nf-core/differentialabundance
Differential abundance analysis for feature/ observation matrices from platforms such as RNA-seq
1.3.0
). The latest
stable release is
1.5.0
.
Define where the pipeline should find input data and save output data.
A string to identify results in the output directory
string
study
A string identifying the technology used to produce the data
string
Path to comma-separated file containing information about the samples in the experiment.
string
^\S+\.(csv|tsv|txt)$
A CSV file describing sample contrasts
string
^\S+\.(csv|tsv|txt)$
The output directory where the results will be saved. You have to use absolute paths to storage on Cloud infrastructure.
string
Type of abundance measure used, platform-dependent
string
counts
Ways of providing your abundance values
TSV-format abundance matrix
string
^\S+\.(tsv|csv|txt)$
Alternative to matrix: a compressed CEL files archive such as often found in GEO
string
None
Use SOFT files from GEO by providing the GSE study identifier
string
None
Column in the samples sheet to be used as the primary sample identifier
string
sample
Type of observation
string
sample
Column in the sample sheet to be used as the display identifier for observations
string
sample
Options related to features
Feature ID attribute in the GTF file (e.g. the gene_id field)
string
gene_id
Feature name attribute in the GTF file (e.g. the gene symbol field)
string
gene_name
Type of feature we have, often ‘gene’
string
gene
When set, use the control features in scaling/ normalisation
boolean
A text file listing technical features (e.g. spikes)
string
Comma-separated string, specifies feature metadata columns to be used for exploratory analysis, platform-specific
string
gene_id,gene_name,gene_biotype
This parameter allows you to supply your own feature annotations. These can often be automatically derived from the GTF used upstream for RNA-seq, or from the Bioconductor annotation package (for affy arrays).
string
^\S+\.(csv|tsv|txt)$
Where a GTF file is supplied, which feature type to use
string
transcript
Where a GTF file is supplied, which field should go first in the converted output table
string
gene_id
Of which assays to compute the log2. Not necessary for maxquant data as this is controlled by the pipeline.
string
Options for processing of affy arrays with justRMA()
Column of the sample sheet containing the Affymetrix CEL file name
string
file
logical value. If TRUE, then background correct using RMA background correction.
boolean
true
integer value indicating which RMA background to use
integer
2
logical value. If TRUE, then works on the PM matrix in place as much as possible, good for large datasets.
boolean
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.
string
None
logical value. If TRUE, a matrix of probe annotations will be derived.
boolean
true
should the spots marked as ‘MASKS’ set to NA?
boolean
should the spots marked as ‘OUTLIERS’ set to NA?
boolean
if TRUE, then overrides what is in rm.mask and rm.oultiers.
boolean
Options for processing of proteomics MaxQuant tables with the Proteus R package
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 ’; take care to also consider trailing whitespace between prefix and samplenames.
string
LFQ intensity
Normalization function to use on the MaxQuant intensities.
string
Which method to use for plotting sample distributions of the MaxQuant intensities; one of ‘violin’, ‘dist’, ‘box’.
string
Should a loess line be added to the plot of mean-variance relationship of the conditions? Default: true.
boolean
true
Valid R palette name
string
Set1
Number of decimals to round the MaxQuant intensities to; default: -1 (will not round).
number
-1
Options related to filtering upstream of differential analysis
Minimum abundance value
number
1
Minimum observations that must pass the threshold to retain the row/ feature (e.g. gene).
number
1
A minimum proportion of observations, given as a number between 0 and 1, that must pass the threshold. Overrides minimum_samples
number
An optional grouping variable to be used to calculate a min_samples value
string
Options related to data exploration
Clustering method used in dendrogram creation
string
ward.D2
Correlation method used in dendrogram creation
string
spearman
Number of features selected before certain exploratory analyses
integer
500
Length of the whiskers in boxplots as multiple of IQR. Defaults to 1.5.
number
1.5
Threshold on MAD score for outlier identification
integer
-5
How should the main grouping variable be selected? ‘auto_pca’, ‘contrasts’, or a valid column name from the observations table.
string
auto_pca
Specifies assay names to be used for matrices, platform-specific
string
raw,normalised,variance_stabilised
Specifies final assay to be used for exploratory analysis, platform-specific
string
variance_stabilised
Valid R palette name
string
Set1
Options related to differential operations
The suffix associated tabular differential results tables
string
.deseq2.results.tsv
The feature identifier column in differential results tables
string
gene_id
The fold change column in differential results tables
string
log2FoldChange
The p value column in differential results tables
string
pvalue
The q value column in differential results tables.
string
padj
Minimum fold change used to calculate differential feature numbers
number
2
Maximum p value used to calculate differential feature numbers
number
1
Maximum q value used to calculate differential feature numbers
number
0.05
Where a features file (GTF) has been provided, what attributed to use to name features
string
gene_name
Indicate whether or not fold changes are on the log scale (default is to assume they are)
boolean
true
Valid R palette name
string
Set1
In differential analysis (DEseq2 or Limma), subset to the contrast samples before modelling variance?
