BC.M.002 BC.M.003 BC.M.014 BC.M.015 BC.M.017
## "case" "case" "case" "case" "case"pheno.data[94:98, 1]## BC.M.551 BC.M.579 BC.M.627 BC.M.630 BC.M.709
## "control" "control" "control" "control" "control"0.6.3 SummarizedExperiment class
Before entering the main workflow, we should put our data and phenotype information into SummarizedExperiment class first, which you can get more information from .
mrna_se <- SummarizedExperiment(
assays = SimpleList(counts=mrna),
colData = pheno.data)
mirna_se <- SummarizedExperiment(
assays = SimpleList(counts=mirna),
colData = pheno.data)0.6.4 GSEA analysis
First step, we use GSEA_ana function to find the pathways which are the most likely enriched in given expreesion data.
table <- GSEA_ana(mrna_se = mrna_se, mirna_se = mirna_se, class = "ER", pathway_num = 2)the result would be a list containg related genes and miRNAs matrix for each pathway.
Note that because it would take a few minutes to run GSEA_ana, here we use the pre-calculated data to show the output.
data(table_pre)For the first pathway,
names(table_pre)[1]## [1] "CHARAFE_BREAST_CANCER_LUMINAL_VS_BASAL_UP - mirna"table_pre[[1]][1:5, 1:5]## BC.M.002 BC.M.003 BC.M.014 BC.M.015 BC.M.017
## hsa-let-7a-5p 13.265629 15.638350 13.895478 14.093235 13.073778
## hsa-let-7a-3p 2.655024 3.458061 3.773592 3.849688 1.625209
## hsa-let-7b-5p 12.896871 15.462644 14.169578 14.373066 12.913365
## hsa-let-7b-3p 1.805261 3.562475 3.441661 3.514808 2.697695
## hsa-let-7d-5p 9.739521 11.480442 10.432780 10.410680 9.861024names(table_pre)[2]## [1] "CHARAFE_BREAST_CANCER_LUMINAL_VS_BASAL_UP - mrna"table_pre[[2]][1:5, 1:5]## BC.M.002 BC.M.003 BC.M.014 BC.M.015 BC.M.017
## MYO5B 11.683596 11.635398 11.227723 11.580794 10.486385
## HPN 8.328735 11.169826 9.674486 12.917072 10.847883
## RSPH1 9.157633 11.376723 10.428724 11.192539 10.217411
## PI4KA 11.258279 10.465667 9.751591 11.539817 10.976314
## HMGCS2 10.151288 8.542307 6.256523 9.715437 8.422795GSEA_ana intersects the related genes and miRNAs found from databases with the given expression data.
0.6.5 GSEA Result
After doing GSEA analysis, we have selected miRNA and gene expression data for each enriched pathway. As for the second step, the generated odject would be put into GSEA_res.
result <- GSEA_res(table = table_pre, pheno.data = pheno.data, class = "ER", DE_method = "limma", cor_cut = 0)This function helps us calculate P-value, Fold-Change, Correlation for each miRNA-gene pair and show these value to users.
names(result)[1]## [1] "CHARAFE_BREAST_CANCER_LUMINAL_VS_BASAL_UP "result[[1]]## miRNA_21 Gene_symbol Ensembl Gene_ID
## [1,] "hsa-let-7b-3p" "MYO5B" "ENSG00000167306" "4645"
## [2,] "hsa-let-7f-1-3p" "MYO5B" "ENSG00000167306" "4645"
## [3,] "hsa-miR-106b-3p" "RSPH1" "ENSG00000160188" "89765"
## [4,] "hsa-let-7d-5p" "HMGCS2" "ENSG00000134240" "3158"
## [5,] "hsa-miR-103a-3p" "HMGCS2" "ENSG00000134240" "3158"
## [6,] "hsa-miR-105-5p" "HMGCS2" "ENSG00000134240" "3158"
## [7,] "hsa-let-7i-3p" "ANXA9" "ENSG00000143412" "8416"
## [8,] "hsa-miR-1-3p" "ZNF84" "ENSG00000198040" "7637"
## [9,] "hsa-miR-106b-3p" "SERF2" "ENSG00000140264" "10169"
## [10,] "hsa-let-7f-2-3p" "RAB11FIP3" "ENSG00000090565" "9727"
## [11,] "hsa-let-7d-5p" "SPDEF" "ENSG00000124664" "25803"
## [12,] "hsa-let-7i-5p" "SPDEF" "ENSG00000124664" "25803"
## [13,] "hsa-let-7b-3p" "VPS72" "ENSG00000163159" "6944"
## [14,] "hsa-let-7i-5p" "HMG20B" "ENSG00000064961" "10362"
## [15,] "hsa-let-7i-3p" "HMG20B" "ENSG00000064961" "10362"
## [16,] "hsa-miR-106b-3p" "CFD" "ENSG00000197766" "1675"
## [17,] "hsa-miR-103a-3p" "TTC3" "ENSG00000182670" "7267"
## [18,] "hsa-miR-106b-3p" "WFS1" "ENSG00000109501" "7466"
## [19,] "hsa-let-7i-5p" "LLGL2" "ENSG00000073350" "3993"
## [20,] "hsa-miR-1-3p" "LLGL2" "ENSG00000073350" "3993"
## [21,] "hsa-let-7b-5p" "EPN3" "ENSG00000049283" "55040"
## [22,] "hsa-let-7d-5p" "EPN3" "ENSG00000049283" "55040"
## [23,] "hsa-miR-100-5p" "EPN3" "ENSG00000049283" "55040"
## [24,] "hsa-let-7b-5p" "PYCR1" "ENSG00000183010" "5831"
## [25,] "hsa-let-7e-5p" "PYCR1" "ENSG00000183010" "5831"
## [26,] "hsa-let-7i-5p" "PYCR1" "ENSG00000183010" "5831"
## [27,] "hsa-miR-1-3p" "PYCR1" "ENSG00000183010" "5831"
## [28,] "hsa-miR-103a-3p" "PYCR1" "ENSG00000183010" "5831"
## [29,] "hsa-let-7e-3p" "GGA1" "ENSG00000100083" "26088"
## [30,] "hsa-miR-106b-3p" "GGA1" "ENSG00000100083" "26088"
## [31,] "hsa-miR-100-5p" "SIDT1" "ENSG00000072858" "54847"
## [32,] "hsa-miR-106b-3p" "TBX3" "ENSG00000135111" "6926"
## [33,] "hsa-let-7e-5p" "FAM46C" "ENSG00000183508" "54855"
## [34,] "hsa-miR-105-5p" "FAM46C" "ENSG00000183508" "54855"
## [35,] "hsa-miR-106b-3p" "ABCA3" "ENSG00000167972" "21"
## [36,] "hsa-miR-106b-3p" "KLHL22" "ENSG00000099910" "84861"
## [37,] "hsa-miR-105-5p" "THSD4" "ENSG00000187720" "79875"
## [38,] "hsa-miR-106b-3p" "THSD4" "ENSG00000187720" "79875"
## [39,] "hsa-let-7d-5p" "CAPN9" "ENSG00000135773" "10753"
## [40,] "hsa-let-7i-3p" "SLC16A6" "ENSG00000108932" "9120"
## [41,] "hsa-miR-105-5p" "SLC16A6" "ENSG00000108932" "9120"
## [42,] "hsa-miR-106b-3p" "SLC16A6" "ENSG00000108932" "9120"
## [43,] "hsa-miR-105-5p" "MLPH" "ENSG00000115648" "79083"
## [44,] "hsa-let-7a-5p" "TMEM184A" "ENSG00000164855" "202915"
## [45,] "hsa-let-7b-5p" "TMEM184A" "ENSG00000164855" "202915"
## [46,] "hsa-let-7d-5p" "TMEM184A" "ENSG00000164855" "202915"
## [47,] "hsa-let-7e-5p" "TMEM184A" "ENSG00000164855" "202915"
## [48,] "hsa-let-7f-5p" "TMEM184A" "ENSG00000164855" "202915"
## [49,] "hsa-let-7g-5p" "TMEM184A" "ENSG00000164855" "202915"
## [50,] "hsa-let-7i-5p" "TMEM184A" "ENSG00000164855" "202915"
## [51,] "hsa-miR-100-5p" "TTC39A" "ENSG00000085831" "22996"
## [52,] "hsa-let-7f-2-3p" "DNALI1" "ENSG00000163879" "7802"
## [53,] "hsa-let-7i-5p" "ABCG1" "ENSG00000160179" "9619"
## [54,] "hsa-miR-100-5p" "ABCG1" "ENSG00000160179" "9619"
## [55,] "hsa-let-7b-3p" "GPR160" "ENSG00000173890" "26996"
## [56,] "hsa-let-7f-1-3p" "GPR160" "ENSG00000173890" "26996"
## [57,] "hsa-let-7f-2-3p" "GPR160" "ENSG00000173890" "26996"
## [58,] "hsa-miR-105-5p" "GPR160" "ENSG00000173890" "26996"
## [59,] "hsa-let-7f-2-3p" "TSPAN13" "ENSG00000106537" "27075"
## [60,] "hsa-let-7f-2-3p" "TMEM57" "ENSG00000204178" "55219"
## [61,] "hsa-let-7b-5p" "ZNF74" "ENSG00000185252" "7625"
## [62,] "hsa-let-7g-5p" "ZNF74" "ENSG00000185252" "7625"
## [63,] "hsa-let-7b-3p" "TNIP1" "ENSG00000145901" "10318"
## [64,] "hsa-let-7f-1-3p" "TNIP1" "ENSG00000145901" "10318"
## [65,] "hsa-let-7f-2-3p" "IQCE" "ENSG00000106012" "23288"
## [66,] "hsa-miR-105-5p" "IQCE" "ENSG00000106012" "23288"
## [67,] "hsa-let-7d-3p" "SNX27" "ENSG00000143376" "81609"
## [68,] "hsa-miR-105-5p" "MAPT" "ENSG00000186868" "4137"
## [69,] "hsa-let-7b-5p" "CSNK1D" "ENSG00000141551" "1453"
## [70,] "hsa-let-7e-5p" "CSNK1D" "ENSG00000141551" "1453"
## [71,] "hsa-let-7g-5p" "CSNK1D" "ENSG00000141551" "1453"
## [72,] "hsa-miR-1-3p" "CSNK1D" "ENSG00000141551" "1453"
## [73,] "hsa-miR-101-3p" "CSNK1D" "ENSG00000141551" "1453"
## [74,] "hsa-let-7b-3p" "SYCP2" "ENSG00000196074" "10388"
## [75,] "hsa-let-7f-1-3p" "SYCP2" "ENSG00000196074" "10388"
## [76,] "hsa-let-7f-2-3p" "SYCP2" "ENSG00000196074" "10388"
## [77,] "hsa-miR-106b-3p" "CLSTN2" "ENSG00000158258" "64084"
## [78,] "hsa-miR-106b-3p" "ATP6AP1" "ENSG00000071553" "537"
## [79,] "hsa-let-7d-3p" "SEC16A" "ENSG00000148396" "9919"
## [80,] "hsa-miR-1-3p" "STRBP" "ENSG00000165209" "55342"
## [81,] "hsa-miR-101-3p" "PGGT1B" "ENSG00000164219" "5229"
## [82,] "hsa-miR-106b-3p" "PGGT1B" "ENSG00000164219" "5229"
## [83,] "hsa-miR-106b-3p" "ZNF444" "ENSG00000167685" "55311"
## [84,] "hsa-let-7a-5p" "C4orf19" "ENSG00000154274" "55286"
## [85,] "hsa-let-7b-5p" "C4orf19" "ENSG00000154274" "55286"
## [86,] "hsa-miR-1-3p" "C4orf19" "ENSG00000154274" "55286"
## [87,] "hsa-miR-106b-3p" "HEXDC" "ENSG00000169660" "284004"
## [88,] "hsa-let-7f-2-3p" "TAPT1" "ENSG00000169762" "202018"
## [89,] "hsa-let-7i-3p" "C10orf82" "ENSG00000165863" "143379"
## [90,] "hsa-miR-106b-3p" "RHPN1" "ENSG00000158106" "114822"
## [91,] "hsa-let-7a-5p" "ABHD11" "ENSG00000106077" "83451"
## [92,] "hsa-let-7b-5p" "ABHD11" "ENSG00000106077" "83451"
## [93,] "hsa-let-7d-5p" "ABHD11" "ENSG00000106077" "83451"
## [94,] "hsa-let-7d-3p" "ABHD11" "ENSG00000106077" "83451"
## [95,] "hsa-let-7e-5p" "ABHD11" "ENSG00000106077" "83451"
## [96,] "hsa-let-7f-5p" "ABHD11" "ENSG00000106077" "83451"
## [97,] "hsa-let-7g-5p" "ABHD11" "ENSG00000106077" "83451"
## [98,] "hsa-let-7i-5p" "ABHD11" "ENSG00000106077" "83451"
## [99,] "hsa-miR-1-3p" "ABHD11" "ENSG00000106077" "83451"
## [100,] "hsa-miR-103a-3p" "ABHD11" "ENSG00000106077" "83451"
## [101,] "hsa-let-7a-5p" "ISG20" "ENSG00000172183" "3669"
## [102,] "hsa-let-7b-5p" "ISG20" "ENSG00000172183" "3669"
