maaslin2
Himel Mallick
himel.stat.iitk@gmail.comAli Rahnavard
gholamali.rahnavard@gmail.comLauren McIver
lauren.j.mciver@gmail.comFriday, May 10, 2019
MaAsLin2 User Manual
MaAsLin2 is the next generation of MaAsLin.
MaAsLin2 is comprehensive R package for finding multivariable association between clinical metadata and microbial meta-omics features. MaAsLin2 relies on general linear models to accommodate most modern epidemiological study designs, including multiple analysis methods (with support for multiple covariates and repeated measures), filtering, normalization, and transform options to customize analysis for your specific study.
If you use the MaAsLin2 software, please cite our manuscript: Mallick et al. (2020+). “Multivariable Association in Population-scale Meta-omics Studies” (In Preparation).
If you have questions, please email the google group MaAsLin Users.
Contents
Description
MaAsLin2 finds associations between microbiome multi-omics features and complex metadata in population-scale epidemiological studies. The software includes multiple analysis methods (with support for multiple covariates and repeated measures), filtering, normalization, and transform options to customize analysis for your specific study.
Requirements
MaAsLin2 is an R package that can be run on the command line or as an R function.
Installation
MaAsLin2 can be run from the command line or as an R function. If only running from the command line, you do not need to install the MaAsLin2 package but you will need to install the MaAsLin2 dependencies.
From command line
- Download the source: MaAsLin2.tar.gz
- Decompress the download:
$ tar xzvf maaslin2.tar.gz
- Install the Bioconductor dependencies edgeR and metagenomeSeq.
- Install the CRAN dependencies:
$ R -q -e "install.packages(c('lmerTest','pbapply','car','dplyr','vegan','chemometrics','ggplot2','pheatmap','hash','logging','data.table','MuMIn','glmmTMB','MASS','cplm','pscl'), repos='http://cran.r-project.org')"
- Install the MaAsLin2 package (only r,equired if running as an R function):
$ R CMD INSTALL maaslin2
From R
Install Bioconductor and then install Maaslin2
if(!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("Maaslin2")How to Run
MaAsLin2 can be run from the command line or as an R function. Both methods require the same arguments, have the same options, and use the same default settings.
Input Files
MaAsLin2 requires two input files.
- Data (or features) file
- This file is tab-delimited.
- Formatted with features as columns and samples as rows.
- The transpose of this format is also okay.
- Possible features in this file include taxonomy or genes.
- Metadata file
- This file is tab-delimited.
- Formatted with features as columns and samples as rows.
- The transpose of this format is also okay.
- Possible metadata in this file include gender or age.
The data file can contain samples not included in the metadata file (along with the reverse case). For both cases, those samples not included in both files will be removed from the analysis. Also the samples do not need to be in the same order in the two files.
NOTE: If running MaAsLin2 as a function, the data and metadata inputs can be of type data.frame instead of a path to a file.
Output Files
MaAsLin2 generates two types of output files: data and visualization.
- Data output files
all_results.tsv- This includes the same data as the data.frame returned.
- This file contains all results ordered by increasing q-value.
- The first columns are the metadata and feature names.
- The next two columns are the value and coefficient from the model.
- The next column is the standard deviation from the model.
- The
Ncolumn is the total number of data points. - The
N.not.zerocolumn is the total of non-zero data points. - The pvalue from the calculation is the second to last column.
- The qvalue is computed with
p.adjustwith the correction method.
significant_results.tsv- This file is a subset of the results in the first file.
- It only includes associations with q-values <= to the threshold.
residuals.rds- This file contains a data frame with residuals for each feature.
fitted.rds- This file contains a data frame with fitted values for each feature.
ranef.rds- This file contains a data frame with extracted random effects for each feature (when random effects are specified).
maaslin2.log- This file contains all log information for the run.
- It includes all settings, warnings, errors, and steps run.
- Visualization output files
heatmap.pdf- This file contains a heatmap of the significant associations.
[a-z/0-9]+.pdf- A plot is generated for each significant association.
- Scatter plots are used for continuous metadata.
- Box plots are for categorical data.
- Data points plotted are after normalization, filtering, and transform.
Run a Demo
Example input files can be found in the inst/extdata folder of the MaAsLin2 source. The files provided were generated from the HMP2 data which can be downloaded from https://ibdmdb.org/ .
HMP2_taxonomy.tsv: is a tab-demilited file with species as columns and samples as rows. It is a subset of the taxonomy file so it just includes the species abundances for all samples.
HMP2_metadata.tsv: is a tab-delimited file with samples as rows and metadata as columns. It is a subset of the metadata file so that it just includes some of the fields.
Command line
$ Maaslin2.R --transform=AST --fixed_effects="diagnosis,dysbiosisnonIBD,dysbiosisUC,dysbiosisCD,antibiotics,age" --random_effects="site,subject" --normalization=NONE --standardize=FALSE inst/extdata/HMP2_taxonomy.tsv inst/extdata/HMP2_metadata.tsv demo_output
- Make sure to provide the full path to the MaAsLin2 executable (ie ./R/Maaslin2.R).
