Commit 131fc2b4 authored by Konrad Zych's avatar Konrad Zych

removing srcdir

parent 9802edad
Pipeline #3051 failed with stage
in 3 minutes 37 seconds
......@@ -13,18 +13,18 @@ test:
stage: test
script:
- Rscript 00_setup.r
- Rscript 01_validate_data.r --srcdir .. --metadata_in num_metadata_cancer-vs-healthy_study-pop-I_N141_tax_profile_mocat_bn_genus.tsv --metadata_out valMetaData.tsv --label_in label_cancer-vs-healthy_study-pop-I_N141_tax_profile_mocat_bn_genus.tsv --label_out valLabel.tsv --feat_in feat_cancer-vs-healthy_study-pop-I_N141_tax_profile_mocat_bn_genus.tsv --feat_out valFeat.tsv
- Rscript 02_select_samples.r --srcdir .. --metadata_in valMetaData.tsv --metadata_out valMetaData_sel.tsv --label_in valLabel.tsv --label_out valLabel_sel.tsv --feat_in valFeat.tsv --feat_out valFeat_sel.tsv --filter_var="age" --allowed_range="[0,120]"
- Rscript 03_check_for_confounders.r --srcdir .. --metadata_in valMetaData_sel.tsv --plot metaCheck.pdf --label_in valLabel_sel.tsv
- Rscript 01_validate_data.r --metadata_in num_metadata_cancer-vs-healthy_study-pop-I_N141_tax_profile_mocat_bn_genus.tsv --metadata_out valMetaData.tsv --label_in label_cancer-vs-healthy_study-pop-I_N141_tax_profile_mocat_bn_genus.tsv --label_out valLabel.tsv --feat_in feat_cancer-vs-healthy_study-pop-I_N141_tax_profile_mocat_bn_genus.tsv --feat_out valFeat.tsv
- Rscript 02_select_samples.r --metadata_in valMetaData.tsv --metadata_out valMetaData_sel.tsv --label_in valLabel.tsv --label_out valLabel_sel.tsv --feat_in valFeat.tsv --feat_out valFeat_sel.tsv --filter_var="age" --allowed_range="[0,120]"
- Rscript 03_check_for_confounders.r --metadata_in valMetaData_sel.tsv --plot metaCheck.pdf --label_in valLabel_sel.tsv
- Rscript 04_filter_features.r --feat_in valFeat_sel.tsv --feat_out valFeat_sel_filtered.tsv --method="abundance" --cutoff="0.001" --recomp_prop="FALSE" --rm_unmapped="TRUE"
- Rscript 05_check_associations.r --srcdir .. --feat_in valFeat_sel_filtered.tsv --label_in valLabel_sel.tsv --plot assoc.pdf --col_scheme="RdYlBu" --alpha="0.7" --min_fc="0" --mult_test="fdr" --max_show="50" --detect_limit="1e-06" --plot_type="bean"
- Rscript 05_check_associations.r --feat_in valFeat_sel_filtered.tsv --label_in valLabel_sel.tsv --plot assoc.pdf --col_scheme="RdYlBu" --alpha="0.7" --min_fc="0" --mult_test="fdr" --max_show="50" --detect_limit="1e-06" --plot_type="bean"
- Rscript 06_normalize_features.r --feat_in valFeat_sel_filtered.tsv --feat_out valFeat_sel_norm.tsv --param_out param_out.tsv --method="log.unit" --log_n0="1e-08" --sd_min_quantile="0.2" --vector_norm="2" --norm_margin="1"
- Rscript 07_add_metadata_as_predictor.r --feat_in valFeat_sel_norm.tsv --feat_out valFeat_sel_norm.tsv --metadata_in valMetaData_sel.tsv --pred_names="fobt" --std_meta="TRUE"
- Rscript 08_split_data.r --srcdir .. --label_in valLabel_sel.tsv --train_sets trainSets.tsv --test_sets testSets.tsv --num_folds="10" --resample="5" --stratify="TRUE" --inseparable="NULL" --metadata_in valMetaData_sel.tsv
- Rscript 09_train_models.r --srcdir .. --feat_in valFeat_sel_norm.tsv --label_in valLabel_sel.tsv --method="lasso" --train_sets trainSets.tsv --mlr_models_list models.RData --stratify="TRUE" --sel_criterion="auprc" --min_nonzero_coeff="2"
