differentialabundance

Alternative to matrix: a compressed CEL files archive such as often found in GEO

(RNA-seq only): optional transcript/gene length matrix with samples and transcript_ids/gene_ids as in the abundance matrix.

TSV/CSV-format abundance matrix

Use SOFT files from GEO by providing the GSE study identifier

A text file listing technical features (e.g. spikes)

Supply your own feature annotations. Can be derived from the GTF (rnaseq) or from the Bioconductor annotation package (affy arrays).

Feature ID attribute in the abundance table as well as in the GTF file (e.g. the gene_id field)

Comma-separated string, specifies feature metadata columns to be used for exploratory analysis, platform-specific

Feature name attribute in the abundance table as well as in the GTF file (e.g. the gene symbol field)

Type of feature. Often 'gene'

When set, use the control features in scaling/ normalization (currently only supported for differential_method deseq2)

A CSV/TSV/YML/YAML file describing sample contrasts to compare groups.

Path to CSV/TSV file containing information about the samples in the experiment.

The output directory where the results will be saved. You have to use absolute paths to storage on Cloud infrastructure.

To how many digits should numeric output in different modules be rounded? If -1 or null, will not round.

Global seed for stochastic methods

A string identifier used to name result files in the output directory

Input data format category used for input validation and routing (not for selecting analysis methods).

Column in the sample sheet to be used as the primary sample identifier

Column in the sample sheet to be used as identifier for observations. If unset, the --observations_id_col is used.

Type of observation

Name of the paramset to run. In profile mode, set by the analysis profile for output directory naming. In paramsheet mode, selects which paramset(s) to run (comma-separated).

Path to a paramsheet YAML file. Setting this activates multi-run (paramsheet) mode where paramsheet values take priority over CLI flags.

alpha parameter passed to results()

altHypothesis parameter passed to results()

fitType parameter passed to DESeq()

independentFiltering parameter passed to results()

lfcThreshold parameter passed to results()

'minReplicatesForReplace' parameter passed to DESeq()

minmu parameter passed to results()

pAdjustMethod parameter passed to results()

sfType parameter passed to DESeq()

Shrink fold changes in results?

test parameter passed to DESeq()

useT parameter passed to DESeq2

blind parameter for rlog() and/ or vst()

variance stabilisation method to use when making a variance stabilised matrix

nsub parameter passed to vst()

The feature identifier column in differential results tables

Advanced option: the suffix associated tabular differential results tables. Will by default use the appropriate suffix according to the study_type.

Maximum p value used to calculate differential feature numbers

Maximum q value used to calculate differential feature numbers

Differential analysis method

Minimum fold change used to calculate differential feature numbers. Note that this number will be log2 transformed

Valid R palette name

In differential analysis (DEseq2 or Limma), subset to the contrast samples before modelling variance?

Method used to adjust p-values for multiple testing (passed to p.adjust).

Turns on and off usage of voomWithDreamWeights() normalization in the DREAM module.

passed to variancePartition::dream(), logical, should 95% confidence intervals be output for logFC? Alternatively, can take a numeric value between zero and one specifying the confidence level required.

Method used to estimate effective degrees of freedom for hypothesis testing in the linear mixed model. Allowed values: adaptive (default), Satterthwaite, Kenward-Roger.

passed to variancePartition::dream() (via eBayes), assumed proportion of genes that are differentially expressed (numeric 0-1).

passed to variancePartition::dream(), logical, use REML estimation for mixed-model variance components (passed through to lmer()).

passed to variancePartition::dream() (via eBayes), logical, should the estimation of df.prior and var.prior be robustified against outlier sample variances?

passed to variancePartition::dream() (via eBayes), comma-separated numeric pair giving the lower and upper limits of the standard deviation of the logFC values used in the prior.

passed to variancePartition::dream() (via eBayes), logical, should an intensity-dependent trend be allowed for the prior variance?

passed to variancePartition::dream() (via eBayes), comma-separated numeric pair giving the proportion of the lower and upper tails to be winsorized before estimating the standard deviation.

passed to topTable(), method used to adjust the p-values for multiple testing.

Sample sheet column to be used to derive a vector or factor specifying a blocking variable on the arrays for limma::lmFit(); however, for random effects models, DREAM is the recommended approach in this pipeline

passed to topTable(), logical, should confidence 95% intervals be output for logFC? Alternatively, can take a numeric value between zero and one specifying the confidence level required.

passed to limma::lmFit(), the inter-duplicate or inter-technical replicate correlation; however for random effects models, DREAM is the recommended approach in this pipeline

passed to topTable(), minimum absolute log2-fold-change required

passed to lmFit(), the fitting method

passed to lmFit(), positive integer giving the number of times each distinct probe is printed on each array.

cutoff value for adjusted p-values. Only genes with lower p-values are listed.

passed to eBayes(), a numeric value between 0 and 1, assumed proportion of genes which are differentially expressed

passed to eBayes(), logical, should the estimation of df.prior and var.prior be robustified against outlier sample variances?

passed to lmFit(), positive integer giving the spacing between duplicate occurrences of the same probe, spacing=1 for consecutive rows.

passed to eBayes, comma separated string of two values, assumed lower and upper limits for the standard deviation of log2-fold-changes for differentially expressed genes

passed to eBayes(), logical, should an intensity-dependent trend be allowed for the prior variance?

Turns on and off usage of voom normalization in the Limma module.

passed to eBayes, comma separated string of length 1 or 2, giving left and right tail proportions of x to Winsorize. Used only when robust=TRUE.