- In the demo command:
HMP2_taxonomy.tsvis the path to your data (or features) fileHMP2_metadata.tsvis the path to your metadata filedemo_outputis the path to the folder to write the output
In R
library(Maaslin2)
input_data <- system.file(
'extdata','HMP2_taxonomy.tsv', package="Maaslin2")
input_metadata <-system.file(
'extdata','HMP2_metadata.tsv', package="Maaslin2")
fit_data <- Maaslin2(
input_data, input_metadata, 'demo_output', transform = "AST",
fixed_effects = c('diagnosis', 'dysbiosisnonIBD','dysbiosisUC','dysbiosisCD', 'antibiotics', 'age'),
random_effects = c('site', 'subject'),
reference = "diagnosis,nonIBD",
normalization = 'NONE',
standardize = FALSE)## [1] "Creating output folder"
## [1] "Creating output figures folder"
## 2022-04-26 17:00:41 INFO::Writing function arguments to log file
## 2022-04-26 17:00:41 INFO::Verifying options selected are valid
## 2022-04-26 17:00:41 INFO::Determining format of input files
## 2022-04-26 17:00:41 INFO::Input format is data samples as rows and metadata samples as rows
## 2022-04-26 17:00:41 INFO::Formula for random effects: expr ~ (1 | site) + (1 | subject)
## 2022-04-26 17:00:41 INFO::Formula for fixed effects: expr ~ diagnosis + dysbiosisnonIBD + dysbiosisUC + dysbiosisCD + antibiotics + age
## 2022-04-26 17:00:41 INFO::Filter data based on min abundance and min prevalence
## 2022-04-26 17:00:41 INFO::Total samples in data: 1595
## 2022-04-26 17:00:41 INFO::Min samples required with min abundance for a feature not to be filtered: 159.500000
## 2022-04-26 17:00:41 INFO::Total filtered features: 0
## 2022-04-26 17:00:41 INFO::Filtered feature names from abundance and prevalence filtering:
## 2022-04-26 17:00:41 INFO::Total filtered features with variance filtering: 0
## 2022-04-26 17:00:41 INFO::Filtered feature names from variance filtering:
## 2022-04-26 17:00:41 INFO::Running selected normalization method: NONE
## 2022-04-26 17:00:41 INFO::Bypass z-score application to metadata
## 2022-04-26 17:00:41 INFO::Running selected transform method: AST
## 2022-04-26 17:00:41 INFO::Running selected analysis method: LM
## 2022-04-26 17:00:42 INFO::Fitting model to feature number 1, Bifidobacterium.adolescentis## boundary (singular) fit: see help('isSingular')## 2022-04-26 17:00:43 INFO::Fitting model to feature number 2, Bifidobacterium.bifidum
## 2022-04-26 17:00:43 INFO::Fitting model to feature number 3, Bifidobacterium.longum## boundary (singular) fit: see help('isSingular')## 2022-04-26 17:00:43 INFO::Fitting model to feature number 4, Bifidobacterium.pseudocatenulatum## boundary (singular) fit: see help('isSingular')## 2022-04-26 17:00:43 INFO::Fitting model to feature number 5, Collinsella.aerofaciens
## 2022-04-26 17:00:43 INFO::Fitting model to feature number 6, Bacteroides.caccae## boundary (singular) fit: see help('isSingular')## 2022-04-26 17:00:43 INFO::Fitting model to feature number 7, Bacteroides.cellulosilyticus
## 2022-04-26 17:00:43 INFO::Fitting model to feature number 8, Bacteroides.dorei## boundary (singular) fit: see help('isSingular')## 2022-04-26 17:00:44 INFO::Fitting model to feature number 9, Bacteroides.eggerthii## boundary (singular) fit: see help('isSingular')## Warning: Model failed to converge with 1 negative eigenvalue: -5.6e+00## 2022-04-26 17:00:44 INFO::Fitting model to feature number 10, Bacteroides.faecis
## 2022-04-26 17:00:44 INFO::Fitting model to feature number 11, Bacteroides.finegoldii## boundary (singular) fit: see help('isSingular')## 2022-04-26 17:00:44 INFO::Fitting model to feature number 12, Bacteroides.fragilis## boundary (singular) fit: see help('isSingular')## 2022-04-26 17:00:44 INFO::Fitting model to feature number 13, Bacteroides.intestinalis## boundary (singular) fit: see help('isSingular')## 2022-04-26 17:00:44 INFO::Fitting model to feature number 14, Bacteroides.massiliensis## boundary (singular) fit: see help('isSingular')## 2022-04-26 17:00:44 INFO::Fitting model to feature number 15, Bacteroides.ovatus
## 2022-04-26 17:00:45 INFO::Fitting model to feature number 16, Bacteroides.salyersiae## boundary (singular) fit: see help('isSingular')## 2022-04-26 17:00:45 INFO::Fitting model to feature number 17, Bacteroides.stercoris
## 2022-04-26 17:00:45 INFO::Fitting model to feature number 18, Bacteroides.thetaiotaomicron## boundary (singular) fit: see help('isSingular')## 2022-04-26 17:00:45 INFO::Fitting model to feature number 19, Bacteroides.uniformis## boundary (singular) fit: see help('isSingular')## 2022-04-26 17:00:45 INFO::Fitting model to feature number 20, Bacteroides.vulgatus## boundary (singular) fit: see help('isSingular')## 2022-04-26 17:00:45 INFO::Fitting model to feature number 21, Bacteroides.xylanisolvens## boundary (singular) fit: see help('isSingular')## 2022-04-26 17:00:46 INFO::Fitting model to feature number 22, Bacteroidales.bacterium.ph8
## 2022-04-26 17:00:46 INFO::Fitting model to feature number 23, Barnesiella.intestinihominis
## 2022-04-26 17:00:46 INFO::Fitting model to feature number 24, Coprobacter.fastidiosus
## 2022-04-26 17:00:46 INFO::Fitting model to feature number 25, Odoribacter.splanchnicus## boundary (singular) fit: see help('isSingular')## 2022-04-26 17:00:46 INFO::Fitting model to feature number 26, Parabacteroides.distasonis## boundary (singular) fit: see help('isSingular')## 2022-04-26 17:00:46 INFO::Fitting model to feature number 27, Parabacteroides.goldsteinii
## 2022-04-26 17:00:46 INFO::Fitting model to feature number 28, Parabacteroides.merdae
## 2022-04-26 17:00:46 INFO::Fitting model to feature number 29, Parabacteroides.unclassified## boundary (singular) fit: see help('isSingular')## 2022-04-26 17:00:47 INFO::Fitting model to feature number 30, Paraprevotella.clara
## 2022-04-26 17:00:47 INFO::Fitting model to feature number 31, Paraprevotella.unclassified
## 2022-04-26 17:00:47 INFO::Fitting model to feature number 32, Prevotella.copri## boundary (singular) fit: see help('isSingular')## 2022-04-26 17:00:47 INFO::Fitting model to feature number 33, Alistipes.finegoldii## boundary (singular) fit: see help('isSingular')## 2022-04-26 17:00:47 INFO::Fitting model to feature number 34, Alistipes.onderdonkii## boundary (singular) fit: see help('isSingular')## 2022-04-26 17:00:47 INFO::Fitting model to feature number 35, Alistipes.putredinis## boundary (singular) fit: see help('isSingular')## 2022-04-26 17:00:47 INFO::Fitting