- Rscript 10_make_predictions.r --srcdir .. --label_in valLabel_sel.tsv --feat_in valFeat_sel_norm.tsv --test_sets testSets.tsv --pred pred.tsv --mlr_models_list models.RData
- Rscript 11_evaluate_predictions.r --srcdir .. --label_in valLabel_sel.tsv --plot evalPlot.pdf --pred pred.tsv
- Rscript 12_interpret_model.r --srcdir .. --label_in valLabel_sel.tsv --feat_in valFeat_sel_norm.tsv --origin_feat valFeat_sel.tsv --metadata_in valMetaData_sel.tsv --mlr_models_list models.RData --plot interpretation.pdf --pred pred.tsv --col_scheme="BrBG" --heatmap_type="zscore" --consens_thres="0.5"
- Rscript 08_split_data.r --label_in valLabel_sel.tsv --train_sets trainSets.tsv --test_sets testSets.tsv --num_folds="10" --resample="5" --stratify="TRUE" --inseparable="NULL" --metadata_in valMetaData_sel.tsv
- Rscript 09_train_models.r --feat_in valFeat_sel_norm.tsv --label_in valLabel_sel.tsv --method="lasso" --train_sets trainSets.tsv --mlr_models_list models.RData --stratify="TRUE" --sel_criterion="auprc" --min_nonzero_coeff="2"
- Rscript 10_make_predictions.r --label_in valLabel_sel.tsv --feat_in valFeat_sel_norm.tsv --test_sets testSets.tsv --pred pred.tsv --mlr_models_list models.RData
- Rscript 11_evaluate_predictions.r --label_in valLabel_sel.tsv --plot evalPlot.pdf --pred pred.tsv
- Rscript 12_interpret_model.r --label_in valLabel_sel.tsv --feat_in valFeat_sel_norm.tsv --origin_feat valFeat_sel.tsv --metadata_in valMetaData_sel.tsv --mlr_models_list models.RData --plot interpretation.pdf --pred pred.tsv --col_scheme="BrBG" --heatmap_type="zscore" --consens_thres="0.5"
only:
- master
- development
......
# Generated by roxygen2: do not edit by hand
export(add.meta.pred)
export(appendDirName)
export(assign.fold)
export(check.associations)
export(confounder.check)
......
......@@ -131,17 +131,6 @@ read.meta <- function(fn.in.meta){
invisible(meta)
}
#' @title Append source directory path
#' @description Append / at the end of the name of the directory path if it is not there
#' @param source.dir string with path to the source directory
#' @export
#' @return string with / at the end
appendDirName <- function(source.dir){
if (substr(source.dir, nchar(source.dir), nchar(source.dir)) != '/') {
source.dir <- paste(source.dir, '/', sep='')
}
invisible(source.dir)
}
##### auxiliary function to trim whitespace from string
# returns string without leading or trailing whitespace
......
......@@ -17,7 +17,6 @@ suppressMessages(library('SIAMCAT'))
# define arguments
option_list <- list(
make_option(c('-s', '--srcdir'), type='character', help='Source directory of this and other utility scripts'),
make_option('--metadata_in', type='character', help='Input file containing meta-data'),
make_option('--metadata_out', type='character', default = "meta_validated.tsv",
help='Output file to which validated meta-data is written'),
......@@ -35,7 +34,6 @@ opt <- parse_args(OptionParser(option_list=option_list))
# print parameters of the run
cat("=== 01_data_validator.r\n")
cat("=== Paramaters of the run:\n\n")
cat('srcdir =', opt$srcdir, '\n')
cat('metadata_in =', opt$metadata_in, '\n')
cat('metadata_out =', opt$metadata_out, '\n')
cat('label_in =', opt$label_in, '\n')
......@@ -44,7 +42,6 @@ cat('feat_in =', opt$feat_in, '\n')
cat('feat_out =', opt$feat_out, '\n')
cat('\n')
source.dir <- appendDirName(opt$srcdir)
start.time <- proc.time()[1]
# reading in the files
......