## [103,] "hsa-let-7d-3p" "ISG20" "ENSG00000172183" "3669"
## [104,] "hsa-let-7f-5p" "ISG20" "ENSG00000172183" "3669"
## [105,] "hsa-miR-1-3p" "ISG20" "ENSG00000172183" "3669"
## [106,] "hsa-let-7i-3p" "GPRC5C" "ENSG00000170412" "55890"
## [107,] "hsa-miR-101-5p" "GPRC5C" "ENSG00000170412" "55890"
## [108,] "hsa-miR-103a-3p" "GPRC5C" "ENSG00000170412" "55890"
## [109,] "hsa-miR-1-3p" "MGRN1" "ENSG00000102858" "23295"
## [110,] "hsa-miR-106b-3p" "MGRN1" "ENSG00000102858" "23295"
## [111,] "hsa-miR-106b-3p" "STARD10" "ENSG00000214530" "10809"
## [112,] "hsa-let-7f-2-3p" "SNED1" "ENSG00000162804" "25992"
## [113,] "hsa-miR-103a-3p" "SNED1" "ENSG00000162804" "25992"
## [114,] "hsa-let-7i-3p" "EFR3B" "ENSG00000084710" "22979"
## [115,] "hsa-miR-101-5p" "EFR3B" "ENSG00000084710" "22979"
## [116,] "hsa-miR-1-3p" "SLC38A10" "ENSG00000157637" "124565"
## [117,] "hsa-miR-106b-3p" "DUSP8" "ENSG00000184545" "1850"
## [118,] "hsa-let-7i-3p" "FAM110B" "ENSG00000169122" "90362"
## [119,] "hsa-miR-106b-3p" "FAM110B" "ENSG00000169122" "90362"
## [120,] "hsa-miR-103a-3p" "HIP1R" "ENSG00000130787" "9026"
## [121,] "hsa-miR-106b-3p" "HIP1R" "ENSG00000130787" "9026"
## [122,] "hsa-let-7d-5p" "CXXC5" "ENSG00000171604" "51523"
## [123,] "hsa-let-7i-5p" "CXXC5" "ENSG00000171604" "51523"
## [124,] "hsa-let-7i-3p" "CXXC5" "ENSG00000171604" "51523"
## [125,] "hsa-let-7b-3p" "DKFZP586I1420" "" "222161"
## [126,] "hsa-let-7f-1-3p" "DKFZP586I1420" "" "222161"
## [127,] "hsa-miR-105-5p" "DKFZP586I1420" "" "222161"
## [128,] "hsa-miR-105-5p" "ELOVL2" "ENSG00000197977" "54898"
## [129,] "hsa-miR-106b-3p" "ELOVL2" "ENSG00000197977" "54898"
## [130,] "hsa-let-7e-3p" "CCDC117" "ENSG00000159873" "150275"
## [131,] "hsa-miR-100-5p" "CCDC117" "ENSG00000159873" "150275"
## [132,] "hsa-miR-106b-3p" "CCDC117" "ENSG00000159873" "150275"
## [133,] "hsa-let-7i-3p" "LFNG" "ENSG00000106003" "3955"
## [134,] "hsa-let-7a-5p" "DENND1A" "ENSG00000119522" "57706"
## [135,] "hsa-let-7b-5p" "DENND1A" "ENSG00000119522" "57706"
## [136,] "hsa-let-7e-5p" "DENND1A" "ENSG00000119522" "57706"
## [137,] "hsa-let-7f-5p" "DENND1A" "ENSG00000119522" "57706"
## [138,] "hsa-let-7g-5p" "DENND1A" "ENSG00000119522" "57706"
## [139,] "hsa-miR-101-3p" "DENND1A" "ENSG00000119522" "57706"
## [140,] "hsa-miR-103a-3p" "DENND1A" "ENSG00000119522" "57706"
## [141,] "hsa-miR-101-3p" "RND1" "ENSG00000172602" "27289"
## [142,] "hsa-miR-105-5p" "RND1" "ENSG00000172602" "27289"
## [143,] "hsa-let-7b-3p" "RHOH" "ENSG00000168421" "399"
## [144,] "hsa-let-7f-1-3p" "RHOH" "ENSG00000168421" "399"
## [145,] "hsa-miR-106b-3p" "ZNF467" "ENSG00000181444" "168544"
## [146,] "hsa-let-7a-5p" "PLCXD1" "ENSG00000182378" "55344"
## [147,] "hsa-let-7a-3p" "PLCXD1" "ENSG00000182378" "55344"
## [148,] "hsa-let-7b-5p" "PLCXD1" "ENSG00000182378" "55344"
## [149,] "hsa-let-7e-5p" "PLCXD1" "ENSG00000182378" "55344"
## [150,] "hsa-let-7e-3p" "PLCXD1" "ENSG00000182378" "55344"
## [151,] "hsa-let-7f-5p" "PLCXD1" "ENSG00000182378" "55344"
## [152,] "hsa-let-7f-1-3p" "PLCXD1" "ENSG00000182378" "55344"
## [153,] "hsa-miR-103a-3p" "PLCXD1" "ENSG00000182378" "55344"
## [154,] "hsa-let-7b-5p" "SBK1" "ENSG00000188322" "388228"
## [155,] "hsa-miR-100-5p" "DHRS13" "ENSG00000167536" "147015"
## [156,] "hsa-let-7i-3p" "KRT19" "ENSG00000171345" "3880"
## [157,] "hsa-let-7b-3p" "CACYBP" "ENSG00000116161" "27101"
## [158,] "hsa-miR-1-3p" "MYEF2" "ENSG00000104177" "50804"
## [159,] "hsa-miR-100-5p" "MYEF2" "ENSG00000104177" "50804"
## [160,] "hsa-miR-1-3p" "TGIF2" "ENSG00000118707" "60436"
## [161,] "hsa-miR-1-3p" "SLC24A3" "ENSG00000185052" "57419"
## [162,] "hsa-miR-105-5p" "KLHDC9" "ENSG00000162755" "126823"
## [163,] "hsa-let-7i-5p" "SLC1A4" "ENSG00000115902" "6509"
## [164,] "hsa-let-7i-3p" "SLC1A4" "ENSG00000115902" "6509"
## [165,] "hsa-miR-1-3p" "SLC1A4" "ENSG00000115902" "6509"
## [166,] "hsa-miR-106b-3p" "SLC1A4" "ENSG00000115902" "6509"
## [167,] "hsa-let-7a-5p" "GRAMD4" "ENSG00000075240" "23151"
## [168,] "hsa-let-7b-5p" "GRAMD4" "ENSG00000075240" "23151"
## [169,] "hsa-let-7e-5p" "GRAMD4" "ENSG00000075240" "23151"
## [170,] "hsa-let-7g-5p" "GRAMD4" "ENSG00000075240" "23151"
## [171,] "hsa-miR-101-3p" "GRAMD4" "ENSG00000075240" "23151"
## [172,] "hsa-miR-103a-3p" "GRAMD4" "ENSG00000075240" "23151"
## [173,] "hsa-miR-106b-3p" "GRAMD4" "ENSG00000075240" "23151"
## [174,] "hsa-miR-105-5p" "SLC44A4" "ENSG00000204385" "80736"
## [175,] "hsa-miR-103a-3p" "SIDT2" "ENSG00000149577" "51092"
## [176,] "hsa-miR-106b-3p" "SIDT2" "ENSG00000149577" "51092"
## [177,] "hsa-let-7a-5p" "KIAA1211" "ENSG00000109265" "57482"
## [178,] "hsa-let-7a-3p" "KIAA1211" "ENSG00000109265" "57482"
## [179,] "hsa-let-7b-5p" "KIAA1211" "ENSG00000109265" "57482"
## [180,] "hsa-let-7e-5p" "KIAA1211" "ENSG00000109265" "57482"
## [181,] "hsa-let-7f-5p" "KIAA1211" "ENSG00000109265" "57482"
## [182,] "hsa-let-7g-5p" "KIAA1211" "ENSG00000109265" "57482"
## [183,] "hsa-miR-101-5p" "KIAA1211" "ENSG00000109265" "57482"
## [184,] "hsa-let-7a-5p" "ZFYVE16" "ENSG00000039319" "9765"
## [185,] "hsa-let-7b-5p" "ZFYVE16" "ENSG00000039319" "9765"
## [186,] "hsa-miR-103a-3p" "ZFYVE16" "ENSG00000039319" "9765"
## [187,] "hsa-miR-100-5p" "ZNF703" "ENSG00000183779" "80139"
## [188,] "hsa-miR-106b-3p" "ZNF703" "ENSG00000183779" "80139"
## [189,] "hsa-let-7f-2-3p" "FOXA1" "ENSG00000129514" "3169"
## [190,] "hsa-let-7i-3p" "FOXA1" "ENSG00000129514" "3169"
## [191,] "hsa-miR-105-5p" "FOXA1" "ENSG00000129514" "3169"
## [192,] "hsa-miR-101-3p" "SYNGR2" "ENSG00000108639" "9144"
## [193,] "hsa-miR-100-5p" "TBL1X" "ENSG00000101849" "6907"
## [194,] "hsa-miR-105-5p" "TBL1X" "ENSG00000101849" "6907"
## [195,] "hsa-let-7a-3p" "SFMBT2" "ENSG00000198879" "57713"
## [196,] "hsa-let-7b-5p" "SFMBT2" "ENSG00000198879" "57713"
## [197,] "hsa-let-7b-3p" "SFMBT2" "ENSG00000198879" "57713"
## [198,] "hsa-let-7f-1-3p" "SFMBT2" "ENSG00000198879" "57713"
## [199,] "hsa-miR-103a-3p" "SFMBT2" "ENSG00000198879" "57713"
## [200,] "hsa-miR-105-5p" "SFMBT2" "ENSG00000198879" "57713"
## [201,] "hsa-let-7i-5p" "NUCB2" "ENSG00000070081" "4925"
## [202,] "hsa-miR-100-5p" "NUCB2" "ENSG00000070081" "4925"
## [203,] "hsa-miR-106b-3p" "NUCB2" "ENSG00000070081" "4925"
## [204,] "hsa-let-7i-5p" "CACNG4" "ENSG00000075461" "27092"
## [205,] "hsa-miR-1-3p" "CACNG4" "ENSG00000075461" "27092"
## [206,] "hsa-let-7b-5p" "DLG3" "ENSG00000082458" "1741"
## [207,] "hsa-let-7e-5p" "DLG3" "ENSG00000082458" "1741"
## [208,] "hsa-miR-105-5p" "LONRF2" "ENSG00000170500" "164832"
## DIANA_microT_CDS EIMMo Microcosm miRDB miRanda PITA rna22 Targetscan
## [1,] 0 1 0 0 1 0 0 0
## [2,] 0 1 0 0 1 0 0 0
## [3,] 0 0 0 0 0 0 1 0
## [4,] 0 1 0 0 0 0 0 0
## [5,] 1 1 0 0 1 0 0 1
## [6,] 1 0 0 0 0 0 0 0
## [7,] 0 1 0 0 0 0 0 0
## [8,] 1 1 0 0 0 0 0 0
## [9,] 0 0 0 0 0 0 1 0
## [10,] 0 0 0 0 1 0 0 0
## [11,] 0 1 0 0 0 0 0 0
## [12,] 0 1 0 0 0 0 0 0
## [13,] 0 0 0 0 1 0 0 0
## [14,] 0 0 0 0 0 0 1 0
## [15,] 0 0 1 0 0 0 0 0
## [16,] 0 0 0 0 0 0 1 0
## [17,] 0 1 0 0 1 0 0 0
## [18,] 0 0 0 0 0 0 1 0
## [19,] 0 0 1 0 0 0 0 0
## [20,] 0 1 0 0 0 0 0 0
## [21,] 0 0 0 0 1 0 0 0
## [22,] 1 0 0 0 0 0 0 0
## [23,] 0 0 0 0 1 0 0 0
## [24,] 0 0 0 0 0 0 1 0
## [25,] 0 0 0 0 0 0 0 0
## [26,] 0 0 0 0 1 0 0 0
## [27,] 0 0 0 0 0 0 0 1
## [28,] 0 1 0 0 0 0 0 0
## [29,] 0 0 1 0 0 0 0 0
## [30,] 0 1 0 0 0 0 0 0
## [31,] 0 0 0 0 1 0 0 0
## [32,] 1 1 1 0 1 0 0 0
## [33,] 1 1 0 0 0 0 0 0
## [34,] 0 0 0 0 0 1 0 0
## [35,] 0 1 0 0 0 0 0 0
## [36,] 0 1 0 0 0 0 1 0
## [37,] 1 1 1 0 0 0 0 0
## [38,] 0 1 1 0 0 0 0 0
## [39,] 0 1 0 0 1 0 0 0
## [40,] 0 1 0 0 0 0 0 0
## [41,] 0 1 0 0 1 0 0 0
## [42,] 0 0 0 0 0 0 1 0
## [43,] 1 1 0 0 1 0 0 0
## [44,] 0 1 0 0 0 0 1 0
## [45,] 0 1 0 0 0 0 0 0
## [46,] 1 1 0 0 0 0 1 0
## [47,] 0 1 0 0 0 0 1 0
## [48,] 0 1 0 0 0 0 0 0
## [49,] 0 1 0 0 0 0 0 0
## [50,] 0 1 0 0 0 0 0 0
## [51,] 0 1 0 1 1 1 0 0
## [52,] 1 0 0 0 1 0 0 0
## [53,] 0 0 0 0 0 0 1 0
## [54,] 0 0 1 0 0 0 0 0
## [55,] 0 1 0 0 0 0 0 0
## [56,] 0 1 0 0 0 0 0 0
## [57,] 0 1 0 0 0 0 0 0
## [58,] 0 0 0 0 1 0 0 0
## [59,] 1 1 0 0 1 0 0 0
## [60,] 0 0 0 0 1 0 0 0
## [61,] 0 1 0 0 0 0 0 0
## [62,] 0 1 0 0 0 0 0 0
## [63,] 0 1 0 0 1 0 0 0
## [64,] 0 1 0 0 1 0 0 0
## [65,] 0 1 0 0 0 0 0 0
## [66,] 0 0 0 0 0 0 1 0
## [67,] 0 0 0 0 1 0 0 0
## [68,] 0 1 0 0 0 0 0 0
## [69,] 0 1 0 0 0 0 0 0
## [70,] 0 1 0 0 0 0 0 0
## [71,] 0 1 0 0 0 0 0 0
## [72,] 0 0 0 0 1 0 0 0
## [73,] 1 0 0 0 0 0 0 1
## [74,] 0 1 0 0 0 0 0 0
## [75,] 0 1 0 0 1 0 0 0
## [76,] 1 1 1 1 1 0 0 0
## [77,] 0 0 0 0 1 0 0 0
## [78,] 0 1 0 0 0 0 0 0
## [79,] 0 0 0 0 0 0 1 0
## [80,] 1 1 0 0 0 0 0 1
## [81,] 1 1 0 0 1 0 0 1
## [82,] 0 0 0 0 1 0 0 0
## [83,] 0 1 0 0 0 0 0 0
## [84,] 0 1 0 0 0 0 0 0
## [85,] 0 1 0 0 0 0 0 0
## [86,] 0 1 0 0 0 0 0 0