model to feature number 36, Alistipes.shahii## boundary (singular) fit: see help('isSingular')## 2022-04-26 17:00:48 INFO::Fitting model to feature number 37, Alistipes.unclassified
## 2022-04-26 17:00:48 INFO::Fitting model to feature number 38, Streptococcus.salivarius
## 2022-04-26 17:00:48 INFO::Fitting model to feature number 39, Clostridium.bolteae## boundary (singular) fit: see help('isSingular')## 2022-04-26 17:00:48 INFO::Fitting model to feature number 40, Clostridium.citroniae## boundary (singular) fit: see help('isSingular')## 2022-04-26 17:00:48 INFO::Fitting model to feature number 41, Clostridium.clostridioforme## boundary (singular) fit: see help('isSingular')## 2022-04-26 17:00:48 INFO::Fitting model to feature number 42, Clostridium.hathewayi## boundary (singular) fit: see help('isSingular')## 2022-04-26 17:00:49 INFO::Fitting model to feature number 43, Clostridium.leptum
## 2022-04-26 17:00:49 INFO::Fitting model to feature number 44, Clostridium.nexile
## 2022-04-26 17:00:49 INFO::Fitting model to feature number 45, Clostridium.symbiosum## boundary (singular) fit: see help('isSingular')## 2022-04-26 17:00:49 INFO::Fitting model to feature number 46, Flavonifractor.plautii## boundary (singular) fit: see help('isSingular')## 2022-04-26 17:00:49 INFO::Fitting model to feature number 47, Eubacterium.eligens
## 2022-04-26 17:00:49 INFO::Fitting model to feature number 48, Eubacterium.hallii
## 2022-04-26 17:00:49 INFO::Fitting model to feature number 49, Eubacterium.rectale
## 2022-04-26 17:00:49 INFO::Fitting model to feature number 50, Eubacterium.siraeum## boundary (singular) fit: see help('isSingular')## 2022-04-26 17:00:50 INFO::Fitting model to feature number 51, Eubacterium.sp.3.1.31## boundary (singular) fit: see help('isSingular')## 2022-04-26 17:00:50 INFO::Fitting model to feature number 52, Eubacterium.ventriosum## boundary (singular) fit: see help('isSingular')## 2022-04-26 17:00:50 INFO::Fitting model to feature number 53, Ruminococcus.gnavus## boundary (singular) fit: see help('isSingular')## 2022-04-26 17:00:50 INFO::Fitting model to feature number 54, Ruminococcus.obeum## boundary (singular) fit: see help('isSingular')## 2022-04-26 17:00:50 INFO::Fitting model to feature number 55, Ruminococcus.torques
## 2022-04-26 17:00:50 INFO::Fitting model to feature number 56, Coprococcus.comes
## 2022-04-26 17:00:51 INFO::Fitting model to feature number 57, Dorea.longicatena
## 2022-04-26 17:00:51 INFO::Fitting model to feature number 58, Lachnospiraceae.bacterium.1.1.57FAA## boundary (singular) fit: see help('isSingular')## 2022-04-26 17:00:51 INFO::Fitting model to feature number 59, Lachnospiraceae.bacterium.3.1.46FAA## boundary (singular) fit: see help('isSingular')## 2022-04-26 17:00:51 INFO::Fitting model to feature number 60, Roseburia.hominis## boundary (singular) fit: see help('isSingular')## 2022-04-26 17:00:51 INFO::Fitting model to feature number 61, Roseburia.intestinalis
## 2022-04-26 17:00:51 INFO::Fitting model to feature number 62, Roseburia.inulinivorans## boundary (singular) fit: see help('isSingular')## 2022-04-26 17:00:51 INFO::Fitting model to feature number 63, Roseburia.unclassified## boundary (singular) fit: see help('isSingular')## 2022-04-26 17:00:52 INFO::Fitting model to feature number 64, Oscillibacter.unclassified
## 2022-04-26 17:00:52 INFO::Fitting model to feature number 65, Peptostreptococcaceae.noname.unclassified## boundary (singular) fit: see help('isSingular')## 2022-04-26 17:00:52 INFO::Fitting model to feature number 66, Faecalibacterium.prausnitzii
## 2022-04-26 17:00:52 INFO::Fitting model to feature number 67, Ruminococcus.bromii## boundary (singular) fit: see help('isSingular')## 2022-04-26 17:00:52 INFO::Fitting model to feature number 68, Ruminococcus.callidus
## 2022-04-26 17:00:52 INFO::Fitting model to feature number 69, Ruminococcus.lactaris
## 2022-04-26 17:00:52 INFO::Fitting model to feature number 70, Subdoligranulum.unclassified
## 2022-04-26 17:00:53 INFO::Fitting model to feature number 71, Coprobacillus.unclassified
## 2022-04-26 17:00:53 INFO::Fitting model to feature number 72, Acidaminococcus.unclassified## Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
## Model failed to converge with max|grad| = 0.00291214 (tol = 0.002, component 1)## 2022-04-26 17:00:53 INFO::Fitting model to feature number 73, Dialister.invisus## boundary (singular) fit: see help('isSingular')## Warning: Model failed to converge with 1 negative eigenvalue: -2.1e+02## 2022-04-26 17:00:53 INFO::Fitting model to feature number 74, Veillonella.atypica## boundary (singular) fit: see help('isSingular')## 2022-04-26 17:00:53 INFO::Fitting model to feature number 75, Veillonella.dispar## boundary (singular) fit: see help('isSingular')## 2022-04-26 17:00:54 INFO::Fitting model to feature number 76, Veillonella.parvula## boundary (singular) fit: see help('isSingular')## 2022-04-26 17:00:54 INFO::Fitting model to feature number 77, Veillonella.unclassified
## 2022-04-26 17:00:54 INFO::Fitting model to feature number 78, Burkholderiales.bacterium.1.1.47
## 2022-04-26 17:00:54 INFO::Fitting model to feature number 79, Parasutterella.excrementihominis## boundary (singular) fit: see help('isSingular')## 2022-04-26 17:00:54 INFO::Fitting model to feature number 80, Sutterella.wadsworthensis
## 2022-04-26 17:00:54 INFO::Fitting model to feature number 81, Bilophila.unclassified
## 2022-04-26 17:00:54 INFO::Fitting model to feature number 82, Escherichia.coli## boundary (singular) fit: see help('isSingular')## 2022-04-26 17:00:55 INFO::Fitting model to feature number 83, Escherichia.unclassified
## 2022-04-26 17:00:55 INFO::Fitting model to feature number 84, Klebsiella.pneumoniae## boundary (singular) fit: see help('isSingular')## 2022-04-26 17:00:55 INFO::Fitting model to feature number 85, Haemophilus.parainfluenzae## boundary (singular) fit: see help('isSingular')## 2022-04-26 17:00:55 INFO::Fitting model to feature number 86, Akkermansia.muciniphila## boundary (singular) fit: see help('isSingular')## Warning: Model failed to converge with 1 negative eigenvalue: -2.2e+02## 2022-04-26 17:00:55 INFO::Fitting model to feature number 87, C2likevirus.unclassified
## 2022-04-26 17:00:55 INFO::Counting total values for each feature
## 2022-04-26 17:00:55 INFO::Writing residuals to file demo_output/residuals.rds
## 2022-04-26 