......@@ -17,7 +17,6 @@ suppressMessages(library('optparse'))
suppressMessages(library('SIAMCAT'))
# define arguments
option_list <- list(
make_option(c('-s', '--srcdir'), type='character', help='Source directory of this and other utility scripts'),
make_option('--metadata_in', type='character', help='Input file containing meta-data'),
make_option('--metadata_out', type='character', help='Output file to which meta-data after selection is written'),
make_option('--label_in', type='character', help='Input file containing labels'),
......@@ -33,7 +32,6 @@ opt <- parse_args(OptionParser(option_list=option_list))
# print parameters of the run
cat("=== 02_sample_selector.r\n")
cat("=== Paramaters of the run:\n\n")
cat('srcdir =', opt$srcdir, '\n')
cat('metadata_in =', opt$metadata_in, '\n')
cat('metadata_out =', opt$metadata_out, '\n')
cat('label_in =', opt$label_in, '\n')
......@@ -44,7 +42,6 @@ cat('filter_var =', opt$filter_var, '\n')
cat('allowed_range =', opt$allowed_range, '\n')
cat('allowed_set =', opt$allowed_set, '\n')
source.dir <- appendDirName(opt$srcdir)
start.time <- proc.time()[1]
......
......@@ -17,7 +17,6 @@ suppressMessages(library('SIAMCAT'))
# define arguments
option_list <- list(
make_option(c('-s', '--srcdir'), type='character', help='Source directory of this and other utility scripts'),
make_option('--metadata_in', type='character', help='Input file containing meta-data'),
make_option('--label_in', type='character', help='Input file containing labels'),
make_option('--plot', type='character', help='Output pdf file which will contain resulting plots')
......@@ -28,13 +27,11 @@ opt <- parse_args(OptionParser(option_list=option_list))
# print parameters of the run
cat("=== 03_confounder_check.r\n")
cat("=== Paramaters of the run:\n\n")
cat('source.dir =', opt$srcdir, '\n')
cat('metadata_in =', opt$metadata_in, '\n')
cat('label_in =', opt$label_in, '\n')
cat('plot =', opt$plot, '\n')
cat('\n')
source.dir <- appendDirName(opt$srcdir)
start.time <- proc.time()[1]
......
......@@ -17,7 +17,6 @@ suppressMessages(library('SIAMCAT'))
# define arguments
option_list <- list(
make_option(c('-s', '--srcdir'), type='character', help='Source directory of this and other utility scripts'),
make_option('--label_in', type='character', help='Input file containing labels'),
make_option('--feat_in', type='character', help='Input file containing features'),
make_option('--plot', type='character', help='Output pdf file which will contain resulting plots'),
......@@ -35,7 +34,6 @@ option_list <- list(
opt <- parse_args(OptionParser(option_list=option_list))
cat("=== 05_association_check.r\n")
cat("=== Paramaters of the run:\n\n")
cat('srcdir =', opt$srcdir, '\n')
cat('label_in =', opt$label_in, '\n')
cat('feat_in =', opt$feat_in, '\n')
cat('plot =', opt$plot, '\n')
......@@ -50,7 +48,6 @@ cat('plot_type =', opt$plot_type, '\n')
cat('\n')
### If variable source.dir does not end with "/", append "/" to end of source.dir
source.dir <- appendDirName(opt$srcdir)
start.time <- proc.time()[1]
feat <- read.features(opt$feat_in)
......
......@@ -20,7 +20,6 @@ r.seed <- 223311
# define arguments
option_list <- list(
make_option(c('-s', '--srcdir'), type='character', help='Source directoyr of utility scripts'),
make_option('--label_in', type='character', help='Input file containing labels'),
make_option('--train_sets', type='character', help='Output file containing training sets'),
make_option('--test_sets', type='character', help='Output file containing test sets'),
......@@ -39,7 +38,6 @@ opt <- parse_args(OptionParser(option_list=option_list))
# print parameters of the run
cat("=== 08_data_splitter.r\n")
cat("=== Paramaters of the run:\n\n")
cat('source.dir =', opt$srcdir, '\n')
cat('label_in =', opt$label_in, '\n')
cat('train_sets =', opt$train_sets, '\n')
cat('test_sets =', opt$test_sets, '\n')
......@@ -50,7 +48,6 @@ cat('inseparable =', opt$inseparable, '\n')
cat('metadata_in =', opt$metadata_in, '\n')
cat('\n')
source.dir <- appendDirName(opt$srcdir)
start.time <- proc.time()[1]
set.seed(r.seed)
......