## [87,] 0 0 1 0 0 0 0 0
## [88,] 1 1 0 0 1 0 0 0
## [89,] 0 1 0 0 0 0 0 0
## [90,] 0 1 0 0 0 0 0 0
## [91,] 0 1 0 0 0 0 0 0
## [92,] 0 1 0 0 1 0 0 0
## [93,] 0 1 0 0 0 0 0 0
## [94,] 0 0 1 0 0 0 0 0
## [95,] 0 1 0 0 0 0 0 0
## [96,] 0 1 0 0 0 0 0 0
## [97,] 0 1 0 0 1 0 0 0
## [98,] 0 1 1 0 1 0 0 0
## [99,] 0 0 0 0 0 0 0 0
## [100,] 0 1 0 0 0 0 0 1
## [101,] 0 0 1 0 0 0 0 0
## [102,] 0 0 1 0 0 0 0 0
## [103,] 0 0 0 0 0 0 1 0
## [104,] 0 0 1 0 0 0 0 0
## [105,] 0 0 0 0 0 0 0 0
## [106,] 0 0 0 0 0 0 1 0
## [107,] 0 0 0 0 0 0 1 0
## [108,] 0 1 0 0 0 0 0 0
## [109,] 0 0 0 0 0 0 1 0
## [110,] 0 1 0 0 0 0 0 0
## [111,] 0 0 1 0 0 0 0 0
## [112,] 0 1 0 0 0 0 0 0
## [113,] 0 1 0 0 0 0 0 0
## [114,] 0 0 0 0 0 0 1 0
## [115,] 0 0 0 0 0 0 1 0
## [116,] 0 1 0 0 0 0 0 1
## [117,] 1 1 1 0 1 0 0 0
## [118,] 0 0 1 0 0 0 0 0
## [119,] 0 1 1 0 1 0 0 0
## [120,] 0 1 0 0 0 0 0 0
## [121,] 0 1 0 0 0 0 0 0
## [122,] 0 1 0 0 0 0 0 0
## [123,] 0 1 0 0 0 0 0 0
## [124,] 0 1 0 0 0 0 0 0
## [125,] 0 0 0 0 1 0 0 0
## [126,] 0 0 0 0 1 0 0 0
## [127,] 0 0 0 0 1 0 0 0
## [128,] 1 1 0 1 1 0 0 0
## [129,] 0 1 0 0 0 0 0 0
## [130,] 1 0 0 0 0 0 0 0
## [131,] 1 0 0 0 0 0 0 0
## [132,] 0 1 0 0 0 0 0 0
## [133,] 0 1 0 0 0 0 1 0
## [134,] 0 1 0 0 0 0 0 0
## [135,] 0 1 0 0 0 0 0 0
## [136,] 0 1 0 0 0 0 0 0
## [137,] 0 1 0 0 0 0 0 0
## [138,] 0 1 0 0 0 0 0 0
## [139,] 0 1 0 0 0 0 0 0
## [140,] 1 0 0 0 0 0 0 1
## [141,] 0 0 0 0 1 0 0 0
## [142,] 1 1 0 0 1 1 0 0
## [143,] 1 1 0 0 1 0 0 0
## [144,] 1 1 0 0 1 0 0 0
## [145,] 0 1 0 0 0 0 0 0
## [146,] 1 0 0 0 0 0 0 0
## [147,] 1 0 0 0 0 0 0 0
## [148,] 1 0 1 0 0 0 0 0
## [149,] 1 0 0 0 0 0 0 0
## [150,] 0 0 0 0 0 0 1 0
## [151,] 1 0 0 0 0 0 0 0
## [152,] 1 0 0 0 1 0 0 0
## [153,] 0 0 0 0 0 0 1 0
## [154,] 1 1 0 0 0 0 0 1
## [155,] 0 1 0 0 0 0 0 0
## [156,] 0 1 0 0 0 0 0 0
## [157,] 0 1 0 0 0 0 0 0
## [158,] 0 1 0 0 1 1 0 1
## [159,] 0 0 0 0 1 0 0 0
## [160,] 1 1 0 0 1 0 0 0
## [161,] 1 1 0 0 0 0 0 0
## [162,] 0 1 0 0 0 0 0 0
## [163,] 1 1 0 0 1 1 0 0
## [164,] 0 1 0 0 0 0 1 0
## [165,] 0 1 0 0 0 0 0 0
## [166,] 0 0 0 0 0 0 1 0
## [167,] 0 1 0 0 0 0 0 0
## [168,] 0 1 0 0 0 0 0 0
## [169,] 0 1 0 0 0 0 0 0
## [170,] 0 1 0 0 0 0 0 0
## [171,] 1 1 0 0 1 1 0 1
## [172,] 0 1 0 0 0 0 0 0
## [173,] 0 1 0 0 0 0 0 0
## [174,] 0 1 0 0 0 0 0 0
## [175,] 1 1 0 0 0 0 0 0
## [176,] 0 1 0 0 0 0 0 0
## [177,] 0 1 0 0 0 0 0 1
## [178,] 0 1 0 0 1 0 0 0
## [179,] 0 1 0 0 0 0 0 0
## [180,] 0 1 0 0 0 0 0 0
## [181,] 0 1 0 0 0 0 0 0
## [182,] 0 1 0 0 0 0 0 0
## [183,] 0 0 0 0 1 0 0 0
## [184,] 1 1 0 0 1 1 0 0
## [185,] 1 1 0 0 1 1 0 0
## [186,] 0 0 0 1 1 0 0 0
## [187,] 0 0 1 0 0 0 0 0
## [188,] 0 0 1 0 0 0 0 0
## [189,] 1 0 0 0 1 0 0 0
## [190,] 0 1 0 0 0 0 0 0
## [191,] 1 0 0 0 1 0 0 0
## [192,] 0 0 0 0 1 0 0 0
## [193,] 0 1 0 0 0 0 0 0
## [194,] 1 1 0 0 1 0 0 0
## [195,] 1 0 0 0 0 0 0 0
## [196,] 1 1 0 0 0 0 0 0
## [197,] 1 0 0 0 0 0 0 0
## [198,] 1 0 0 0 0 0 0 0
## [199,] 1 1 0 0 0 0 0 0
## [200,] 1 1 0 0 0 0 0 0
## [201,] 1 0 0 0 0 0 0 0
## [202,] 0 0 1 0 0 0 0 0
## [203,] 0 0 0 0 1 0 0 0
## [204,] 0 1 0 0 1 1 0 0
## [205,] 1 1 0 0 1 0 0 0
## [206,] 0 0 0 0 0 0 1 0
## [207,] 0 0 0 0 0 0 1 0
## [208,] 1 1 0 0 0 0 0 0
## Sum miRecords miRTarBase Validate Correlation( 0 )
## [1,] 2 0 0 "FALSE" "-0.00469329458275759"
## [2,] 2 0 0 "FALSE" "-0.026803017193859"
## [3,] 1 0 0 "FALSE" "-0.160745567601311"
## [4,] 1 0 0 "FALSE" "-0.111964048541342"
## [5,] 4 0 0 "FALSE" "-0.101357243121489"
## [6,] 1 0 0 "FALSE" "-0.0138595925653847"
## [7,] 1 0 0 "FALSE" "-0.0493985280901175"
## [8,] 2 0 0 "FALSE" "-0.0129238223686879"
## [9,] 1 0 0 "FALSE" "-0.0665867533017747"
## [10,] 1 0 0 "FALSE" "-0.0564326046509687"
## [11,] 1 0 0 "FALSE" "-0.0459942601748237"
## [12,] 1 0 0 "FALSE" "-0.0736721307003247"
## [13,] 1 0 0 "FALSE" "-0.0247048756048784"
## [14,] 1 0 0 "FALSE" "-0.0282557589021449"
## [15,] 1 0 0 "FALSE" "-0.139497841212745"
## [16,] 1 0 0 "FALSE" "-0.202114297419076"
## [17,] 2 0 0 "FALSE" "-0.0340419828768836"
## [18,] 1 0 0 "FALSE" "-0.173814257426519"
## [19,] 1 0 0 "FALSE" "-0.0377887870473492"
## [20,] 1 0 0 "FALSE" "-0.00437566645359563"
## [21,] 1 0 0 "FALSE" "-0.0690182848141104"
## [22,] 1 0 0 "FALSE" "-0.192730189701922"
## [23,] 1 0 0 "FALSE" "-0.124900788830998"
## [24,] 1 0 0 "FALSE" "-0.0746142430648831"
## [25,] 0 0 1 "TRUE" "-0.10602416731452"
## [26,] 1 0 0 "FALSE" "-0.0344292287371299"
## [27,] 1 0 0 "FALSE" "-0.0785143844421945"
## [28,] 1 0 0 "FALSE" "-0.0410779417225139"
## [29,] 1 0 0 "FALSE" "-0.0454305279633042"
## [30,] 1 0 0 "FALSE" "-0.0349988603196793"
## [31,] 1 0 0 "FALSE" "-0.0141626858752407"
## [32,] 4 0 0 "FALSE" "-0.0822283193088585"
## [33,] 2 0 0 "FALSE" "-0.0604113554871089"
## [34,] 1 0 0 "FALSE" "-0.0203223156891843"
## [35,] 1 0 0 "FALSE" "-0.115734682603499"
## [36,] 2 0 0 "FALSE" "-0.00432212791596763"
## [37,] 3 0 0 "FALSE" "-0.0534159788289955"
## [38,] 2 0 0 "FALSE" "-0.246049858460371"
## [39,] 2 0 0 "FALSE" "-0.0071521882579686"
## [40,] 1 0 0 "FALSE" "-0.100898169242734"
## [41,] 2 0 0 "FALSE" "-0.00200040458554424"
## [42,] 1 0 0 "FALSE" "-0.169642024353886"
## [43,] 3 0 0 "FALSE" "-0.0148017844400933"
## [44,] 2 0 0 "FALSE" "-0.0732159489190473"
## [45,] 1 0 0 "FALSE" "-0.13518772101538"
## [46,] 3 0 0 "FALSE" "-0.0390888970943003"
## [47,] 2 0 0 "FALSE" "-0.0273816812836608"
## [48,] 1 0 0 "FALSE" "-0.0157707076358428"
## [49,] 1 0 0 "FALSE" "-0.0900948416232156"
## [50,] 1 0 0 "FALSE" "-0.155527063583308"
## [51,] 4 0 0 "FALSE" "-0.0173644681089988"
## [52,] 2 0 0 "FALSE" "-0.079831022998766"
## [53,] 1 0 0 "FALSE" "-0.00255998389069238"
## [54,] 1 0 0 "FALSE" "-0.0817444527295079"
## [55,] 1 0 0 "FALSE" "-0.0435133887663125"
## [56,] 1 0 0 "FALSE" "-0.0648260542173642"
## [57,] 1 0 0 "FALSE" "-0.111139803499355"
## [58,] 1 0 0 "FALSE" "-0.0260413357680768"
## [59,] 3 0 0 "FALSE" "-0.0163612525393968"
## [60,] 1 0 0 "FALSE" "-0.0695257974504453"
## [61,] 1 0 0 "FALSE" "-0.0412623460405872"
## [62,] 1 0 0 "FALSE" "-0.0195641118842683"
## [63,] 2 0 0 "FALSE" "-0.00238088236483886"
## [64,] 2 0 0 "FALSE" "-0.0351031159735516"
## [65,] 1 0 0 "FALSE" "-0.0765302572779514"
## [66,] 1 0 0 "FALSE" "-0.0222647475081597"
## [67,] 1 0 0 "FALSE" "-0.0376332495812914"
## [68,] 1 0 0 "FALSE" "-0.0584480443897348"
## [69,] 1 0 1 "TRUE" "-0.0351889800902353"
## [70,] 1 0 0 "FALSE" "-0.0828608450534563"
## [71,] 1 0 0 "FALSE" "-0.0249917822697364"
## [72,] 1 0 0 "FALSE" "-0.0245841663095478"
## [73,] 2 0 0 "FALSE" "-0.0408393201437719"
## [74,] 1 0 0 "FALSE" "-0.00472945993817595"
## [75,] 2 0 0 "FALSE" "-0.108476180046981"
## [76,] 5 0 0 "FALSE" "-0.0716325467108868"
## [77,] 1 0 0 "FALSE" "-0.0576418474845019"
## [78,] 1 0 0 "FALSE" "-0.00970440394200319"
## [79,] 1 0 0 "FALSE" "-0.0830020201853157"
## [80,] 3 0 0 "FALSE" "-0.054160466135176"
## [81,] 4 0 0 "FALSE" "-0.0271760407350081"
## [82,] 1 0 0 "FALSE" "-0.0358427677256584"
## [83,] 1 0 0 "FALSE" "-0.058034455549039"
## [84,] 1 0 0 "FALSE" "-0.0429066437295362"
## [85,] 1 0 0 "FALSE" "-0.130449896054702"
## [86,] 1 0 0 "FALSE" "-0.151273635131331"
## [87,] 1 0 0 "FALSE" "-0.039744653296719"
## [88,] 3 0 0 "FALSE" "-0.0451579052452179"
## [89,] 1 0 0 "FALSE" "-0.0299938982569402"
## [90,] 1 0 0 "FALSE" "-0.0950125795664926"
## [91,] 1 0 0 "FALSE" "-0.20116287467963"
## [92,] 2 0 0 "FALSE" "-0.219314853824572"
## [93,] 1 0 0 "FALSE" "-0.115977183999841"
## [94,] 1 0 0 "FALSE" "-0.104332959579403"
## [95,] 1 0 0 "FALSE" "-0.107095725822984"
## [96,] 1 0 0 "FALSE" "-0.151368320928965"
## [97,] 2 0 0 "FALSE" "-0.128497771519202"
## [98,] 3 0 0 "FALSE" "-0.123583054545899"
## [99,] 0 0 1 "TRUE" "-0.0390063073534936"
## [100,] 2 0 0 "FALSE" "-0.056173338446142"
## [101,] 1 0 0 "FALSE" "-0.097656761169652"
## [102,] 1 0 0 "FALSE" "-0.257021654065956"
## [103,] 1 0 0 "FALSE" "-0.0690016072561739"
## [104,] 1 0 0 "FALSE" "-0.0150605613671584"
## [105,] 0 0 1 "TRUE" "-0.18124075540884"
## [106,] 1 0 0 "FALSE" "-0.0101757786578789"
## [107,] 1 0 0 "FALSE" "-0.0331220298035206"
## [108,] 1 0 0 "FALSE" "-0.00394057958050813"
## [109,] 1 0 0 "FALSE" "-0.0145831749276612"
## [110,] 1 0 0 "FALSE" "-0.0561175516080145"
## [111,] 1 0 0 "FALSE" "-0.119570155944897"
## [112,] 1 0 0 "FALSE" "-0.058225569486375"
## [113,] 1 0 0 "FALSE" "-0.120724326456088"
## [114,] 1 0 0 "FALSE" "-0.0680166897997314"
## [115,] 1 0 0 "FALSE" "-0.049807040142193"
## [116,] 2 0 0 "FALSE" "-0.105681085626406"
## [117,] 4 0 0 "FALSE" "-0.119231337341744"
## [118,] 1 0 0 "FALSE" "-0.0938743003752882"
## [119,] 3 0 0 "FALSE" "-0.226685031063792"
## [120,] 1 0 0 "FALSE" "-0.070813384908843"
## [121,] 1 0 0 "FALSE" "-0.0602364327741436"
## [122,] 1 0 0 "FALSE" "-0.0296976569649153"
## [123,] 1 0 0 "FALSE" "-0.146829408454961"
