bodymapRat 1.0.0
The bodymapRat package contains gene expression
data on 652 RNA-Seq samples from a comprehensive rat
transcriptomic BodyMap study. These samples include
the sequence identifier information provided in the
header of the FASTQ files which can be used as a
surrogate for batch. These samples have not been
normalized or pre-processed.
The data are provided in a SummarizedExperiment. The
phenotypic information can be extracted using the
colData() function and a description of the phenotypic
data is listed in the table below:
| Title | Description |
|---|---|
| sraExperiment | SRA Experiment ID |
| title | Title of sample provided by the authors |
| geoAccession | GEO Accession ID |
| BioSample | BioSample ID |
| avgLength | Average read length |
| instrument | Machine identifier (from FASTQ header) |
| runID | Run ID (from FASTQ header) |
| fcID | Flow cell ID (from FASTQ header) |
| fcLane | Flow cell lane (from FASTQ header) |
| tile | Tile (from FASTQ header) |
| xtile | xtile (from FASTQ header) |
| ytile | ytile (from FASTQ header) |
| organ | Body organ |
| sex | Gender |
| stage | Stage |
| techRep | Technical replicate number |
| colOrgan | Column of colors to help with plotting |
| rnaRIN | RIN number |
| barcode | barcode number |
The data can be accessed as follows:
library(SummarizedExperiment)
library(bodymapRat)We use the bodymapRat() function to download the
relevant files from Bioconductor’s
ExperimentHub web
resource. Running this function will download a
SummarizedExperiment object, which contains read counts, as
well as the metadata on the rows (genes) and columns (cells).
bm_rat <- bodymapRat()
# Get the expression data
counts = assay(bm_rat)
dim(counts)## [1] 32637 652counts[1:5, 1:5]## SRR1169893 SRR1169894 SRR1169895 SRR1169896 SRR1169897
## ENSRNOG00000000001 1 0 0 1 4
## ENSRNOG00000000007 1 1 0 3 0
## ENSRNOG00000000008 7 4 2 3 7
## ENSRNOG00000000009 0 0 0 0 1
## ENSRNOG00000000010 0 1 0 0 0# Get the meta data along columns
head(colData(bm_rat))## DataFrame with 6 rows and 22 columns
## sraExperiment sraRun title geoAccession sraSample
## <character> <character> <character> <factor> <factor>
## SRR1169893 SRX471368 SRR1169893 Adr_F_002_1 GSM1328469 SRS558114
## SRR1169894 SRX471368 SRR1169894 Adr_F_002_1 GSM1328469 SRS558114
## SRR1169895 SRX471369 SRR1169895 Adr_F_002_2 GSM1328470 SRS558115
## SRR1169896 SRX471369 SRR1169896 Adr_F_002_2 GSM1328470 SRS558115
## SRR1169897 SRX471370 SRR1169897 Adr_F_002_3 GSM1328471 SRS558116
## SRR1169898 SRX471370 SRR1169898 Adr_F_002_3 GSM1328471 SRS558116
## BioSample avgLength organ sex stage
## <factor> <integer> <character> <character> <numeric>
## SRR1169893 SAMN02642886 50 Adrenal F 2
## SRR1169894 SAMN02642886 50 Adrenal F 2
## SRR1169895 SAMN02642867 50 Adrenal F 2
## SRR1169896 SAMN02642867 50 Adrenal F 2
## SRR1169897 SAMN02642894 50 Adrenal F 2
## SRR1169898 SAMN02642894 50 Adrenal F 2
## techRep colOrgan mix rnaRIN barcode
## <integer> <character> <character> <character> <character>
## SRR1169893 1 brown M1 9.3 11
## SRR1169894 2 brown M1 9.3 11
## SRR1169895 1 brown M1 9.1 5
## SRR1169896 2 brown M1 9.1 5
## SRR1169897 1 brown M1 9.5 3
## SRR1169898 2 brown M1 9.5 3
## instrument runID fcID fcLane tile
## <character> <character> <character> <character> <character>
## SRR1169893 HWI-ST845 120326 D0VTJACXX 2 1101
## SRR1169894 HWI-ST845 120525 D10G7ACXX 2 1101
## SRR1169895 HWI-ST845 120326 D0VTJACXX 5 1101
## SRR1169896 HWI-ST845 120525 D10G7ACXX 5 1101
## SRR1169897 HWI-ST1131 120424 C0P4UACXX 4 1101
## SRR1169898 HWI-ST1195 120525 C0TDUACXX 4 1101
## xtile ytile
## <character> <character>
## SRR1169893 1506 2000
## SRR1169894 1394 2133
## SRR1169895 1170 2029
## SRR1169896 1650 2126
## SRR1169897 1675 2216
## SRR1169898 1138 2067The data in this package are used as an example
data set in the
qsmooth Bioconductor package.