17:00:55 INFO::Writing fitted values to file demo_output/fitted.rds
## 2022-04-26 17:00:55 INFO::Writing extracted random effects to file demo_output/ranef.rds
## 2022-04-26 17:00:55 INFO::Writing all results to file (ordered by increasing q-values): demo_output/all_results.tsv
## 2022-04-26 17:00:55 INFO::Writing the significant results (those which are less than or equal to the threshold of 0.250000 ) to file (ordered by increasing q-values): demo_output/significant_results.tsv
## 2022-04-26 17:00:55 INFO::Writing heatmap of significant results to file: demo_output/heatmap.pdf## Warning in xtfrm.data.frame(x): cannot xtfrm data frames## 2022-04-26 17:00:56 INFO::Writing association plots (one for each significant association) to output folder: demo_output
## 2022-04-26 17:00:56 INFO::Plotting associations from most to least significant, grouped by metadata
## 2022-04-26 17:00:56 INFO::Plotting data for metadata number 1, dysbiosisCD
## 2022-04-26 17:00:56 INFO::Creating boxplot for categorical data, dysbiosisCD vs Faecalibacterium.prausnitzii## 2022-04-26 17:00:56 INFO::Creating boxplot for categorical data, dysbiosisCD vs Bacteroides.uniformis## 2022-04-26 17:00:56 INFO::Creating boxplot for categorical data, dysbiosisCD vs Eubacterium.rectale## 2022-04-26 17:00:56 INFO::Creating boxplot for categorical data, dysbiosisCD vs Alistipes.putredinis## 2022-04-26 17:00:57 INFO::Creating boxplot for categorical data, dysbiosisCD vs Subdoligranulum.unclassified## 2022-04-26 17:00:57 INFO::Creating boxplot for categorical data, dysbiosisCD vs Escherichia.coli## 2022-04-26 17:00:57 INFO::Creating boxplot for categorical data, dysbiosisCD vs Bacteroides.vulgatus## 2022-04-26 17:00:57 INFO::Creating boxplot for categorical data, dysbiosisCD vs Clostridium.clostridioforme## 2022-04-26 17:00:57 INFO::Creating boxplot for categorical data, dysbiosisCD vs Klebsiella.pneumoniae## 2022-04-26 17:00:58 INFO::Creating boxplot for categorical data, dysbiosisCD vs Clostridium.hathewayi## 2022-04-26 17:00:58 INFO::Creating boxplot for categorical data, dysbiosisCD vs Alistipes.shahii## 2022-04-26 17:00:58 INFO::Creating boxplot for categorical data, dysbiosisCD vs Ruminococcus.obeum## 2022-04-26 17:00:58 INFO::Creating boxplot for categorical data, dysbiosisCD vs Roseburia.inulinivorans## 2022-04-26 17:00:58 INFO::Creating boxplot for categorical data, dysbiosisCD vs Bacteroides.thetaiotaomicron## 2022-04-26 17:00:59 INFO::Creating boxplot for categorical data, dysbiosisCD vs Coprococcus.comes## 2022-04-26 17:00:59 INFO::Creating boxplot for categorical data, dysbiosisCD vs Veillonella.unclassified## 2022-04-26 17:00:59 INFO::Creating boxplot for categorical data, dysbiosisCD vs Lachnospiraceae.bacterium.3.1.46FAA## 2022-04-26 17:00:59 INFO::Creating boxplot for categorical data, dysbiosisCD vs Sutterella.wadsworthensis## 2022-04-26 17:00:59 INFO::Creating boxplot for categorical data, dysbiosisCD vs Odoribacter.splanchnicus## 2022-04-26 17:01:00 INFO::Creating boxplot for categorical data, dysbiosisCD vs Parabacteroides.distasonis## 2022-04-26 17:01:00 INFO::Creating boxplot for categorical data, dysbiosisCD vs Roseburia.hominis## 2022-04-26 17:01:00 INFO::Creating boxplot for categorical data, dysbiosisCD vs Burkholderiales.bacterium.1.1.47## 2022-04-26 17:01:00 INFO::Creating boxplot for categorical data, dysbiosisCD vs Escherichia.unclassified## 2022-04-26 17:01:00 INFO::Creating boxplot for categorical data, dysbiosisCD vs Bilophila.unclassified## 2022-04-26 17:01:01 INFO::Creating boxplot for categorical data, dysbiosisCD vs Dorea.longicatena## 2022-04-26 17:01:01 INFO::Creating boxplot for categorical data, dysbiosisCD vs Alistipes.unclassified## 2022-04-26 17:01:01 INFO::Creating boxplot for categorical data, dysbiosisCD vs Clostridium.symbiosum## 2022-04-26 17:01:01 INFO::Creating boxplot for categorical data, dysbiosisCD vs Eubacterium.hallii## 2022-04-26 17:01:01 INFO::Creating boxplot for categorical data, dysbiosisCD vs Parasutterella.excrementihominis## 2022-04-26 17:01:02 INFO::Creating boxplot for categorical data, dysbiosisCD vs Bacteroides.stercoris## 2022-04-26 17:01:02 INFO::Creating boxplot for categorical data, dysbiosisCD vs Alistipes.finegoldii## 2022-04-26 17:01:02 INFO::Creating boxplot for categorical data, dysbiosisCD vs Eubacterium.ventriosum## 2022-04-26 17:01:02 INFO::Creating boxplot for categorical data, dysbiosisCD vs Clostridium.nexile## 2022-04-26 17:01:02 INFO::Creating boxplot for categorical data, dysbiosisCD vs Clostridium.leptum## 2022-04-26 17:01:03 INFO::Creating boxplot for categorical data, dysbiosisCD vs Veillonella.parvula## 2022-04-26 17:01:03 INFO::Creating boxplot for categorical data, dysbiosisCD vs Bacteroides.ovatus## 2022-04-26 17:01:03 INFO::Creating boxplot for categorical data, dysbiosisCD vs Oscillibacter.unclassified## 2022-04-26 17:01:03 INFO::Creating boxplot for categorical data, dysbiosisCD vs Bacteroides.finegoldii## 2022-04-26 17:01:03 INFO::Creating boxplot for categorical data, dysbiosisCD vs Ruminococcus.bromii## 2022-04-26 17:01:04 INFO::Creating boxplot for categorical data, dysbiosisCD vs Coprobacillus.unclassified## 2022-04-26 17:01:04 INFO::Creating boxplot for categorical data, dysbiosisCD vs Parabacteroides.merdae## 2022-04-26 17:01:04 INFO::Creating boxplot for categorical data, dysbiosisCD vs Bacteroides.eggerthii## 2022-04-26 17:01:04 INFO::Creating boxplot for categorical data, dysbiosisCD vs Veillonella.dispar## 2022-04-26 17:01:05 INFO::Creating boxplot for categorical data, dysbiosisCD vs Collinsella.aerofaciens## 2022-04-26 17:01:05 INFO::Creating boxplot for categorical data, dysbiosisCD vs Bacteroides.caccae## 2022-04-26 17:01:05 INFO::Creating boxplot for categorical data, dysbiosisCD vs Ruminococcus.gnavus## 2022-04-26 17:01:05 INFO::Creating boxplot for categorical data, dysbiosisCD vs Paraprevotella.clara## 2022-04-26 17:01:05 INFO::Creating boxplot for categorical data, dysbiosisCD vs Bacteroides.xylanisolvens## 2022-04-26 17:01:06 INFO::Creating boxplot for categorical data, dysbiosisCD vs Ruminococcus.lactaris## 2022-04-26 17:01:06 INFO::Creating boxplot for categorical data, dysbiosisCD vs Paraprevotella.unclassified## 2022-04-26 17:01:06 INFO::Creating boxplot for categorical data, dysbiosisCD vs Ruminococcus.torques## 2022-04-26 17:01:06 INFO::Creating boxplot for categorical data, dysbiosisCD vs