## [124,] 1 0 0 "FALSE" "-0.126825052930146"
## [125,] 1 0 0 "FALSE" "-0.192139087005256"
## [126,] 1 0 0 "FALSE" "-0.245961400752861"
## [127,] 1 0 0 "FALSE" "-0.160354054590504"
## [128,] 4 0 0 "FALSE" "-0.00817700606888721"
## [129,] 1 0 0 "FALSE" "-0.166165736860862"
## [130,] 1 0 0 "FALSE" "-0.020591098341203"
## [131,] 1 0 0 "FALSE" "-0.156550368224252"
## [132,] 1 0 0 "FALSE" "-0.00340707573051329"
## [133,] 2 0 0 "FALSE" "-0.163885469526453"
## [134,] 1 0 0 "FALSE" "-0.115324291439957"
## [135,] 1 0 0 "FALSE" "-0.202342752181346"
## [136,] 1 0 0 "FALSE" "-0.155479324387455"
## [137,] 1 0 0 "FALSE" "-0.0540145088887996"
## [138,] 1 0 0 "FALSE" "-0.0224334977028391"
## [139,] 1 0 0 "FALSE" "-0.104625832313338"
## [140,] 2 0 0 "FALSE" "-0.108540941652119"
## [141,] 1 0 0 "FALSE" "-0.0766236447481583"
## [142,] 4 0 0 "FALSE" "-0.125361353868268"
## [143,] 3 0 0 "FALSE" "-0.0604414780172276"
## [144,] 3 0 0 "FALSE" "-0.0739512843673057"
## [145,] 1 0 0 "FALSE" "-0.145557019847801"
## [146,] 1 0 0 "FALSE" "-0.0440783400191794"
## [147,] 1 0 0 "FALSE" "-0.0344401414239305"
## [148,] 2 0 0 "FALSE" "-0.113223203527758"
## [149,] 1 0 1 "TRUE" "-0.0616939347447661"
## [150,] 1 0 0 "FALSE" "-0.107974718298354"
## [151,] 1 0 0 "FALSE" "-0.00569716655807841"
## [152,] 2 0 0 "FALSE" "-0.0256859656450377"
## [153,] 1 0 0 "FALSE" "-0.00331831710821351"
## [154,] 3 0 0 "FALSE" "-0.0226451835679747"
## [155,] 1 0 0 "FALSE" "-0.0833785911473021"
## [156,] 1 0 0 "FALSE" "-0.204935297589399"
## [157,] 1 0 0 "FALSE" "-0.00491598822446839"
## [158,] 4 0 1 "TRUE" "-0.0625430156898712"
## [159,] 1 0 0 "FALSE" "-0.0302015522570322"
## [160,] 3 0 0 "FALSE" "-0.0177008472006125"
## [161,] 2 0 0 "FALSE" "-0.0694300616335995"
## [162,] 1 0 0 "FALSE" "-0.104518550024666"
## [163,] 4 0 0 "FALSE" "-0.0121717274157986"
## [164,] 2 0 0 "FALSE" "-0.164940310465331"
## [165,] 1 0 0 "FALSE" "-0.00350777845481623"
## [166,] 1 0 0 "FALSE" "-0.0656903184542091"
## [167,] 1 0 0 "FALSE" "-0.0122239422959904"
## [168,] 1 0 0 "FALSE" "-0.0696453990415214"
## [169,] 1 0 0 "FALSE" "-0.156265954349996"
## [170,] 1 0 0 "FALSE" "-0.0150296203705942"
## [171,] 5 0 0 "FALSE" "-0.0201860012584755"
## [172,] 1 0 0 "FALSE" "-0.0832663530915705"
## [173,] 1 0 0 "FALSE" "-0.0118018214239647"
## [174,] 1 0 0 "FALSE" "-0.0456494530357291"
## [175,] 2 0 0 "FALSE" "-0.0171192541550353"
## [176,] 1 0 0 "FALSE" "-0.182969916489946"
## [177,] 2 0 0 "FALSE" "-0.078930113173772"
## [178,] 2 0 0 "FALSE" "-0.0245626961130111"
## [179,] 1 0 0 "FALSE" "-0.109259974409534"
## [180,] 1 0 0 "FALSE" "-0.0678909792151139"
## [181,] 1 0 0 "FALSE" "-0.0353851406857655"
## [182,] 1 0 0 "FALSE" "-0.0264400615492675"
## [183,] 1 0 0 "FALSE" "-0.042513000852672"
## [184,] 4 0 0 "FALSE" "-0.0180079166104844"
## [185,] 4 0 0 "FALSE" "-0.0160010452631988"
## [186,] 2 0 0 "FALSE" "-0.0557495511343818"
## [187,] 1 0 0 "FALSE" "-0.162973238495035"
## [188,] 1 0 0 "FALSE" "-0.093420459285713"
## [189,] 2 0 0 "FALSE" "-0.0207866845099378"
## [190,] 1 0 0 "FALSE" "-0.0861313367496941"
## [191,] 2 0 0 "FALSE" "-0.147112989994077"
## [192,] 1 0 0 "FALSE" "-0.0571812656679315"
## [193,] 1 0 0 "FALSE" "-0.0899548646481515"
## [194,] 3 0 0 "FALSE" "-0.0921118130054476"
## [195,] 1 0 0 "FALSE" "-0.156938750282532"
## [196,] 2 0 0 "FALSE" "-0.0737659137840028"
## [197,] 1 0 0 "FALSE" "-0.0314932092951809"
## [198,] 1 0 0 "FALSE" "-0.037838514663787"
## [199,] 2 0 0 "FALSE" "-0.00126378564005593"
## [200,] 2 0 0 "FALSE" "-0.0325585079645554"
## [201,] 1 0 1 "TRUE" "-0.0719658449360214"
## [202,] 1 0 0 "FALSE" "-0.00099687991162299"
## [203,] 1 0 0 "FALSE" "-0.130902782548756"
## [204,] 3 0 0 "FALSE" "-0.0604463809017228"
## [205,] 3 0 0 "FALSE" "-0.0448347830995044"
## [206,] 1 0 0 "FALSE" "-0.158427805002612"
## [207,] 1 0 0 "FALSE" "-0.128727704613367"
## [208,] 2 0 0 "FALSE" "-0.131492575727561"
## logratio(miRNA) P-adjust(miRNA) mean_case(miRNA)
## [1,] "0.260930386290323" "0.246997134412268" "2.71811076129032"
## [2,] "0.12843422015233" "0.524207090686478" "1.98063033209677"
## [3,] "-0.459609872320788" "0.0268114568476553" "1.12506766529032"
## [4,] "-0.00435579659498231" "0.975457378262621" "10.5471040645161"
## [5,] "0.395326186827957" "0.00801637073812844" "11.2174993951613"
## [6,] "-0.297657890803763" "0.291928618591068" "0.663438186612903"
## [7,] "-0.0418024902374552" "0.884721897720132" "1.79228402129032"
## [8,] "0.313214337043011" "0.432025621108341" "3.60085180370968"
## [9,] "-0.459609872320788" "0.0268114568476553" "1.12506766529032"
## [10,] "0.0133768047777778" "0.972760477429415" "0.7742908005"
## [11,] "-0.00435579659498231" "0.975457378262621" "10.5471040645161"
## [12,] "-0.143935879032258" "0.325068307671028" "11.5634993709677"
## [13,] "0.260930386290323" "0.246997134412268" "2.71811076129032"
## [14,] "-0.143935879032258" "0.325068307671028" "11.5634993709677"
## [15,] "-0.0418024902374552" "0.884721897720132" "1.79228402129032"
## [16,] "-0.459609872320788" "0.0268114568476553" "1.12506766529032"
## [17,] "0.395326186827957" "0.00801637073812844" "11.2174993951613"
## [18,] "-0.459609872320788" "0.0268114568476553" "1.12506766529032"
## [19,] "-0.143935879032258" "0.325068307671028" "11.5634993709677"
## [20,] "0.313214337043011" "0.432025621108341" "3.60085180370968"
## [21,] "0.75106936469534" "0.000849277717515689" "13.9084079758065"
## [22,] "-0.00435579659498231" "0.975457378262621" "10.5471040645161"
## [23,] "-0.25095749767025" "0.19228460871898" "9.24812269677419"
## [24,] "0.75106936469534" "0.000849277717515689" "13.9084079758065"
## [25,] "0.483138913530466" "0.00459245770983532" "10.6757934274194"
## [26,] "-0.143935879032258" "0.325068307671028" "11.5634993709677"
## [27,] "0.313214337043011" "0.432025621108341" "3.60085180370968"
## [28,] "0.395326186827957" "0.00801637073812844" "11.2174993951613"
## [29,] "0.5615149596819" "0.00247854366880183" "2.34753278870968"
## [30,] "-0.459609872320788" "0.0268114568476553" "1.12506766529032"
## [31,] "-0.25095749767025" "0.19228460871898" "9.24812269677419"
## [32,] "-0.459609872320788" "0.0268114568476553" "1.12506766529032"
## [33,] "0.483138913530466" "0.00459245770983532" "10.6757934274194"
## [34,] "-0.297657890803763" "0.291928618591068" "0.663438186612903"
## [35,] "-0.459609872320788" "0.0268114568476553" "1.12506766529032"
## [36,] "-0.459609872320788" "0.0268114568476553" "1.12506766529032"
## [37,] "-0.297657890803763" "0.291928618591068" "0.663438186612903"
## [38,] "-0.459609872320788" "0.0268114568476553" "1.12506766529032"
## [39,] "-0.00435579659498231" "0.975457378262621" "10.5471040645161"
## [40,] "-0.0418024902374552" "0.884721897720132" "1.79228402129032"
## [41,] "-0.297657890803763" "0.291928618591068" "0.663438186612903"
## [42,] "-0.459609872320788" "0.0268114568476553" "1.12506766529032"
## [43,] "-0.297657890803763" "0.291928618591068" "0.663438186612903"
## [44,] "0.393125512992832" "0.0358146963292343" "14.1567251935484"
## [45,] "0.75106936469534" "0.000849277717515689" "13.9084079758065"
## [46,] "-0.00435579659498231" "0.975457378262621" "10.5471040645161"
## [47,] "0.483138913530466" "0.00459245770983532" "10.6757934274194"
## [48,] "0.263929851254481" "0.184062819074797" "13.7247531290323"
## [49,] "0.141142457437276" "0.432025621108341" "11.9694836935484"
## [50,] "-0.143935879032258" "0.325068307671028" "11.5634993709677"
## [51,] "-0.25095749767025" "0.19228460871898" "9.24812269677419"
## [52,] "0.0133768047777778" "0.972760477429415" "0.7742908005"
## [53,] "-0.143935879032258" "0.325068307671028" "11.5634993709677"
## [54,] "-0.25095749767025" "0.19228460871898" "9.24812269677419"
## [55,] "0.260930386290323" "0.246997134412268" "2.71811076129032"
## [56,] "0.12843422015233" "0.524207090686478" "1.98063033209677"
## [57,] "0.0133768047777778" "0.972760477429415" "0.7742908005"
## [58,] "-0.297657890803763" "0.291928618591068" "0.663438186612903"
## [59,] "0.0133768047777778" "0.972760477429415" "0.7742908005"
## [60,] "0.0133768047777778" "0.972760477429415" "0.7742908005"
## [61,] "0.75106936469534" "0.000849277717515689" "13.9084079758065"
## [62,] "0.141142457437276" "0.432025621108341" "11.9694836935484"
## [63,] "0.260930386290323" "0.246997134412268" "2.71811076129032"
## [64,] "0.12843422015233" "0.524207090686478" "1.98063033209677"
## [65,] "0.0133768047777778" "0.972760477429415" "0.7742908005"
## [66,] "-0.297657890803763" "0.291928618591068" "0.663438186612903"
## [67,] "0.153662880080645" "0.436254579533941" "2.87293672258065"
## [68,] "-0.297657890803763" "0.291928618591068" "0.663438186612903"
## [69,] "0.75106936469534" "0.000849277717515689" "13.9084079758065"