sessionInfo()## R version 3.6.0 (2019-04-26)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 18.04.2 LTS
##
## Matrix products: default
## BLAS: /home/biocbuild/bbs-3.9-bioc/R/lib/libRblas.so
## LAPACK: /home/biocbuild/bbs-3.9-bioc/R/lib/libRlapack.so
##
## locale:
## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
## [3] LC_TIME=en_US.UTF-8 LC_COLLATE=C
## [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
## [7] LC_PAPER=en_US.UTF-8 LC_NAME=C
## [9] LC_ADDRESS=C LC_TELEPHONE=C
## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
##
## attached base packages:
## [1] parallel stats4 stats graphics grDevices utils datasets
## [8] methods base
##
## other attached packages:
## [1] bodymapRat_1.0.0 ExperimentHub_1.10.0
## [3] AnnotationHub_2.16.0 BiocFileCache_1.8.0
## [5] dbplyr_1.4.0 SummarizedExperiment_1.14.0
## [7] DelayedArray_0.10.0 BiocParallel_1.18.0
## [9] matrixStats_0.54.0 Biobase_2.44.0
## [11] GenomicRanges_1.36.0 GenomeInfoDb_1.20.0
## [13] IRanges_2.18.0 S4Vectors_0.22.0
## [15] BiocGenerics_0.30.0 knitr_1.22
## [17] BiocStyle_2.12.0
##
## loaded via a namespace (and not attached):
## [1] tidyselect_0.2.5 xfun_0.6
## [3] purrr_0.3.2 lattice_0.20-38
## [5] htmltools_0.3.6 yaml_2.2.0
## [7] interactiveDisplayBase_1.22.0 blob_1.1.1
## [9] rlang_0.3.4 later_0.8.0
## [11] pillar_1.3.1 glue_1.3.1
## [13] DBI_1.0.0 rappdirs_0.3.1
## [15] bit64_0.9-7 GenomeInfoDbData_1.2.1
## [17] stringr_1.4.0 zlibbioc_1.30.0
## [19] evaluate_0.13 memoise_1.1.0
## [21] httpuv_1.5.1 curl_3.3
## [23] AnnotationDbi_1.46.0 Rcpp_1.0.1
## [25] xtable_1.8-4 promises_1.0.1
## [27] BiocManager_1.30.4 XVector_0.24.0
## [29] mime_0.6 bit_1.1-14
## [31] digest_0.6.18 stringi_1.4.3
## [33] shiny_1.3.2 bookdown_0.9
## [35] dplyr_0.8.0.1 grid_3.6.0
## [37] tools_3.6.0 bitops_1.0-6
## [39] magrittr_1.5 RCurl_1.95-4.12
## [41] tibble_2.1.1 RSQLite_2.1.1
## [43] crayon_1.3.4 pkgconfig_2.0.2
## [45] Matrix_1.2-17 assertthat_0.2.1
## [47] rmarkdown_1.12 httr_1.4.0
## [49] R6_2.4.0 compiler_3.6.0