C2likevirus.unclassified## 2022-04-26 17:01:06 INFO::Creating boxplot for categorical data, dysbiosisCD vs Bacteroides.faecis## 2022-04-26 17:01:07 INFO::Creating boxplot for categorical data, dysbiosisCD vs Bifidobacterium.longum## 2022-04-26 17:01:07 INFO::Creating boxplot for categorical data, dysbiosisCD vs Eubacterium.siraeum## 2022-04-26 17:01:07 INFO::Creating boxplot for categorical data, dysbiosisCD vs Dialister.invisus## 2022-04-26 17:01:07 INFO::Creating boxplot for categorical data, dysbiosisCD vs Parabacteroides.unclassified## 2022-04-26 17:01:10 INFO::Plotting data for metadata number 2, dysbiosisUC
## 2022-04-26 17:01:10 INFO::Creating boxplot for categorical data, dysbiosisUC vs Subdoligranulum.unclassified## 2022-04-26 17:01:10 INFO::Creating boxplot for categorical data, dysbiosisUC vs Prevotella.copri## 2022-04-26 17:01:10 INFO::Creating boxplot for categorical data, dysbiosisUC vs Bacteroides.fragilis## 2022-04-26 17:01:10 INFO::Creating boxplot for categorical data, dysbiosisUC vs Bacteroides.caccae## 2022-04-26 17:01:11 INFO::Creating boxplot for categorical data, dysbiosisUC vs Faecalibacterium.prausnitzii## 2022-04-26 17:01:11 INFO::Creating boxplot for categorical data, dysbiosisUC vs Oscillibacter.unclassified## 2022-04-26 17:01:11 INFO::Creating boxplot for categorical data, dysbiosisUC vs Bacteroides.uniformis## 2022-04-26 17:01:12 INFO::Creating boxplot for categorical data, dysbiosisUC vs Eubacterium.hallii## 2022-04-26 17:01:12 INFO::Creating boxplot for categorical data, dysbiosisUC vs Bacteroides.faecis## 2022-04-26 17:01:12 INFO::Creating boxplot for categorical data, dysbiosisUC vs Klebsiella.pneumoniae## 2022-04-26 17:01:12 INFO::Creating boxplot for categorical data, dysbiosisUC vs Coprobacillus.unclassified## 2022-04-26 17:01:12 INFO::Creating boxplot for categorical data, dysbiosisUC vs Bacteroides.stercoris## 2022-04-26 17:01:13 INFO::Creating boxplot for categorical data, dysbiosisUC vs Eubacterium.rectale## 2022-04-26 17:01:13 INFO::Creating boxplot for categorical data, dysbiosisUC vs Ruminococcus.gnavus## 2022-04-26 17:01:13 INFO::Creating boxplot for categorical data, dysbiosisUC vs Bacteroides.ovatus## 2022-04-26 17:01:13 INFO::Creating boxplot for categorical data, dysbiosisUC vs Lachnospiraceae.bacterium.3.1.46FAA## 2022-04-26 17:01:13 INFO::Creating boxplot for categorical data, dysbiosisUC vs Eubacterium.siraeum## 2022-04-26 17:01:14 INFO::Creating boxplot for categorical data, dysbiosisUC vs Alistipes.putredinis## 2022-04-26 17:01:14 INFO::Creating boxplot for categorical data, dysbiosisUC vs Ruminococcus.obeum## 2022-04-26 17:01:14 INFO::Creating boxplot for categorical data, dysbiosisUC vs Escherichia.coli## 2022-04-26 17:01:14 INFO::Creating boxplot for categorical data, dysbiosisUC vs Bacteroides.eggerthii## 2022-04-26 17:01:14 INFO::Creating boxplot for categorical data, dysbiosisUC vs Clostridium.leptum## 2022-04-26 17:01:15 INFO::Creating boxplot for categorical data, dysbiosisUC vs Barnesiella.intestinihominis## 2022-04-26 17:01:15 INFO::Creating boxplot for categorical data, dysbiosisUC vs Alistipes.shahii## 2022-04-26 17:01:15 INFO::Creating boxplot for categorical data, dysbiosisUC vs Collinsella.aerofaciens## 2022-04-26 17:01:15 INFO::Creating boxplot for categorical data, dysbiosisUC vs Clostridium.nexile## 2022-04-26 17:01:15 INFO::Creating boxplot for categorical data, dysbiosisUC vs Bacteroides.xylanisolvens## 2022-04-26 17:01:16 INFO::Creating boxplot for categorical data, dysbiosisUC vs Parabacteroides.goldsteinii## 2022-04-26 17:01:16 INFO::Creating boxplot for categorical data, dysbiosisUC vs Eubacterium.ventriosum## 2022-04-26 17:01:16 INFO::Creating boxplot for categorical data, dysbiosisUC vs Coprococcus.comes## 2022-04-26 17:01:16 INFO::Creating boxplot for categorical data, dysbiosisUC vs Bifidobacterium.adolescentis## 2022-04-26 17:01:16 INFO::Creating boxplot for categorical data, dysbiosisUC vs Veillonella.atypica## 2022-04-26 17:01:19 INFO::Plotting data for metadata number 3, dysbiosisnonIBD
## 2022-04-26 17:01:19 INFO::Creating boxplot for categorical data, dysbiosisnonIBD vs Faecalibacterium.prausnitzii## 2022-04-26 17:01:19 INFO::Creating boxplot for categorical data, dysbiosisnonIBD vs Eubacterium.rectale## 2022-04-26 17:01:19 INFO::Creating boxplot for categorical data, dysbiosisnonIBD vs Prevotella.copri## 2022-04-26 17:01:20 INFO::Creating boxplot for categorical data, dysbiosisnonIBD vs Eubacterium.sp.3.1.31## 2022-04-26 17:01:20 INFO::Creating boxplot for categorical data, dysbiosisnonIBD vs Roseburia.hominis## 2022-04-26 17:01:20 INFO::Creating boxplot for categorical data, dysbiosisnonIBD vs Odoribacter.splanchnicus## 2022-04-26 17:01:20 INFO::Creating boxplot for categorical data, dysbiosisnonIBD vs Bilophila.unclassified## 2022-04-26 17:01:20 INFO::Creating boxplot for categorical data, dysbiosisnonIBD vs Escherichia.coli## 2022-04-26 17:01:21 INFO::Creating boxplot for categorical data, dysbiosisnonIBD vs Subdoligranulum.unclassified## 2022-04-26 17:01:21 INFO::Creating boxplot for categorical data, dysbiosisnonIBD vs Clostridium.leptum## 2022-04-26 17:01:21 INFO::Creating boxplot for categorical data, dysbiosisnonIBD vs Bacteroides.fragilis## 2022-04-26 17:01:21 INFO::Creating boxplot for categorical data, dysbiosisnonIBD vs Klebsiella.pneumoniae## 2022-04-26 17:01:21 INFO::Creating boxplot for categorical data, dysbiosisnonIBD vs Ruminococcus.torques## 2022-04-26 17:01:22 INFO::Creating boxplot for categorical data, dysbiosisnonIBD vs Clostridium.clostridioforme## 2022-04-26 17:01:22 INFO::Creating boxplot for categorical data, dysbiosisnonIBD vs Alistipes.putredinis## 2022-04-26 17:01:22 INFO::Creating boxplot for categorical data, dysbiosisnonIBD vs Coprobacillus.unclassified## 2022-04-26 17:01:22 INFO::Creating boxplot for categorical data, dysbiosisnonIBD vs Eubacterium.eligens## 2022-04-26 17:01:22 INFO::Creating boxplot for categorical data, dysbiosisnonIBD vs Veillonella.dispar## 2022-04-26 17:01:23 INFO::Creating boxplot for categorical data, dysbiosisnonIBD vs Bacteroides.eggerthii## 2022-04-26 17:01:23 INFO::Creating boxplot for categorical data, dysbiosisnonIBD vs Lachnospiraceae.bacterium.3.1.46FAA## 2022-04-26 17:01:23 INFO::Creating boxplot for categorical data, dysbiosisnonIBD vs Ruminococcus.obeum## 2022-04-26 17:01:23 INFO::Creating boxplot for categorical