## [70,] "0.483138913530466" "0.00459245770983532" "10.6757934274194"
## [71,] "0.141142457437276" "0.432025621108341" "11.9694836935484"
## [72,] "0.313214337043011" "0.432025621108341" "3.60085180370968"
## [73,] "0.355484058870967" "0.0309691965546709" "9.51399518387097"
## [74,] "0.260930386290323" "0.246997134412268" "2.71811076129032"
## [75,] "0.12843422015233" "0.524207090686478" "1.98063033209677"
## [76,] "0.0133768047777778" "0.972760477429415" "0.7742908005"
## [77,] "-0.459609872320788" "0.0268114568476553" "1.12506766529032"
## [78,] "-0.459609872320788" "0.0268114568476553" "1.12506766529032"
## [79,] "0.153662880080645" "0.436254579533941" "2.87293672258065"
## [80,] "0.313214337043011" "0.432025621108341" "3.60085180370968"
## [81,] "0.355484058870967" "0.0309691965546709" "9.51399518387097"
## [82,] "-0.459609872320788" "0.0268114568476553" "1.12506766529032"
## [83,] "-0.459609872320788" "0.0268114568476553" "1.12506766529032"
## [84,] "0.393125512992832" "0.0358146963292343" "14.1567251935484"
## [85,] "0.75106936469534" "0.000849277717515689" "13.9084079758065"
## [86,] "0.313214337043011" "0.432025621108341" "3.60085180370968"
## [87,] "-0.459609872320788" "0.0268114568476553" "1.12506766529032"
## [88,] "0.0133768047777778" "0.972760477429415" "0.7742908005"
## [89,] "-0.0418024902374552" "0.884721897720132" "1.79228402129032"
## [90,] "-0.459609872320788" "0.0268114568476553" "1.12506766529032"
## [91,] "0.393125512992832" "0.0358146963292343" "14.1567251935484"
## [92,] "0.75106936469534" "0.000849277717515689" "13.9084079758065"
## [93,] "-0.00435579659498231" "0.975457378262621" "10.5471040645161"
## [94,] "0.153662880080645" "0.436254579533941" "2.87293672258065"
## [95,] "0.483138913530466" "0.00459245770983532" "10.6757934274194"
## [96,] "0.263929851254481" "0.184062819074797" "13.7247531290323"
## [97,] "0.141142457437276" "0.432025621108341" "11.9694836935484"
## [98,] "-0.143935879032258" "0.325068307671028" "11.5634993709677"
## [99,] "0.313214337043011" "0.432025621108341" "3.60085180370968"
## [100,] "0.395326186827957" "0.00801637073812844" "11.2174993951613"
## [101,] "0.393125512992832" "0.0358146963292343" "14.1567251935484"
## [102,] "0.75106936469534" "0.000849277717515689" "13.9084079758065"
## [103,] "0.153662880080645" "0.436254579533941" "2.87293672258065"
## [104,] "0.263929851254481" "0.184062819074797" "13.7247531290323"
## [105,] "0.313214337043011" "0.432025621108341" "3.60085180370968"
## [106,] "-0.0418024902374552" "0.884721897720132" "1.79228402129032"
## [107,] "0.579902692123656" "0.00107084889770573" "2.45416823629032"
## [108,] "0.395326186827957" "0.00801637073812844" "11.2174993951613"
## [109,] "0.313214337043011" "0.432025621108341" "3.60085180370968"
## [110,] "-0.459609872320788" "0.0268114568476553" "1.12506766529032"
## [111,] "-0.459609872320788" "0.0268114568476553" "1.12506766529032"
## [112,] "0.0133768047777778" "0.972760477429415" "0.7742908005"
## [113,] "0.395326186827957" "0.00801637073812844" "11.2174993951613"
## [114,] "-0.0418024902374552" "0.884721897720132" "1.79228402129032"
## [115,] "0.579902692123656" "0.00107084889770573" "2.45416823629032"
## [116,] "0.313214337043011" "0.432025621108341" "3.60085180370968"
## [117,] "-0.459609872320788" "0.0268114568476553" "1.12506766529032"
## [118,] "-0.0418024902374552" "0.884721897720132" "1.79228402129032"
## [119,] "-0.459609872320788" "0.0268114568476553" "1.12506766529032"
## [120,] "0.395326186827957" "0.00801637073812844" "11.2174993951613"
## [121,] "-0.459609872320788" "0.0268114568476553" "1.12506766529032"
## [122,] "-0.00435579659498231" "0.975457378262621" "10.5471040645161"
## [123,] "-0.143935879032258" "0.325068307671028" "11.5634993709677"
## [124,] "-0.0418024902374552" "0.884721897720132" "1.79228402129032"
## [125,] "0.260930386290323" "0.246997134412268" "2.71811076129032"
## [126,] "0.12843422015233" "0.524207090686478" "1.98063033209677"
## [127,] "-0.297657890803763" "0.291928618591068" "0.663438186612903"
## [128,] "-0.297657890803763" "0.291928618591068" "0.663438186612903"
## [129,] "-0.459609872320788" "0.0268114568476553" "1.12506766529032"
## [130,] "0.5615149596819" "0.00247854366880183" "2.34753278870968"
## [131,] "-0.25095749767025" "0.19228460871898" "9.24812269677419"
## [132,] "-0.459609872320788" "0.0268114568476553" "1.12506766529032"
## [133,] "-0.0418024902374552" "0.884721897720132" "1.79228402129032"
## [134,] "0.393125512992832" "0.0358146963292343" "14.1567251935484"
## [135,] "0.75106936469534" "0.000849277717515689" "13.9084079758065"
## [136,] "0.483138913530466" "0.00459245770983532" "10.6757934274194"
## [137,] "0.263929851254481" "0.184062819074797" "13.7247531290323"
## [138,] "0.141142457437276" "0.432025621108341" "11.9694836935484"
## [139,] "0.355484058870967" "0.0309691965546709" "9.51399518387097"
## [140,] "0.395326186827957" "0.00801637073812844" "11.2174993951613"
## [141,] "0.355484058870967" "0.0309691965546709" "9.51399518387097"
## [142,] "-0.297657890803763" "0.291928618591068" "0.663438186612903"
## [143,] "0.260930386290323" "0.246997134412268" "2.71811076129032"
## [144,] "0.12843422015233" "0.524207090686478" "1.98063033209677"
## [145,] "-0.459609872320788" "0.0268114568476553" "1.12506766529032"
## [146,] "0.393125512992832" "0.0358146963292343" "14.1567251935484"
## [147,] "0.542315739964158" "0.00391914122085866" "3.24683051774194"
## [148,] "0.75106936469534" "0.000849277717515689" "13.9084079758065"
## [149,] "0.483138913530466" "0.00459245770983532" "10.6757934274194"
## [150,] "0.5615149596819" "0.00247854366880183" "2.34753278870968"
## [151,] "0.263929851254481" "0.184062819074797" "13.7247531290323"
## [152,] "0.12843422015233" "0.524207090686478" "1.98063033209677"
## [153,] "0.395326186827957" "0.00801637073812844" "11.2174993951613"
## [154,] "0.75106936469534" "0.000849277717515689" "13.9084079758065"
## [155,] "-0.25095749767025" "0.19228460871898" "9.24812269677419"
## [156,] "-0.0418024902374552" "0.884721897720132" "1.79228402129032"
## [157,] "0.260930386290323" "0.246997134412268" "2.71811076129032"
## [158,] "0.313214337043011" "0.432025621108341" "3.60085180370968"
## [159,] "-0.25095749767025" "0.19228460871898" "9.24812269677419"
## [160,] "0.313214337043011" "0.432025621108341" "3.60085180370968"
## [161,] "0.313214337043011" "0.432025621108341" "3.60085180370968"
## [162,] "-0.297657890803763" "0.291928618591068" "0.663438186612903"
## [163,] "-0.143935879032258" "0.325068307671028" "11.5634993709677"
## [164,] "-0.0418024902374552" "0.884721897720132" "1.79228402129032"
## [165,] "0.313214337043011" "0.432025621108341" "3.60085180370968"
## [166,] "-0.459609872320788" "0.0268114568476553" "1.12506766529032"
## [167,] "0.393125512992832" "0.0358146963292343" "14.1567251935484"
## [168,] "0.75106936469534" "0.000849277717515689" "13.9084079758065"
## [169,] "0.483138913530466" "0.00459245770983532" "10.6757934274194"
## [170,] "0.141142457437276" "0.432025621108341" "11.9694836935484"
## [171,] "0.355484058870967" "0.0309691965546709" "9.51399518387097"
## [172,] "0.395326186827957" "0.00801637073812844" "11.2174993951613"
## [173,] "-0.459609872320788" "0.0268114568476553" "1.12506766529032"
## [174,] "-0.297657890803763" "0.291928618591068" "0.663438186612903"
## [175,] "0.395326186827957" "0.00801637073812844" "11.2174993951613"
## [176,] "-0.459609872320788" "0.0268114568476553" "1.12506766529032"
## [177,] "0.393125512992832" "0.0358146963292343" "14.1567251935484"
## [178,] "0.542315739964158" "0.00391914122085866" "3.24683051774194"
## [179,] "0.75106936469534" "0.000849277717515689" "13.9084079758065"
## [180,] "0.483138913530466" "0.00459245770983532" "10.6757934274194"
## [181,] "0.263929851254481" "0.184062819074797" "13.7247531290323"
## [182,] "0.141142457437276" "0.432025621108341" "11.9694836935484"
## [183,] "0.579902692123656" "0.00107084889770573" "2.45416823629032"
## [184,] "0.393125512992832" "0.0358146963292343" "14.1567251935484"
## [185,] "0.75106936469534" "0.000849277717515689" "13.9084079758065"
## [186,] "0.395326186827957" "0.00801637073812844" "11.2174993951613"
## [187,] "-0.25095749767025" "0.19228460871898" "9.24812269677419"
## [188,] "-0.459609872320788" "0.0268114568476553" "1.12506766529032"
## [189,] "0.0133768047777778" "0.972760477429415" "0.7742908005"
## [190,] "-0.0418024902374552" "0.884721897720132" "1.79228402129032"
## [191,] "-0.297657890803763" "0.291928618591068" "0.663438186612903"
## [192,] "0.355484058870967" "0.0309691965546709" "9.51399518387097"
## [193,] "-0.25095749767025" "0.19228460871898" "9.24812269677419"
## [194,] "-0.297657890803763" "0.291928618591068" "0.663438186612903"