......@@ -25,7 +25,6 @@ DEBUG.CHECKS <- FALSE # performs additional checks (asserting tha
# define arguments
option_list <- list(
make_option(c('-s', '--srcdir'), type='character', help='Source directory of this and other utility scripts'),
make_option('--feat_in', type='character', help='Input file containing features'),
make_option('--label_in', type='character', help='Input file containing labels'),
make_option('--method', type='character', default='lasso', help='class of learner, directly passed to mlr::makeLearner'),
......@@ -47,7 +46,6 @@ DEBUG.CHECKS <- FALSE # performs additional checks (asserting tha
# print parameters of the run
cat("=== 09_plm_trainer.r\n")
cat("=== Paramaters of the run:\n\n")
cat('srcdir =', opt$srcdir, '\n')
cat('feat_in =', opt$feat_in, '\n')
cat('label_in =', opt$label_in, '\n')
cat('method =', opt$method, '\n')
......@@ -60,9 +58,6 @@ cat('param_set =', opt$param_set, '\n')
cat('\n')
opt$srcdir <- appendDirName(opt$srcdir)
# optional parameters will be reset to NULL if specified as 'NULL', 'NONE' or 'UNKNOWN'
if (toupper(opt$train_sets)=='NULL' || toupper(opt$train_sets)=='NONE' || toupper(opt$train_sets)=='UNKNOWN') {
opt$train_sets= NULL
......
......@@ -19,7 +19,6 @@ suppressMessages(library('methods'))
# define arguments
option_list = list(
make_option(c('-s', '--srcdir'), type='character', help='Source directory of this and other utility scripts'),
make_option('--feat_in', type='character', help='Input file containing features'),
make_option('--mlr_models_list', type='character', help='Input RData file containing the trained models'),
make_option('--label_in', type='character', default='NULL', help='Input file containing labels'),
......@@ -31,7 +30,6 @@ opt <- parse_args(OptionParser(option_list=option_list))
# print parameters of the run
cat("=== 10_plm_predictor.r\n")
cat("=== Paramaters of the run:\n\n")
cat('srcdir =', opt$srcdir, '\n')
cat('feat_in =', opt$feat_in, '\n')
cat('mlr_models_list =', opt$mlr_models_list,'\n')
cat('label_in =', opt$label_in, '\n')
......@@ -39,7 +37,6 @@ cat('test_sets =', opt$test_sets, '\n')
cat('pred =', opt$pred, '\n')
cat('\n')
source.dir <- appendDirName(opt$srcdir)
# optional parameters will be reset to NULL if specified as 'NULL', 'NONE' or 'UNKNOWN'
if (is.null(opt$test_sets)) {
opt$test_sets = NULL
......
......@@ -19,7 +19,6 @@ suppressMessages(library('SIAMCAT'))
# define arguments
option_list = list(
#make_option('--pkgdir', type='character', help='Source directory of dataprep'),
make_option(c('-s', '--srcdir'), type='character', help='Source directory of this and other utility scripts'),
make_option('--label_in', type='character', help='Input file containing labels'),
make_option('--pred', type='character', help='Input file containing the trained classification model(s)'),
make_option('--plot', type='character', help='Output file for plotting'),
......@@ -31,7 +30,6 @@ suppressMessages(library('SIAMCAT'))
opt <- parse_args(OptionParser(option_list=option_list))
cat("=== 11_model_evaler.r\n")
cat("=== Paramaters of the run:\n\n")
cat('srcdir =', opt$srcdir, '\n')
cat('label_in =', opt$label_in, '\n')
cat('pred =', opt$pred, '\n')
cat('plot =', opt$plot, '\n')
......@@ -40,7 +38,6 @@ cat('output_results =', opt$output_results, '\n')
cat('\n')
### If variable source.dir does not end with "/", append "/" to end of source.dir
source.dir <- appendDirName(opt$srcdir)
start.time <- proc.time()[1]
label <- read.labels(opt$label_in)
......