data, dysbiosisnonIBD vs Ruminococcus.bromii## 2022-04-26 17:01:23 INFO::Creating boxplot for categorical data, dysbiosisnonIBD vs Parasutterella.excrementihominis## 2022-04-26 17:01:24 INFO::Creating boxplot for categorical data, dysbiosisnonIBD vs Alistipes.shahii## 2022-04-26 17:01:24 INFO::Creating boxplot for categorical data, dysbiosisnonIBD vs Barnesiella.intestinihominis## 2022-04-26 17:01:24 INFO::Creating boxplot for categorical data, dysbiosisnonIBD vs Burkholderiales.bacterium.1.1.47## 2022-04-26 17:01:24 INFO::Creating boxplot for categorical data, dysbiosisnonIBD vs Paraprevotella.unclassified## 2022-04-26 17:01:27 INFO::Plotting data for metadata number 4, antibiotics
## 2022-04-26 17:01:27 INFO::Creating boxplot for categorical data, antibiotics vs Escherichia.coli## 2022-04-26 17:01:27 INFO::Creating boxplot for categorical data, antibiotics vs Roseburia.inulinivorans## 2022-04-26 17:01:27 INFO::Creating boxplot for categorical data, antibiotics vs Roseburia.intestinalis## 2022-04-26 17:01:27 INFO::Creating boxplot for categorical data, antibiotics vs Bacteroidales.bacterium.ph8## 2022-04-26 17:01:27 INFO::Creating boxplot for categorical data, antibiotics vs Roseburia.hominis## 2022-04-26 17:01:28 INFO::Creating boxplot for categorical data, antibiotics vs Dialister.invisus## 2022-04-26 17:01:28 INFO::Creating boxplot for categorical data, antibiotics vs Klebsiella.pneumoniae## 2022-04-26 17:01:28 INFO::Creating boxplot for categorical data, antibiotics vs Eubacterium.rectale## 2022-04-26 17:01:28 INFO::Creating boxplot for categorical data, antibiotics vs Sutterella.wadsworthensis## 2022-04-26 17:01:28 INFO::Creating boxplot for categorical data, antibiotics vs Bacteroides.thetaiotaomicron## 2022-04-26 17:01:28 INFO::Creating boxplot for categorical data, antibiotics vs Ruminococcus.callidus## 2022-04-26 17:01:29 INFO::Creating boxplot for categorical data, antibiotics vs Bacteroides.finegoldii## 2022-04-26 17:01:29 INFO::Creating boxplot for categorical data, antibiotics vs Alistipes.onderdonkii## 2022-04-26 17:01:29 INFO::Creating boxplot for categorical data, antibiotics vs Dorea.longicatena## 2022-04-26 17:01:29 INFO::Creating boxplot for categorical data, antibiotics vs Bifidobacterium.pseudocatenulatum## 2022-04-26 17:01:29 INFO::Creating boxplot for categorical data, antibiotics vs Bifidobacterium.longum## 2022-04-26 17:01:29 INFO::Creating boxplot for categorical data, antibiotics vs Clostridium.bolteae## 2022-04-26 17:01:30 INFO::Creating boxplot for categorical data, antibiotics vs Clostridium.hathewayi## 2022-04-26 17:01:30 INFO::Creating boxplot for categorical data, antibiotics vs Faecalibacterium.prausnitzii## 2022-04-26 17:01:30 INFO::Creating boxplot for categorical data, antibiotics vs Ruminococcus.bromii## 2022-04-26 17:01:30 INFO::Creating boxplot for categorical data, antibiotics vs Eubacterium.eligens## 2022-04-26 17:01:30 INFO::Creating boxplot for categorical data, antibiotics vs Ruminococcus.obeum## 2022-04-26 17:01:31 INFO::Creating boxplot for categorical data, antibiotics vs Bacteroides.fragilis## 2022-04-26 17:01:31 INFO::Creating boxplot for categorical data, antibiotics vs Escherichia.unclassified## 2022-04-26 17:01:31 INFO::Creating boxplot for categorical data, antibiotics vs Bilophila.unclassified## 2022-04-26 17:01:31 INFO::Creating boxplot for categorical data, antibiotics vs Eubacterium.sp.3.1.31## 2022-04-26 17:01:31 INFO::Creating boxplot for categorical data, antibiotics vs Alistipes.putredinis## 2022-04-26 17:01:32 INFO::Creating boxplot for categorical data, antibiotics vs Veillonella.parvula## 2022-04-26 17:01:32 INFO::Creating boxplot for categorical data, antibiotics vs Bacteroides.caccae## 2022-04-26 17:01:32 INFO::Creating boxplot for categorical data, antibiotics vs Parabacteroides.distasonis## 2022-04-26 17:01:32 INFO::Creating boxplot for categorical data, antibiotics vs Parabacteroides.merdae## 2022-04-26 17:01:32 INFO::Creating boxplot for categorical data, antibiotics vs Parasutterella.excrementihominis## 2022-04-26 17:01:32 INFO::Creating boxplot for categorical data, antibiotics vs Bifidobacterium.adolescentis## 2022-04-26 17:01:33 INFO::Creating boxplot for categorical data, antibiotics vs Lachnospiraceae.bacterium.1.1.57FAA## 2022-04-26 17:01:33 INFO::Creating boxplot for categorical data, antibiotics vs Akkermansia.muciniphila## 2022-04-26 17:01:33 INFO::Creating boxplot for categorical data, antibiotics vs Clostridium.symbiosum## 2022-04-26 17:01:33 INFO::Creating boxplot for categorical data, antibiotics vs Paraprevotella.clara## 2022-04-26 17:01:33 INFO::Creating boxplot for categorical data, antibiotics vs Bacteroides.faecis## 2022-04-26 17:01:36 INFO::Plotting data for metadata number 5, age
## 2022-04-26 17:01:36 INFO::Creating scatter plot for continuous data, age vs Clostridium.clostridioforme## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 19 rows containing missing values (geom_point).## 2022-04-26 17:01:36 INFO::Creating scatter plot for continuous data, age vs Haemophilus.parainfluenzae## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 19 rows containing missing values (geom_point).## 2022-04-26 17:01:36 INFO::Creating scatter plot for continuous data, age vs Bifidobacterium.pseudocatenulatum## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 19 rows containing missing values (geom_point).## 2022-04-26 17:01:36 INFO::Creating scatter plot for continuous data, age vs Subdoligranulum.unclassified## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 19 rows containing missing values (geom_point).## 2022-04-26 17:01:37 INFO::Creating scatter plot for continuous data, age vs Bacteroides.intestinalis## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 19 rows containing missing values (geom_point).## 2022-04-26 17:01:37 INFO::Creating scatter plot for continuous data, age vs Faecalibacterium.prausnitzii## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 19 rows containing missing values (geom_point).## 2022-04-26 17:01:37 INFO::Creating scatter plot for continuous data, age vs Clostridium.symbiosum## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 19 rows containing missing values (geom_point).## 2022-04-26 17:01:37 INFO::Creating scatter plot for continuous data, age vs Ruminococcus.bromii## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 19 rows containing missing values (geom_point).