## [195,] "0.542315739964158" "0.00391914122085866" "3.24683051774194"
## [196,] "0.75106936469534" "0.000849277717515689" "13.9084079758065"
## [197,] "0.260930386290323" "0.246997134412268" "2.71811076129032"
## [198,] "0.12843422015233" "0.524207090686478" "1.98063033209677"
## [199,] "0.395326186827957" "0.00801637073812844" "11.2174993951613"
## [200,] "-0.297657890803763" "0.291928618591068" "0.663438186612903"
## [201,] "-0.143935879032258" "0.325068307671028" "11.5634993709677"
## [202,] "-0.25095749767025" "0.19228460871898" "9.24812269677419"
## [203,] "-0.459609872320788" "0.0268114568476553" "1.12506766529032"
## [204,] "-0.143935879032258" "0.325068307671028" "11.5634993709677"
## [205,] "0.313214337043011" "0.432025621108341" "3.60085180370968"
## [206,] "0.75106936469534" "0.000849277717515689" "13.9084079758065"
## [207,] "0.483138913530466" "0.00459245770983532" "10.6757934274194"
## [208,] "-0.297657890803763" "0.291928618591068" "0.663438186612903"
## mean_control(miRNA) logratio(gene) P-adjust(gene)
## [1,] "2.457180375" "-0.274279164157706" "0.281564520324039"
## [2,] "1.85219611194444" "-0.274279164157706" "0.281564520324039"
## [3,] "1.58467753761111" "1.40108635589606" "8.14361477201009e-07"
## [4,] "10.5514598611111" "0.78136412939068" "0.0987135836521272"
## [5,] "10.8221732083333" "0.78136412939068" "0.0987135836521272"
## [6,] "0.961096077416667" "0.78136412939068" "0.0987135836521272"
## [7,] "1.83408651152778" "1.87866651555555" "1.82994795998066e-10"
## [8,] "3.28763746666667" "0.0972127002867378" "0.503271933096673"
## [9,] "1.58467753761111" "0.0906114629928325" "0.531674114312941"
## [10,] "0.760913995722222" "0.819136647858423" "2.19655014733162e-06"
## [11,] "10.5514598611111" "1.7955132184319" "6.27250368110013e-07"
## [12,] "11.70743525" "1.7955132184319" "6.27250368110013e-07"
## [13,] "2.457180375" "-0.105646599740144" "0.593239706283949"
## [14,] "11.70743525" "0.164426834256274" "0.271222847223139"
## [15,] "1.83408651152778" "0.164426834256274" "0.271222847223139"
## [16,] "1.58467753761111" "0.645890723118278" "0.074741476439557"
## [17,] "10.8221732083333" "0.150630936514338" "0.439420706609033"
## [18,] "1.58467753761111" "0.746969606577062" "0.000155434840252826"
## [19,] "11.70743525" "-0.066785074435483" "0.749079073583798"
## [20,] "3.28763746666667" "-0.066785074435483" "0.749079073583798"
## [21,] "13.1573386111111" "0.327663989318998" "0.169736522335655"
## [22,] "10.5514598611111" "0.327663989318998" "0.169736522335655"
## [23,] "9.49908019444444" "0.327663989318998" "0.169736522335655"
## [24,] "13.1573386111111" "-0.400548569892473" "0.0632670560653719"
## [25,] "10.1926545138889" "-0.400548569892473" "0.0632670560653719"
## [26,] "11.70743525" "-0.400548569892473" "0.0632670560653719"
## [27,] "3.28763746666667" "-0.400548569892473" "0.0632670560653719"
## [28,] "10.8221732083333" "-0.400548569892473" "0.0632670560653719"
## [29,] "1.78601782902778" "-0.0940064069892461" "0.621866321796862"
## [30,] "1.58467753761111" "-0.0940064069892461" "0.621866321796862"
## [31,] "9.49908019444444" "0.681921928566307" "0.00156729450897665"
## [32,] "1.58467753761111" "0.676254081989248" "0.00369409623615164"
## [33,] "10.1926545138889" "0.165081362293908" "0.41024072512539"
## [34,] "0.961096077416667" "0.165081362293908" "0.41024072512539"
## [35,] "1.58467753761111" "0.816552631550179" "0.00253061523327468"
## [36,] "1.58467753761111" "-0.0221023723207887" "0.890466217213773"
## [37,] "0.961096077416667" "2.16992893517921" "1.41095482197442e-11"
## [38,] "1.58467753761111" "2.16992893517921" "1.41095482197442e-11"
## [39,] "10.5514598611111" "0.595871673933692" "0.0468488370475683"
## [40,] "1.83408651152778" "0.921755124498208" "4.66907829461033e-05"
## [41,] "0.961096077416667" "0.921755124498208" "4.66907829461033e-05"
## [42,] "1.58467753761111" "0.921755124498208" "4.66907829461033e-05"
## [43,] "0.961096077416667" "1.35908654586022" "1.97154136219981e-07"
## [44,] "13.7635996805556" "-0.0689702640681009" "0.774529370564702"
## [45,] "13.1573386111111" "-0.0689702640681009" "0.774529370564702"
## [46,] "10.5514598611111" "-0.0689702640681009" "0.774529370564702"
## [47,] "10.1926545138889" "-0.0689702640681009" "0.774529370564702"
## [48,] "13.4608232777778" "-0.0689702640681009" "0.774529370564702"
## [49,] "11.8283412361111" "-0.0689702640681009" "0.774529370564702"
## [50,] "11.70743525" "-0.0689702640681009" "0.774529370564702"
## [51,] "9.49908019444444" "0.880217813790322" "0.000586725931820622"
## [52,] "0.760913995722222" "2.42536514608423" "1.36168143234451e-11"
## [53,] "11.70743525" "0.653742176137994" "0.000101460941640254"
## [54,] "9.49908019444444" "0.653742176137994" "0.000101460941640254"
## [55,] "2.457180375" "1.04988091651434" "0.000513088481147208"
## [56,] "1.85219611194444" "1.04988091651434" "0.000513088481147208"
## [57,] "0.760913995722222" "1.04988091651434" "0.000513088481147208"
## [58,] "0.961096077416667" "1.04988091651434" "0.000513088481147208"
## [59,] "0.760913995722222" "1.06418007429212" "0.000101460941640254"
## [60,] "0.760913995722222" "0.0701641049372768" "0.673339317627116"
## [61,] "13.1573386111111" "-0.304281804910394" "0.0240460862473942"
## [62,] "11.8283412361111" "-0.304281804910394" "0.0240460862473942"
## [63,] "2.457180375" "-0.0284001860483869" "0.840033441773759"
## [64,] "1.85219611194444" "-0.0284001860483869" "0.840033441773759"
## [65,] "0.760913995722222" "0.315794221200717" "0.0860814380769875"
## [66,] "0.961096077416667" "0.315794221200717" "0.0860814380769875"
## [67,] "2.7192738425" "0.129616373969533" "0.446847057822629"
## [68,] "0.961096077416667" "1.20351927226702" "2.84479739057599e-06"
## [69,] "13.1573386111111" "-0.0794770483333327" "0.635312896541165"
## [70,] "10.1926545138889" "-0.0794770483333327" "0.635312896541165"
## [71,] "11.8283412361111" "-0.0794770483333327" "0.635312896541165"
## [72,] "3.28763746666667" "-0.0794770483333327" "0.635312896541165"
## [73,] "9.158511125" "-0.0794770483333327" "0.635312896541165"
## [74,] "2.457180375" "0.800439898378136" "0.00057597286814142"
## [75,] "1.85219611194444" "0.800439898378136" "0.00057597286814142"
## [76,] "0.760913995722222" "0.800439898378136" "0.00057597286814142"
## [77,] "1.58467753761111" "1.2497375746147" "5.7965482617752e-07"
## [78,] "1.58467753761111" "0.353898591039426" "0.0640225432216981"
## [79,] "2.7192738425" "0.363128905824373" "0.0961216832746928"
## [80,] "3.28763746666667" "0.273498156424731" "0.100856256540663"
## [81,] "9.158511125" "0.0485400201075263" "0.632344165687227"
## [82,] "1.58467753761111" "0.0485400201075263" "0.632344165687227"
## [83,] "1.58467753761111" "0.494635142025089" "0.000534573799705414"
## [84,] "13.7635996805556" "-0.102791621890681" "0.673339317627116"
## [85,] "13.1573386111111" "-0.102791621890681" "0.673339317627116"
## [86,] "3.28763746666667" "-0.102791621890681" "0.673339317627116"
## [87,] "1.58467753761111" "0.3698449615681" "0.0110193216376923"
## [88,] "0.760913995722222" "0.779465988888889" "4.44564910293446e-06"
## [89,] "1.83408651152778" "0.437748235528674" "0.0240460862473942"
## [90,] "1.58467753761111" "0.443096507786738" "0.0385530970099399"
## [91,] "13.7635996805556" "-0.0246945528673823" "0.910752168339817"
## [92,] "13.1573386111111" "-0.0246945528673823" "0.910752168339817"
## [93,] "10.5514598611111" "-0.0246945528673823" "0.910752168339817"
## [94,] "2.7192738425" "-0.0246945528673823" "0.910752168339817"
## [95,] "10.1926545138889" "-0.0246945528673823" "0.910752168339817"
## [96,] "13.4608232777778" "-0.0246945528673823" "0.910752168339817"
## [97,] "11.8283412361111" "-0.0246945528673823" "0.910752168339817"
## [98,] "11.70743525" "-0.0246945528673823" "0.910752168339817"
## [99,] "3.28763746666667" "-0.0246945528673823" "0.910752168339817"
## [100,] "10.8221732083333" "-0.0246945528673823" "0.910752168339817"
## [101,] "13.7635996805556" "-0.498722641487454" "0.0771122458248699"
## [102,] "13.1573386111111" "-0.498722641487454" "0.0771122458248699"
## [103,] "2.7192738425" "-0.498722641487454" "0.0771122458248699"
## [104,] "13.4608232777778" "-0.498722641487454" "0.0771122458248699"
## [105,] "3.28763746666667" "-0.498722641487454" "0.0771122458248699"
## [106,] "1.83408651152778" "0.0183046245340499" "0.940240541374255"
## [107,] "1.87426554416667" "0.0183046245340499" "0.940240541374255"
## [108,] "10.8221732083333" "0.0183046245340499" "0.940240541374255"
## [109,] "3.28763746666667" "0.224791879390681" "0.212354345352163"
## [110,] "1.58467753761111" "0.224791879390681" "0.212354345352163"
## [111,] "1.58467753761111" "1.3043305822491" "2.07386469276697e-06"