......@@ -18,7 +18,6 @@ suppressMessages(library('SIAMCAT'))
# define arguments
option_list <- list(
make_option(c('-s', '--srcdir'), type='character', help='Source directory of this and other utility scripts'),
make_option('--label_in', type='character', help='Input file containing labels'),
make_option('--feat_in', type='character', help='Input file containing features'),
make_option('--origin_feat', type='character', help='Input file containing unnormalized/filtered features'),
......@@ -38,7 +37,6 @@ option_list <- list(
opt <- parse_args(OptionParser(option_list=option_list))
cat("=== 12_model_interpretor.r\n")
cat("=== Paramaters of the run:\n\n")
cat('srcdir =', opt$srcdir, '\n')
cat('feat =', opt$feat, '\n')
cat('origin_feat. =', opt$origin_feat, '\n')
cat('metadata_in =', opt$metadata_in, '\n')
......@@ -51,12 +49,6 @@ cat('consens_thres =', opt$consens_thres, '\n')
cat('heatmap_type =', opt$heatmap_type, '\n')
cat('\n')
### If variable source.dir does not end with "/", append "/" to end of source.dir
source.dir <- appendDirName(opt$srcdir)
# TODO (remove last check)
# optional parameters will be reset to NULL if specified as 'NULL', 'NONE' or 'UNKNOWN'
### read features and labels
start.time <- proc.time()[1]
feat <- read.features(opt$feat)
......
Rscript 00_setup.r
Rscript 01_validate_data.r --srcdir .. --metadata_in num_metadata_cancer-vs-healthy_study-pop-I_N141_tax_profile_mocat_bn_genus.tsv --metadata_out valMetaData.tsv --label_in label_cancer-vs-healthy_study-pop-I_N141_tax_profile_mocat_bn_genus.tsv --label_out valLabel.tsv --feat_in feat_cancer-vs-healthy_study-pop-I_N141_tax_profile_mocat_bn_genus.tsv --feat_out valFeat.tsv
Rscript 02_select_samples.r --srcdir .. --metadata_in valMetaData.tsv --metadata_out valMetaData_sel.tsv --label_in valLabel.tsv --label_out valLabel_sel.tsv --feat_in valFeat.tsv --feat_out valFeat_sel.tsv --filter_var="age" --allowed_range="[0,120]"
Rscript 03_check_for_confounders.r --srcdir .. --metadata_in valMetaData_sel.tsv --plot metaCheck.pdf --label_in valLabel_sel.tsv
Rscript 01_validate_data.r --metadata_in num_metadata_cancer-vs-healthy_study-pop-I_N141_tax_profile_mocat_bn_genus.tsv --metadata_out valMetaData.tsv --label_in label_cancer-vs-healthy_study-pop-I_N141_tax_profile_mocat_bn_genus.tsv --label_out valLabel.tsv --feat_in feat_cancer-vs-healthy_study-pop-I_N141_tax_profile_mocat_bn_genus.tsv --feat_out valFeat.tsv
Rscript 02_select_samples.r --metadata_in valMetaData.tsv --metadata_out valMetaData_sel.tsv --label_in valLabel.tsv --label_out valLabel_sel.tsv --feat_in valFeat.tsv --feat_out valFeat_sel.tsv --filter_var="age" --allowed_range="[0,120]"
Rscript 03_check_for_confounders.r --metadata_in valMetaData_sel.tsv --plot metaCheck.pdf --label_in valLabel_sel.tsv
Rscript 04_filter_features.r --feat_in valFeat_sel.tsv --feat_out valFeat_sel_filtered.tsv --method="abundance" --cutoff="0.001" --recomp_prop="FALSE" --rm_unmapped="TRUE"
Rscript 05_check_associations.r --srcdir .. --feat_in valFeat_sel_filtered.tsv --label_in valLabel_sel.tsv --plot assoc.pdf --col_scheme="RdYlBu" --alpha="0.7" --min_fc="0" --mult_test="fdr" --max_show="50" --detect_limit="1e-06" --plot_type="bean"