Alpha value for the Box-Cox transformation used by propd. Leave unset to skip the transformation.

False discovery rate threshold used to define significantly proportional pairs.

Use moderated theta values in propd.

Number of theta cutoffs evaluated when estimating FDR by permutation.

Number of permutations for FDR estimation. 0 uses the analytical FDR from F-statistic p-values.

Save the gene-by-gene adjacency matrix. Must be set to true when pairing propd with --functional_method grea, which consumes the adjacency.

Save the table of significant pairwise statistics.

Save the full table of pairwise statistics (very large).

Save the propd object as an RDS file.

Clustering method used in dendrogram creation

Correlation method used in dendrogram creation

Of which assays to compute the log2 during exploratory analysis. Not necessary for maxquant data as this is controlled by the pipeline.

Threshold on MAD score for outlier identification

How should the main grouping variable be selected? 'auto_pca', 'contrasts', or a valid column name from the observations table.

Number of features selected before certain exploratory analyses. If -1, will use all features.

Valid R palette name

Length of the whiskers in boxplots as multiple of IQR. Defaults to 1.5.

Comma-separated list of methods to use (e.g., 'ora,ulm')

Removes sources of a net with less than min_n targets

Path to TSV file containing network file for decoupler

Functional analysis method. Set to 'none' (default) to disable functional analysis.

Gene sets in GMT or GMX-format; for GSEA: multiple comma-separated input files in either format are possible. For gprofiler2: A single file in GMT format is possible; this has lowest priority and will be overridden by --gprofiler2_token and --gprofiler2_organism.

Which column to use as gene IDs in the background matrix.

Path to CSV/TSV/TXT file that should be used as a background list of genes for the query; alternatively, 'auto' (default) or 'false'.

The method that should be used for multiple testing correction.

How to calculate the statistical domain size.

Whether to include evcodes in the results.

Maximum q value used for significance testing.

Should underrepresentation be measured instead of overrepresentation?

How many genes must be differentially expressed in a pathway for it to be considered enriched? Default 1.

Short name of the organism that is analyzed, e.g. hsapiens for homo sapiens.

Valid R palette name

Should only significant enrichment results be considered?

On which source databases to run the gprofiler query

Token that should be used as a query.

Number of permutations used by grea to estimate enrichment significance.

Maximum number of features in a gene set.

Minimum number of features in a gene set.

Make detailed geneset report?

Use median for class metrics

Metric for ranking genes

Normalisation mode

Number of permutations

Number of markers

Gene list ordering mode

Permutation type

Plot graphs for the top sets of each phenotype

Randomization mode

Save random ranked lists

Enrichment statistic

Max size: exclude larger sets

Min size: exclude smaller sets

Gene list sorting mode

Make a zipped file with all reports

Email address for completion summary, only when pipeline fails.

Display the help message.

Display the full detailed help message.

Method used to save pipeline results to output directory.

Display hidden parameters in the help message (only works when --help or --help_full are provided).

Boolean whether to validate parameters against the schema at runtime

logical value. If set to true, apply background correction using RMA.

integer value indicating which RMA background to use

logical value. If TRUE, a matrix of probe annotations will be derived.

Used to specify the name of an alternative cdf package. If set to NULL, then the usual cdf package based on Affymetrix' mappings will be used.

logical value. If TRUE, then works on the PM matrix in place as much as possible, good for large datasets.

Column of the sample sheet containing the Affymetrix CEL file name

if TRUE, then overrides what is in rm.mask and rm.oultiers.

should the spots marked as 'MASKS' set to NA?

should the spots marked as 'OUTLIERS' set to NA?

An optional grouping variable to be used to calculate a min_samples value

Minimum abundance value. Set to false to disable abundance filtering.

A minimum proportion of observations, given as a number between 0 and 1, that must pass the threshold. Overrides minimum_samples

A minimum proportion of observations, given as a number between 0 and 1, that must have a value (not NA) to retain the row/ feature (e.g. gene).

Minimum observations that must pass the threshold to retain the row/ feature (e.g. gene).

Minimum observations that must have a value (not NA) to retain the row/ feature (e.g. gene). Overrides filtering_min_proportion_not_na.

If a GTF file is supplied, which feature type to use

If a GTF file is supplied, which field should go first in the converted output table

Genome annotation file in GTF format

Prefix of the column names of the MaxQuant proteingroups table in which the intensity values are saved; the prefix has to be followed by the sample names that are also found in the samplesheet. Default: 'LFQ intensity'; will search for both the prefix as entered and the prefix followed by one whitespace.

Normalization function to use on the MaxQuant intensities.

Valid R palette name

Should a loess line be added to the plot of mean-variance relationship of the conditions? Default: true.

Which method to use for plotting sample distributions of the MaxQuant intensities; one of 'violin', 'dist', 'box'.

Name of iGenomes reference.

A markdown file containing citations to include in the final report

Email address for completion summary.

An author for reporting outputs

Semicolon-separated string of contributor info that should be listed in the report.

A description for reporting outputs

Qmd/Rmd/ipynb report template(s) from which to create the pipeline report. Supply a single path or a comma-separated list of paths to render multiple reports per paramset.

A title for reporting outputs

Skip generation of reports

Should a Shiny app be built?

Should the app be deployed to shinyapps.io?

Your shinyapps.io account name

The name of the app to push to in your shinyapps.io account