## [112,] "0.760913995722222" "0.341289856120072" "0.121257033313765"
## [113,] "10.8221732083333" "0.341289856120072" "0.121257033313765"
## [114,] "1.83408651152778" "-0.105737552652331" "0.206890146000646"
## [115,] "1.87426554416667" "-0.105737552652331" "0.206890146000646"
## [116,] "3.28763746666667" "-0.118856767464158" "0.521457651001563"
## [117,] "1.58467753761111" "0.264439281191757" "0.184845095152697"
## [118,] "1.83408651152778" "1.04312231704301" "9.08341136279668e-06"
## [119,] "1.58467753761111" "1.04312231704301" "9.08341136279668e-06"
## [120,] "10.8221732083333" "-0.16410807750896" "0.415702996804968"
## [121,] "1.58467753761111" "-0.16410807750896" "0.415702996804968"
## [122,] "10.5514598611111" "1.2476072950448" "3.96488583623637e-09"
## [123,] "11.70743525" "1.2476072950448" "3.96488583623637e-09"
## [124,] "1.83408651152778" "1.2476072950448" "3.96488583623637e-09"
## [125,] "2.457180375" "0.283849083288532" "0.128522317430866"
## [126,] "1.85219611194444" "0.283849083288532" "0.128522317430866"
## [127,] "0.961096077416667" "0.283849083288532" "0.128522317430866"
## [128,] "0.961096077416667" "0.152084021379928" "0.212354345352163"
## [129,] "1.58467753761111" "0.152084021379928" "0.212354345352163"
## [130,] "1.78601782902778" "0.464959122473118" "0.0628744699958889"
## [131,] "9.49908019444444" "0.464959122473118" "0.0628744699958889"
## [132,] "1.58467753761111" "0.464959122473118" "0.0628744699958889"
## [133,] "1.83408651152778" "0.00191829141577138" "0.988192045399355"
## [134,] "13.7635996805556" "-0.34094438077957" "0.00860241915390606"
## [135,] "13.1573386111111" "-0.34094438077957" "0.00860241915390606"
## [136,] "10.1926545138889" "-0.34094438077957" "0.00860241915390606"
## [137,] "13.4608232777778" "-0.34094438077957" "0.00860241915390606"
## [138,] "11.8283412361111" "-0.34094438077957" "0.00860241915390606"
## [139,] "9.158511125" "-0.34094438077957" "0.00860241915390606"
## [140,] "10.8221732083333" "-0.34094438077957" "0.00860241915390606"
## [141,] "9.158511125" "0.176846033360215" "0.531674114312941"
## [142,] "0.961096077416667" "0.176846033360215" "0.531674114312941"
## [143,] "2.457180375" "0.75743010047491" "0.00822001518267293"
## [144,] "1.85219611194444" "0.75743010047491" "0.00822001518267293"
## [145,] "1.58467753761111" "0.0889274530555548" "0.438985017202481"
## [146,] "13.7635996805556" "-0.0858636887096775" "0.635312896541165"
## [147,] "2.70451477777778" "-0.0858636887096775" "0.635312896541165"
## [148,] "13.1573386111111" "-0.0858636887096775" "0.635312896541165"
## [149,] "10.1926545138889" "-0.0858636887096775" "0.635312896541165"
## [150,] "1.78601782902778" "-0.0858636887096775" "0.635312896541165"
## [151,] "13.4608232777778" "-0.0858636887096775" "0.635312896541165"
## [152,] "1.85219611194444" "-0.0858636887096775" "0.635312896541165"
## [153,] "10.8221732083333" "-0.0858636887096775" "0.635312896541165"
## [154,] "13.1573386111111" "-0.0602517025089604" "0.483384061251613"
## [155,] "9.49908019444444" "0.26857133719534" "0.304507379361637"
## [156,] "1.83408651152778" "0.137811671953404" "0.561702568129719"
## [157,] "2.457180375" "-0.138744352688173" "0.508609150568473"
## [158,] "3.28763746666667" "0.0955080030824371" "0.490359594244203"
## [159,] "9.49908019444444" "0.0955080030824371" "0.490359594244203"
## [160,] "3.28763746666667" "-0.00965798807347618" "0.943896953941426"
## [161,] "3.28763746666667" "0.487373240026882" "0.117462359699773"
## [162,] "0.961096077416667" "1.42145250612007" "3.22387671732929e-06"
## [163,] "11.70743525" "0.245562178243727" "0.287198185723224"
## [164,] "1.83408651152778" "0.245562178243727" "0.287198185723224"
## [165,] "3.28763746666667" "0.245562178243727" "0.287198185723224"
## [166,] "1.58467753761111" "0.245562178243727" "0.287198185723224"
## [167,] "13.7635996805556" "-0.154042436890681" "0.121257033313765"
## [168,] "13.1573386111111" "-0.154042436890681" "0.121257033313765"
## [169,] "10.1926545138889" "-0.154042436890681" "0.121257033313765"
## [170,] "11.8283412361111" "-0.154042436890681" "0.121257033313765"
## [171,] "9.158511125" "-0.154042436890681" "0.121257033313765"
## [172,] "10.8221732083333" "-0.154042436890681" "0.121257033313765"
## [173,] "1.58467753761111" "-0.154042436890681" "0.121257033313765"
## [174,] "0.961096077416667" "1.80042208596774" "4.38369761870984e-07"
## [175,] "10.8221732083333" "0.287680863620073" "0.0452363910101052"
## [176,] "1.58467753761111" "0.287680863620073" "0.0452363910101052"
## [177,] "13.7635996805556" "-0.0531431949910388" "0.635312896541165"
## [178,] "2.70451477777778" "-0.0531431949910388" "0.635312896541165"
## [179,] "13.1573386111111" "-0.0531431949910388" "0.635312896541165"
## [180,] "10.1926545138889" "-0.0531431949910388" "0.635312896541165"
## [181,] "13.4608232777778" "-0.0531431949910388" "0.635312896541165"
## [182,] "11.8283412361111" "-0.0531431949910388" "0.635312896541165"
## [183,] "1.87426554416667" "-0.0531431949910388" "0.635312896541165"
## [184,] "13.7635996805556" "-0.0325320655555563" "0.726113082768401"
## [185,] "13.1573386111111" "-0.0325320655555563" "0.726113082768401"
## [186,] "10.8221732083333" "-0.0325320655555563" "0.726113082768401"
## [187,] "9.49908019444444" "0.412350103136201" "0.00243787567434807"
## [188,] "1.58467753761111" "0.412350103136201" "0.00243787567434807"
## [189,] "0.760913995722222" "2.62871618991935" "8.47951826309877e-09"
## [190,] "1.83408651152778" "2.62871618991935" "8.47951826309877e-09"
## [191,] "0.961096077416667" "2.62871618991935" "8.47951826309877e-09"
## [192,] "9.158511125" "0.181959138969535" "0.521610045686861"
## [193,] "9.49908019444444" "0.307198805071685" "0.0654869415933698"
## [194,] "0.961096077416667" "0.307198805071685" "0.0654869415933698"
## [195,] "2.70451477777778" "-0.0458736311648744" "0.631603981354613"
## [196,] "13.1573386111111" "-0.0458736311648744" "0.631603981354613"
## [197,] "2.457180375" "-0.0458736311648744" "0.631603981354613"
## [198,] "1.85219611194444" "-0.0458736311648744" "0.631603981354613"
## [199,] "10.8221732083333" "-0.0458736311648744" "0.631603981354613"
## [200,] "0.961096077416667" "-0.0458736311648744" "0.631603981354613"
## [201,] "11.70743525" "0.565640802553762" "0.00860241915390606"
## [202,] "9.49908019444444" "0.565640802553762" "0.00860241915390606"
## [203,] "1.58467753761111" "0.565640802553762" "0.00860241915390606"
## [204,] "11.70743525" "0.551519544363799" "0.00658763061704287"
## [205,] "3.28763746666667" "0.551519544363799" "0.00658763061704287"
## [206,] "13.1573386111111" "-0.250514620394266" "0.0513344437604453"
## [207,] "10.1926545138889" "-0.250514620394266" "0.0513344437604453"
## [208,] "0.961096077416667" "2.25645131103943" "3.6511553203874e-11"
## mean_case(gene) mean_control(gene) de novo
## [1,] "11.2184064330645" "11.4926855972222" 0
## [2,] "11.2184064330645" "11.4926855972222" 0
## [3,] "10.8860943914516" "9.48500803555556" 0
## [4,] "8.5685921366129" "7.78722800722222" 0
## [5,] "8.5685921366129" "7.78722800722222" 0
## [6,] "8.5685921366129" "7.78722800722222" 0
## [7,] "9.585765225" "7.70709870944444" 0
## [8,] "10.0222594730645" "9.92504677277778" 0
## [9,] "14.6169198435484" "14.5263083805556" 0
## [10,] "11.3761430325806" "10.5570063847222" 0
## [11,] "12.9655517887097" "11.1700385702778" 0
## [12,] "12.9655517887097" "11.1700385702778" 0
## [13,] "11.012596878871" "11.1182434786111" 0
## [14,] "10.8879934756452" "10.7235666413889" 0
## [15,] "10.8879934756452" "10.7235666413889" 0
## [16,] "13.7745548564516" "13.1286641333333" 0
## [17,] "10.3657648179032" "10.2151338813889" 0
## [18,] "10.5484809443548" "9.80151133777778" 0
## [19,] "10.5165094330645" "10.5832945075" 0
## [20,] "10.5165094330645" "10.5832945075" 0
## [21,] "9.91263204709677" "9.58496805777778" 0
## [22,] "9.91263204709677" "9.58496805777778" 0
## [23,] "9.91263204709677" "9.58496805777778" 0
## [24,] "14.5046142467742" "14.9051628166667" 0
## [25,] "14.5046142467742" "14.9051628166667" 0
## [26,] "14.5046142467742" "14.9051628166667" 0
## [27,] "14.5046142467742" "14.9051628166667" 0
## [28,] "14.5046142467742" "14.9051628166667" 0
## [29,] "13.5441684096774" "13.6381748166667" 0
## [30,] "13.5441684096774" "13.6381748166667" 0
## [31,] "8.95929116967742" "8.27736924111111" 0
## [32,] "8.42556038032258" "7.74930629833333" 0
## [33,] "7.57038927451613" "7.40530791222222" 0
## [34,] "7.57038927451613" "7.40530791222222" 0
## [35,] "11.0381468501613" "10.2215942186111" 0
## [36,] "7.69568655629032" "7.71778892861111" 0
## [37,] "11.0620734062903" "8.89214447111111" 0
## [38,] "11.0620734062903" "8.89214447111111" 0
## [39,] "8.12967414532258" "7.53380247138889" 0
## [40,] "8.2484851533871" "7.32673002888889" 