Rscript 05_check_associations.r --feat_in valFeat_sel_filtered.tsv --label_in valLabel_sel.tsv --plot assoc.pdf --col_scheme="RdYlBu" --alpha="0.7" --min_fc="0" --mult_test="fdr" --max_show="50" --detect_limit="1e-06" --plot_type="bean"
Rscript 06_normalize_features.r --feat_in valFeat_sel_filtered.tsv --feat_out valFeat_sel_norm.tsv --param_out param_out.tsv --method="log.unit" --log_n0="1e-08" --sd_min_quantile="0.2" --vector_norm="2" --norm_feature="FALSE" --norm_sample="TRUE" --norm_global="FALSE"
Rscript 07_add_metadata_as_predictor.r --feat_in valFeat_sel_norm.tsv --feat_out valFeat_sel_norm.tsv --metadata_in valMetaData_sel.tsv --pred_names="fobt" --std_meta="TRUE"
Rscript 08_split_data.r --srcdir .. --label_in valLabel_sel.tsv --train_sets trainSets.tsv --test_sets testSets.tsv --num_folds="10" --resample="5" --stratify="TRUE" --inseparable="NULL" --metadata_in valMetaData_sel.tsv
Rscript 09_train_models.r --srcdir .. --feat_in valFeat_sel_norm.tsv --label_in valLabel_sel.tsv --method="lasso" --train_sets trainSets.tsv --mlr_models_list models.RData --stratify="TRUE" --sel_criterion="auprc" --min_nonzero_coeff="2" --model models.tsv --model_matrix model.matrix.txt
Rscript 10_make_predictions.r --srcdir .. --label_in valLabel_sel.tsv --feat_in valFeat_sel_norm.tsv --test_sets testSets.tsv --pred pred.tsv --mlr_models_list models.RData --model_matrix model.matrix.txt --hyperpars hyperpars.txt
Rscript 11_evaluate_predictions.r --srcdir .. --label valLabel_sel.tsv --plot evalPlot.pdf --pred pred.tsv
Rscript 12_interpret_model.r --srcdir .. --label valLabel_sel.tsv --feat valFeat_sel_norm.tsv --origin_feat valFeat_sel.tsv --meta valMetaData_sel.tsv --model models.tsv --plot interpretation.pdf --pred pred.tsv --col_scheme="BrBG" --heatmap_type="zscore" --consens_thres="0.5"
\ No newline at end of file
Rscript 08_split_data.r --label_in valLabel_sel.tsv --train_sets trainSets.tsv --test_sets testSets.tsv --num_folds="10" --resample="5" --stratify="TRUE" --inseparable="NULL" --metadata_in valMetaData_sel.tsv
Rscript 09_train_models.r --feat_in valFeat_sel_norm.tsv --label_in valLabel_sel.tsv --method="lasso" --train_sets trainSets.tsv --mlr_models_list models.RData --stratify="TRUE" --sel_criterion="auprc" --min_nonzero_coeff="2" --model models.tsv --model_matrix model.matrix.txt
Rscript 10_make_predictions.r --label_in valLabel_sel.tsv --feat_in valFeat_sel_norm.tsv --test_sets testSets.tsv --pred pred.tsv --mlr_models_list models.RData --model_matrix model.matrix.txt --hyperpars hyperpars.txt
Rscript 11_evaluate_predictions.r --label valLabel_sel.tsv --plot evalPlot.pdf --pred pred.tsv
Rscript 12_interpret_model.r --label valLabel_sel.tsv --feat valFeat_sel_norm.tsv --origin_feat valFeat_sel.tsv --meta valMetaData_sel.tsv --model models.tsv --plot interpretation.pdf --pred pred.tsv --col_scheme="BrBG" --heatmap_type="zscore" --consens_thres="0.5"
\ No newline at end of file
......@@ -59,6 +59,18 @@
</li>
<li>
<a href="reference/index.html">Reference</a>
</li>
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<a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
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<a href="articles/SIAMCAT_vignette.html">SIAMCAT: Statistical Inference of Associations between Microbial Communities And host phenoTypes</a>
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......