boolean
test
parameter passed to DESeq()
string
fitType
parameter passed to DESeq()
string
sfType
parameter passed to DESeq()
string
‘minReplicatesForReplace’ parameter passed to DESeq()
integer
7
useT
parameter passed to DESeq2
boolean
independentFiltering
parameter passed to results()
boolean
true
lfcThreshold
parameter passed to results()
integer
altHypothesis
parameter passed to results()
string
greaterAbs
pAdjustMethod
parameter passed to results()
string
BH
alpha
parameter passed to results()
number
0.1
minmu
parameter passed to results()
number
0.5
variance stabilisation method to use when making a variance stabilised matrix
string
Shink fold changes in results?
boolean
true
Number of cores
integer
1
blind
parameter for rlog() and/ or vst()
boolean
true
nsub
parameter passed to vst()
integer
1000
passed to lmFit(), positive integer giving the number of times each distinct probe is printed on each array.
number
passed to lmFit(), positive integer giving the spacing between duplicate occurrences of the same probe, spacing=1 for consecutive rows.
string
None
Sample sheet column to be used to derive a vector or factor specifying a blocking variable on the arrays
string
None
passed to lmFit(), the inter-duplicate or inter-technical replicate correlation
string
None
passed to lmFit(), the fitting method
string
passed to eBayes(), a numeric value between 0 and 1, assumed proportion of genes which are differentially expressed
number
0.01
passed to eBayes(), logical, should an intensity-dependent trend be allowed for the prior variance?
boolean
passed to eBayes(), logical, should the estimation of df.prior and var.prior be robustified against outlier sample variances?
boolean
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
string
0.1,4
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.
string
0.05,0.1
passed to topTable(), minimum absolute log2-fold-change required
integer
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.
boolean
passed to topTable(), method used to adjust the p-values for multiple testing.
string
cutoff value for adjusted p-values. Only genes with lower p-values are listed.
number
1
Set to run GSEA to infer differential gene sets in contrasts
boolean
Permutation type
string
Number of permutations
integer
1000
Enrichment statistic
string
Metric for ranking genes
string
Gene list sorting mode
string
Gene list ordering mode
string
Max size: exclude larger sets
integer
500
Min size: exclude smaller sets
integer
15
Normalisation mode
string
Randomization mode
string
Make detailed geneset report?
boolean
true
Use median for class metrics
boolean
Number of markers
integer
100
Plot graphs for the top sets of each phenotype
integer
20
Seed for permutation
string
timestamp
Save random ranked lists
boolean
Make a zipped file with all reports
boolean
Gene sets in GMT or GMX-format (multiple comma-separated input files are possible)
string
None
Should a Shiny app be built?
boolean
true
Should the app be deployed to shinyapps.io?
boolean
Your shinyapps.io account name
string
None
The name of the app to push to in your shinyapps.io account
string
None
Should we guess the log status of matrices and unlog for the app?
boolean
true
Rmd report template from which to create the pipeline report
string
^\S+\.Rmd$
Email address for completion summary.
string
^([a-zA-Z0-9_\-\.]+)@([a-zA-Z0-9_\-\.]+)\.([a-zA-Z]{2,5})$
A logo to display in the report instead of the generic pipeline logo
string
docs/images/nf-core-differentialabundance_logo_light.png
CSS to use to style the output, in lieu of the default nf-core styling
string
assets/nf-core_style.css
A markdown file containing citations to include in the fiinal report
string
CITATIONS.md
A title for reporting outputs
string
None
An author for reporting outputs
string
None
A description for reporting outputs
string
None
Reference genome related files and options required for the workflow.
Name of iGenomes reference.
string
Genome annotation file in GTF format
string
^\S+\.gtf(\.gz)?
Do not load the iGenomes reference config.
boolean
Parameters used to describe centralised config profiles. These should not be edited.
Git commit id for Institutional configs.
string
master
Base directory for Institutional configs.
string
https://raw.githubusercontent.com/nf-core/configs/master
Institutional config name.
string
Institutional config description.
string
Institutional config contact information.
string
Institutional config URL link.
string
Set the top limit for requested resources for any single job.
Maximum number of CPUs that can be requested for any single job.
integer
16
Maximum amount of memory that can be requested for any single job.
string
128.GB
^\d+(\.\d+)?\.?\s*(K|M|G|T)?B$
Maximum amount of time that can be requested for any single job.
string
240.h
^(\d+\.?\s*(s|m|h|d|day)\s*)+$
Less common options for the pipeline, typically set in a config file.
Display help text.
boolean
Display version and exit.
boolean
Method used to save pipeline results to output directory.
string
Email address for completion summary, only when pipeline fails.
string
^([a-zA-Z0-9_\-\.]+)@([a-zA-Z0-9_\-\.]+)\.([a-zA-Z]{2,5})$
Send plain-text email instead of HTML.
boolean
Do not use coloured log outputs.
boolean
Incoming hook URL for messaging service
string
Boolean whether to validate parameters against the schema at runtime
boolean
true
Show all params when using --help
boolean
Validation of parameters fails when an unrecognised parameter is found.
boolean
Validation of parameters in lenient more.
boolean