0
## [41,] "8.2484851533871" "7.32673002888889" 0
## [42,] "8.2484851533871" "7.32673002888889" 0
## [43,] "9.74105918419355" "8.38197263833333" 0
## [44,] "9.51118165870968" "9.58015192277778" 0
## [45,] "9.51118165870968" "9.58015192277778" 0
## [46,] "9.51118165870968" "9.58015192277778" 0
## [47,] "9.51118165870968" "9.58015192277778" 0
## [48,] "9.51118165870968" "9.58015192277778" 0
## [49,] "9.51118165870968" "9.58015192277778" 0
## [50,] "9.51118165870968" "9.58015192277778" 0
## [51,] "10.3451832662903" "9.4649654525" 0
## [52,] "11.3498071608065" "8.92444201472222" 0
## [53,] "10.5390777541935" "9.88533557805555" 0
## [54,] "10.5390777541935" "9.88533557805555" 0
## [55,] "11.2344046029032" "10.1845236863889" 0
## [56,] "11.2344046029032" "10.1845236863889" 0
## [57,] "11.2344046029032" "10.1845236863889" 0
## [58,] "11.2344046029032" "10.1845236863889" 0
## [59,] "12.0139219329032" "10.9497418586111" 0
## [60,] "9.33591464854839" "9.26575054361111" 0
## [61,] "9.47491935564516" "9.77920116055556" 0
## [62,] "9.47491935564516" "9.77920116055556" 0
## [63,] "8.36535806145161" "8.3937582475" 0
## [64,] "8.36535806145161" "8.3937582475" 0
## [65,] "11.3129354306452" "10.9971412094444" 0
## [66,] "11.3129354306452" "10.9971412094444" 0
## [67,] "8.74901937258064" "8.61940299861111" 0
## [68,] "8.13640123532258" "6.93288196305556" 0
## [69,] "11.071394925" "11.1508719733333" 0
## [70,] "11.071394925" "11.1508719733333" 0
## [71,] "11.071394925" "11.1508719733333" 0
## [72,] "11.071394925" "11.1508719733333" 0
## [73,] "11.071394925" "11.1508719733333" 0
## [74,] "8.58800569532258" "7.78756579694444" 0
## [75,] "8.58800569532258" "7.78756579694444" 0
## [76,] "8.58800569532258" "7.78756579694444" 0
## [77,] "8.21679992822581" "6.96706235361111" 0
## [78,] "13.4868625854839" "13.1329639944444" 0
## [79,] "11.1916897469355" "10.8285608411111" 0
## [80,] "11.4087726722581" "11.1352745158333" 0
## [81,] "6.87506713677419" "6.82652711666667" 0
## [82,] "6.87506713677419" "6.82652711666667" 0
## [83,] "11.8533889225806" "11.3587537805556" 0
## [84,] "7.4720977083871" "7.57488933027778" 0
## [85,] "7.4720977083871" "7.57488933027778" 0
## [86,] "7.4720977083871" "7.57488933027778" 0
## [87,] "9.36097694129032" "8.99113197972222" 0
## [88,] "10.600268405" "9.82080241611111" 0
## [89,] "7.37322184580645" "6.93547361027778" 0
## [90,] "9.90633540806452" "9.46323890027778" 0
## [91,] "12.9034160193548" "12.9281105722222" 0
## [92,] "12.9034160193548" "12.9281105722222" 0
## [93,] "12.9034160193548" "12.9281105722222" 0
## [94,] "12.9034160193548" "12.9281105722222" 0
## [95,] "12.9034160193548" "12.9281105722222" 0
## [96,] "12.9034160193548" "12.9281105722222" 0
## [97,] "12.9034160193548" "12.9281105722222" 0
## [98,] "12.9034160193548" "12.9281105722222" 0
## [99,] "12.9034160193548" "12.9281105722222" 0
## [100,] "12.9034160193548" "12.9281105722222" 0
## [101,] "13.2969204112903" "13.7956430527778" 0
## [102,] "13.2969204112903" "13.7956430527778" 0
## [103,] "13.2969204112903" "13.7956430527778" 0
## [104,] "13.2969204112903" "13.7956430527778" 0
## [105,] "13.2969204112903" "13.7956430527778" 0
## [106,] "8.08787522564516" "8.06957060111111" 0
## [107,] "8.08787522564516" "8.06957060111111" 0
## [108,] "8.08787522564516" "8.06957060111111" 0
## [109,] "12.8023194016129" "12.5775275222222" 0
## [110,] "12.8023194016129" "12.5775275222222" 0
## [111,] "12.6985306241935" "11.3942000419444" 0
## [112,] "8.51591132306452" "8.17462146694444" 0
## [113,] "8.51591132306452" "8.17462146694444" 0
## [114,] "6.33624481290323" "6.44198236555556" 0
## [115,] "6.33624481290323" "6.44198236555556" 0
## [116,] "7.87809375225806" "7.99695051972222" 0
## [117,] "9.22120844758065" "8.95676916638889" 0
## [118,] "9.41723547370968" "8.37411315666667" 0
## [119,] "9.41723547370968" "8.37411315666667" 0
## [120,] "12.1458561919355" "12.3099642694444" 0
## [121,] "12.1458561919355" "12.3099642694444" 0
## [122,] "13.4014502403226" "12.1538429452778" 0
## [123,] "13.4014502403226" "12.1538429452778" 0
## [124,] "13.4014502403226" "12.1538429452778" 0
## [125,] "10.3526938696774" "10.0688447863889" 0
## [126,] "10.3526938696774" "10.0688447863889" 0
## [127,] "10.3526938696774" "10.0688447863889" 0
## [128,] "6.59644993193548" "6.44436591055556" 0
## [129,] "6.59644993193548" "6.44436591055556" 0
## [130,] "11.6801654308065" "11.2152063083333" 0
## [131,] "11.6801654308065" "11.2152063083333" 0
## [132,] "11.6801654308065" "11.2152063083333" 0
## [133,] "8.20879584419355" "8.20687755277778" 0
## [134,] "6.9724568683871" "7.31340124916667" 0
## [135,] "6.9724568683871" "7.31340124916667" 0
## [136,] "6.9724568683871" "7.31340124916667" 0
## [137,] "6.9724568683871" "7.31340124916667" 0
## [138,] "6.9724568683871" "7.31340124916667" 0
## [139,] "6.9724568683871" "7.31340124916667" 0
## [140,] "6.9724568683871" "7.31340124916667" 0
## [141,] "8.04364874919355" "7.86680271583333" 0
## [142,] "8.04364874919355" "7.86680271583333" 0
## [143,] "10.3916130374194" "9.63418293694444" 0
## [144,] "10.3916130374194" "9.63418293694444" 0
## [145,] "6.98219636" "6.89326890694444" 0
## [146,] "8.48951189129032" "8.57537558" 0
## [147,] "8.48951189129032" "8.57537558" 0
## [148,] "8.48951189129032" "8.57537558" 0
## [149,] "8.48951189129032" "8.57537558" 0
## [150,] "8.48951189129032" "8.57537558" 0
## [151,] "8.48951189129032" "8.57537558" 0
## [152,] "8.48951189129032" "8.57537558" 0
## [153,] "8.48951189129032" "8.57537558" 0
## [154,] "6.54965400193548" "6.60990570444444" 0
## [155,] "10.1861109908065" "9.91753965361111" 0
## [156,] "17.5653704080645" "17.4275587361111" 0
## [157,] "12.2657196806452" "12.4044640333333" 0
## [158,] "7.36270688419355" "7.26719888111111" 0
## [159,] "7.36270688419355" "7.26719888111111" 0
## [160,] "7.46377880887097" "7.47343679694444" 0
## [161,] "10.5959257541935" "10.1085525141667" 0
## [162,] "11.5493079280645" "10.1278554219444" 0
## [163,] "8.99141984435484" "8.74585766611111" 0
## [164,] "8.99141984435484" "8.74585766611111" 0
## [165,] "8.99141984435484" "8.74585766611111" 0
## [166,] "8.99141984435484" "8.74585766611111" 0
## [167,] "7.2532758833871" "7.40731832027778" 0
## [168,] "7.2532758833871" "7.40731832027778" 0
## [169,] "7.2532758833871" "7.40731832027778" 0
## [170,] "7.2532758833871" "7.40731832027778" 0
## [171,] "7.2532758833871" "7.40731832027778" 0
## [172,] "7.2532758833871" "7.40731832027778" 0
## [173,] "7.2532758833871" "7.40731832027778" 0
## [174,] "10.0424925209677" "8.242070435" 0
## [175,] "12.3877191580645" "12.1000382944444" 0
## [176,] "12.3877191580645" "12.1000382944444" 0
## [177,] "6.66489320306452" "6.71803639805556" 0
## [178,] "6.66489320306452" "6.71803639805556" 0
## [179,] "6.66489320306452" "6.71803639805556" 0
## [180,] "6.66489320306452" "6.71803639805556" 0
## [181,] "6.66489320306452" "6.71803639805556" 0
## [182,] "6.66489320306452" "6.71803639805556" 0
## [183,] "6.66489320306452" "6.71803639805556" 0
## [184,] "6.31490324" "6.34743530555556" 0
## [185,] "6.31490324" "6.34743530555556" 0
## [186,] "6.31490324" "6.34743530555556" 0
## [187,] "7.32820054258065" "6.91585043944444" 0
## [188,] "7.32820054258065" "6.91585043944444" 0
## [189,] "13.9638110774194" "11.3350948875" 0
## [190,] "13.9638110774194" "11.3350948875" 0
## [191,] "13.9638110774194" "11.3350948875" 0
## [192,] "11.2522421525806" "11.0702830136111" 0
## [193,] "9.04463756451613" "8.73743875944444" 0
## [194,] "9.04463756451613" "8.73743875944444" 0
## [195,] "6.6810354616129" "6.72690909277778" 0
## [196,] "6.6810354616129" "6.72690909277778" 0
## [197,] "6.6810354616129" "6.72690909277778" 0
## [198,] "6.6810354616129" "6.72690909277778" 0
## [199,] "6.6810354616129" "6.72690909277778" 0
## [200,] "6.6810354616129" "6.72690909277778" 0
## [201,] "8.8635200483871" "8.29787924583333" 0
## [202,] "8.8635200483871" "8.29787924583333" 0
## [203,] "8.8635200483871" "8.29787924583333" 0
## [204,] "7.69552500741935" "7.14400546305556" 0
## [205,] "7.69552500741935" "7.14400546305556" 0
## [206,] "7.84967777516129" "8.10019239555556" 0
## [207,] "7.84967777516129" "8.10019239555556" 0
## [208,] "10.3627084004839" "8.10625708944444" 00.7 Other Functions
0.7.1 Multiple-Groups Data
As for the data, which classify samples into more than two groups, anamiR provides function multi_Differ. User can get more information about this function by refering to its documentation.
0.7.2 Continuous Data
The data with continuous phenotype feature are also supported, differExp_continuous contains linear regression model, which can fit the continuous data series. User can get more information about this function by refering to its documentation.