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......@@ -79,22 +91,25 @@
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<p>This function calculates for each feature the median log10 fold
change between the different classes found in labels.</p>
<p>This function calculates for each feature a pseudo-fold change
(geometrical mean of the difference between quantiles)
between the different classes found in labels.</p>
<p>Significance of the differences is computed for each feature using a wilcoxon
test followed by multiple hypothesis testing correction.</p>
<p>Additionally, the Area under the Receiver Operating Characteristic Curve
'(AU-ROC) is computed for the features found to be associated with the two
different classes at a user-specified significance level <code>alpha</code>.</p>
(AU-ROC) and a prevalence shift are computed for the features found to be
associated with the two different classes at a user-specified
significance level <code>alpha</code>.</p>
<p>Finally, the function produces a plot of the top <code>max.show</code> associated
features, showing the distribution of the log10-transformed abundances for
both classes, the median fold change, and the AU-ROC.</p>
both classes, and user-selected panels for the effect (AU-ROC, Prevalence
Shift, and Fold Change)</p>
<pre class="usage"><span class='fu'>check.associations</span>(<span class='no'>feat</span>, <span class='no'>label</span>, <span class='no'>fn.plot</span>, <span class='kw'>color.scheme</span> <span class='kw'>=</span> <span class='st'>"RdYlBu"</span>,
<span class='kw'>alpha</span> <span class='kw'>=</span> <span class='fl'>0.05</span>, <span class='kw'>mult.corr</span> <span class='kw'>=</span> <span class='st'>"fdr"</span>, <span class='kw'>sort.by</span> <span class='kw'>=</span> <span class='st'>"fc"</span>, <span class='kw'>detect.lim</span> <span class='kw'>=</span> <span class='fl'>10</span>^-<span class='fl'>8</span>,
<span class='kw'>pr.cutoff</span> <span class='kw'>=</span> <span class='fl'>10</span>^-<span class='fl'>6</span>, <span class='kw'>max.show</span> <span class='kw'>=</span> <span class='fl'>50</span>, <span class='kw'>plot.type</span> <span class='kw'>=</span> <span class='st'>"bean"</span>, <span class='kw'>panels</span> <span class='kw'>=</span> <span class='fu'>c</span>(<span class='st'>"fc"</span>,
<span class='st'>"auroc"</span>))</pre>
<span class='kw'>pr.cutoff</span> <span class='kw'>=</span> <span class='fl'>10</span>^-<span class='fl'>6</span>, <span class='kw'>max.show</span> <span class='kw'>=</span> <span class='fl'>50</span>, <span class='kw'>plot.type</span> <span class='kw'>=</span> <span class='st'>"quantile.box"</span>,
<span class='kw'>panels</span> <span class='kw'>=</span> <span class='fu'>c</span>(<span class='st'>"fc"</span>, <span class='st'>"auroc"</span>))</pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a> Arguments</h2>
<table class="ref-arguments">
......@@ -131,13 +146,21 @@ both classes, the median fold change, and the AU-ROC.</p>
<th>detect.lim</th>
<td><p>float, pseudocount to be added before log-transormation of the data, defaults to <code>1e-08</code></p></td>
</tr>
<tr>
<th>pr.cutoff</th>
<td><p>float, cutoff for the prevalence computation, defaults to <code>1e-06</code></p></td>
</tr>
<tr>
<th>max.show</th>
<td><p>integer, how many associated features should be shown, defaults to <code>50</code></p></td>
</tr>
<tr>
<th>plot.type</th>
<td><p>string, specify how the abundance should be plotted, must be one of these: <code>c("bean", "box", "quantile.box", "quantile.rect")</code>, defaults to <code>"bean"</code></p></td>
<td><p>string, specify how the abundance should be plotted, must be one of these: <code>c("bean", "box", "quantile.box", "quantile.rect")</code>, defaults to <code>"quantile.box"</code></p></td>
</tr>
<tr>
<th>panels</th>
<td><p>vector, name of the panels to be plotted next to the log10-transformed abundances, possible entries are <code>c("fc", "auroc", "prevalence")</code>, defaults to <code>c("fc", "auroc")</code></p></td>
</tr>
</table>
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