## 2022-04-26 17:01:37 INFO::Creating scatter plot for continuous data, age vs Akkermansia.muciniphila## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 19 rows containing missing values (geom_point).## 2022-04-26 17:01:38 INFO::Creating scatter plot for continuous data, age vs Veillonella.dispar## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 19 rows containing missing values (geom_point).## 2022-04-26 17:01:38 INFO::Creating scatter plot for continuous data, age vs Collinsella.aerofaciens## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 19 rows containing missing values (geom_point).## 2022-04-26 17:01:38 INFO::Creating scatter plot for continuous data, age vs Roseburia.intestinalis## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 19 rows containing missing values (geom_point).## 2022-04-26 17:01:38 INFO::Creating scatter plot for continuous data, age vs Bacteroides.thetaiotaomicron## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 19 rows containing missing values (geom_point).## 2022-04-26 17:01:38 INFO::Creating scatter plot for continuous data, age vs Dialister.invisus## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 19 rows containing missing values (geom_point).## 2022-04-26 17:01:39 INFO::Creating scatter plot for continuous data, age vs Acidaminococcus.unclassified## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 19 rows containing missing values (geom_point).## 2022-04-26 17:01:39 INFO::Creating scatter plot for continuous data, age vs Veillonella.unclassified## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 19 rows containing missing values (geom_point).## 2022-04-26 17:01:39 INFO::Creating scatter plot for continuous data, age vs Bifidobacterium.longum## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 19 rows containing missing values (geom_point).## 2022-04-26 17:01:39 INFO::Creating scatter plot for continuous data, age vs Alistipes.unclassified## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 19 rows containing missing values (geom_point).## 2022-04-26 17:01:39 INFO::Creating scatter plot for continuous data, age vs Bacteroidales.bacterium.ph8## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 19 rows containing missing values (geom_point).## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 19 rows containing missing values (geom_point).## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 19 rows containing missing values (geom_point).## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 19 rows containing missing values (geom_point).## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 19 rows containing missing values (geom_point).## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 19 rows containing missing values (geom_point).## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 19 rows containing missing values (geom_point).## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 19 rows containing missing values (geom_point).## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 19 rows containing missing values (geom_point).## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 19 rows containing missing values (geom_point).## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 19 rows containing missing values (geom_point).## 2022-04-26 17:01:42 INFO::Plotting data for metadata number 6, diagnosis
## 2022-04-26 17:01:42 INFO::Creating boxplot for categorical data, diagnosis vs Clostridium.clostridioforme## 2022-04-26 17:01:43 INFO::Creating boxplot for categorical data, diagnosis vs Clostridium.bolteae## 2022-04-26 17:01:43 INFO::Creating boxplot for categorical data, diagnosis vs Alistipes.putredinis## 2022-04-26 17:01:43 INFO::Creating boxplot for categorical data, diagnosis vs Oscillibacter.unclassified## 2022-04-26 17:01:43 INFO::Creating boxplot for categorical data, diagnosis vs Alistipes.shahii## 2022-04-26 17:01:44 INFO::Creating boxplot for categorical data, diagnosis vs Collinsella.aerofaciens## 2022-04-26 17:01:44 INFO::Creating boxplot for categorical data, diagnosis vs Akkermansia.muciniphila## 2022-04-26 17:01:44 INFO::Creating boxplot for categorical data, diagnosis vs Coprobacillus.unclassified## 2022-04-26 17:01:44 INFO::Creating boxplot for categorical data, diagnosis vs Parabacteroides.goldsteinii## 2022-04-26 17:01:44 INFO::Creating boxplot for categorical data, diagnosis vs Ruminococcus.bromii## 2022-04-26 17:01:45 INFO::Creating boxplot for categorical data, diagnosis vs Ruminococcus.callidus## 2022-04-26 17:01:45 INFO::Creating boxplot for categorical data, diagnosis vs Sutterella.wadsworthensis## 2022-04-26 17:01:45 INFO::Creating boxplot for categorical data, diagnosis vs Ruminococcus.bromii## 2022-04-26 17:01:45 INFO::Creating boxplot for categorical data, diagnosis vs Akkermansia.muciniphila## 2022-04-26 17:01:46 INFO::Creating boxplot for categorical data, diagnosis vs Ruminococcus.obeum## 2022-04-26 17:01:46 INFO::Creating boxplot for categorical data, diagnosis vs Bacteroidales.bacterium.ph8## 2022-04-26 17:01:46 INFO::Creating boxplot for categorical data, diagnosis vs Bifidobacterium.adolescentis## 2022-04-26 17:01:46 INFO::Creating boxplot for categorical data, diagnosis vs Bacteroides.fragilis## 2022-04-26 17:01:47 INFO::Creating boxplot for categorical data, diagnosis vs Alistipes.finegoldii## 2022-04-26 17:01:47 INFO::Creating boxplot for categorical data, diagnosis vs Clostridium.leptum## 2022-04-26 17:01:47 INFO::Creating boxplot for categorical data, diagnosis vs Sutterella.wadsworthensis## 2022-04-26 17:01:47 INFO::Creating boxplot for categorical data, diagnosis vs Escherichia.unclassified## 2022-04-26 17:01:48 INFO::Creating boxplot for categorical data, diagnosis vs Ruminococcus.lactaris## 2022-04-26 17:01:48 INFO::Creating boxplot for categorical data, diagnosis vs Bilophila.unclassified## 2022-04-26 17:01:48 INFO::Creating boxplot for categorical data, diagnosis vs Ruminococcus.gnavus## 2022-04-26 17:01:48 INFO::Creating boxplot for categorical data, diagnosis vs Subdoligranulum.unclassified## 2022-04-26 17:01:48 INFO::Creating boxplot for categorical data, diagnosis vs Coprobacillus.unclassified## 2022-04-26 17:01:49 INFO::Creating boxplot for categorical data, diagnosis vs Parabacteroides.unclassified
Session Info
Session info from running the demo in R can be displayed with the following command.
sessionInfo()## R version 4.2.0 RC (2022-04-19 r82224)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 20.04.4 LTS
##
## Matrix products: default
## BLAS: /home/biocbuild/bbs-3.15-bioc/R/lib/libRblas.so
## LAPACK: /home/biocbuild/bbs-3.15-bioc/R/lib/libRlapack.so
##
## locale:
## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
## [3] LC_TIME=en_GB 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] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] Maaslin2_1.10.0
##
## loaded via a namespace (and not attached):
## [1] Rcpp_1.0.8.3 mvtnorm_1.1-3 lattice_0.20-45
## [4] assertthat_0.2.1 digest_0.6.29 utf8_1.2.2
## [7] R6_2.5.1 pcaPP_2.0-1 evaluate_0.15
## [10] highr_0.9 ggplot2_3.3.5 pillar_1.7.0
## [13] rlang_1.0.2 minqa_1.2.4 data.table_1.14.2
## [16] nloptr_2.0.0 jquerylib_0.1.4 Matrix_1.4-1
## [19] hash_2.2.6.2 rmarkdown_2.14 labeling_0.4.2
## [22] splines_4.2.0 lme4_1.1-29 stringr_1.4.0
## [25] pheatmap_1.0.12 munsell_0.5.0 compiler_4.2.0
## [28] numDeriv_2016.8-1.1 xfun_0.30 pkgconfig_2.0.3
## [31] lmerTest_3.1-3 biglm_0.9-2.1 mgcv_1.8-40
## [34] htmltools_0.5.2 tidyselect_1.1.2 tibble_3.1.6
## [37] logging_0.10-108 fansi_1.0.3 crayon_1.5.1
## [40] dplyr_1.0.8 withr_2.5.0 MASS_7.3-57
## [43] grid_4.2.0 nlme_3.1-157 jsonlite_1.8.0
## [46] gtable_0.3.0 lifecycle_1.0.1 DBI_1.1.2
## [49] magrittr_2.0.3 scales_1.2.0 cli_3.3.0
## [52] stringi_1.7.6 pbapply_1.5-0 farver_2.1.0
## [55] getopt_1.20.3 lpsymphony_1.24.0 robustbase_0.95-0
## [58] optparse_1.7.1 bslib_0.3.1 ellipsis_0.3.2
## [61] generics_0.1.2 vctrs_0.4.1 boot_1.3-28
## [64] RColorBrewer_1.1-3 tools_4.2.0 glue_1.6.2
## [67] DEoptimR_1.0-11 purrr_0.3.4 parallel_4.2.0
## [70] fastmap_1.1.0 yaml_2.3.5 colorspace_2.0-3
## [73] knitr_1.38 sass_0.4.1Options
Run MaAsLin2 help to print a list of the options and the default settings.
$ Maaslin2.R –help Usage: ./R/Maaslin2.R options <data.tsv> <metadata.tsv>
Options: -h, –help Show this help message and exit
-a MIN_ABUNDANCE, --min_abundance=MIN_ABUNDANCE
The minimum abundance for each feature [ Default: 0 ]
-p MIN_PREVALENCE, --min_prevalence=MIN_PREVALENCE
The minimum percent of samples for which a feature
is detected at minimum abundance [ Default: 0.1 ]
-b MIN_VARIANCE, --min_variance=MIN_VARIANCE
Keep features with variance greater than
[ Default: 0.0 ]
-s MAX_SIGNIFICANCE, --max_significance=MAX_SIGNIFICANCE
The q-value threshold for significance [ Default: 0.25 ]
-n NORMALIZATION, --normalization=NORMALIZATION
The normalization method to apply [ Default: TSS ]
[ Choices: TSS, CLR, CSS, NONE, TMM ]
-t TRANSFORM, --transform=TRANSFORM
The transform to apply [ Default: LOG ]
[ Choices: LOG, LOGIT, AST, NONE ]
-m ANALYSIS_METHOD, --analysis_method=ANALYSIS_METHOD
The analysis method to apply [ Default: LM ]
[ Choices: LM, CPLM, NEGBIN, ZINB ]
-r RANDOM_EFFECTS, --random_effects=RANDOM_EFFECTS
The random effects for the model, comma-delimited
for multiple effects [ Default: none ]
-f FIXED_EFFECTS, --fixed_effects=FIXED_EFFECTS
The fixed effects for the model, comma-delimited
for multiple effects [ Default: all ]
-c CORRECTION, --correction=CORRECTION
The correction method for computing the
q-value [ Default: BH ]
-z STANDARDIZE, --standardize=STANDARDIZE
Apply z-score so continuous metadata are
on the same scale [ Default: TRUE ]
-l PLOT_HEATMAP, --plot_heatmap=PLOT_HEATMAP
Generate a heatmap for the significant
associations [ Default: TRUE ]
-i HEATMAP_FIRST_N, --heatmap_first_n=HEATMAP_FIRST_N
In heatmap, plot top N features with significant
associations [ Default: TRUE ]
-o PLOT_SCATTER, --plot_scatter=PLOT_SCATTER
Generate scatter plots for the significant
associations [ Default: TRUE ]
-e CORES, --cores=CORES
The number of R processes to run in parallel
[ Default: 1 ]
-d REFERENCE, --reference=REFERENCE
The factor to use as a reference for a variable
with more than two levels provided as a string
of 'variable,reference' semi-colon delimited
for multiple variables [ Default: NA ] Troubleshooting
- Question: When I run from the command line I see the error
Maaslin2.R: command not found. How do I fix this?- Answer: Provide the full path to the executable when running Maaslin2.R.
- Question: When I run as a function I see the error
Error in library(Maaslin2): there is no package called 'Maaslin2'. How do I fix this?- Answer: Install the R package and then try loading the library again.
- Question: When I try to install the R package I see errors about dependencies not being installed. Why is this?
- Answer: Installing the R package will not automatically install the packages MaAsLin2 requires. Please install the dependencies and then install the MaAsLin2 R package.