workflows/differential_expression/pseudobulk_deseq2

Description

Performs pseudobulk generation and subsequent differential expression analysis using DESeq2.

Inputs

Name	Type & Properties	Description
--input	file required	Input h5mu file.
--modality	string	Which modality from the input MuData file to process.
--input_layer	string	Input layer to use. If None, X is used. This layer must contain raw counts.
--obs_cell_group	string required	.obs field containing the variable to group on. Typically this field contains cell groups such as annotated cell types or clusters. If provided, will generate DESeq2 analysis per cell group.
--obs_groups	string multiple	.obs fields containing the experimental condition(s) to create pseudobulk samples for.
--var_gene_names	string	Name of the .var field that contains gene symbols. If not provided, .var.index will be used.

Name

Type & Properties

--input

file

required

--modality

string

--input_layer

string

--obs_cell_group

string

required

--obs_groups

string

multiple

--var_gene_names

string

Pseudobulk Options

Name	Type & Properties	Description
--aggregation_method	string	Method to aggregate the raw counts for pseudoreplicates. Either sum or mean.
--random_state	integer	The random seed for sampling.

Name

Type & Properties

--aggregation_method

string

--random_state

integer

Filtering options

Name	Type & Properties	Description
--min_obs_per_sample	integer	Minimum number of observations per pseudobulk sample.
--filter_genes_min_samples	integer	Minimum number of samples a gene must be expressed in to be included in the analysis. If None, no filtering is applied.
--filter_gene_patterns	string multiple	List of regex patterns to filter out genes. Genes matching any of these patterns will be excluded from the analysis.

Name

Type & Properties

--min_obs_per_sample

integer

--filter_genes_min_samples

integer

--filter_gene_patterns

string

multiple

DGEA options

Name	Type & Properties	Description
--design_formula	string required	Design formula for DESeq2 analysis in R-style format. Specifies the statistical model to account for various factors.
--contrast_column	string required	Column in the metadata to use for the contrast. This column should contain the conditions to compare.
--contrast_values	string required multiple	Values to compare in the contrast column. First value is baseline, following values are different treatments.
--p_adj_threshold	double	Adjusted p-value threshold for significance. Genes with adjusted p-values below this threshold will be considered significant.
--log2fc_threshold	double	Log2 fold change threshold for significance. Genes with absolute log2 fold change above this threshold will be considered significant.

Name

Type & Properties

--design_formula

string

required

--contrast_column

string

required

--contrast_values

string

required

multiple

--p_adj_threshold

double

--log2fc_threshold

double

Outputs

Name	Type & Properties	Description
--output -o	file required output	Output directory for DESeq2 results, containing one CSV file per cell group (as defined by `--obs_cell_group`)
--output_prefix	string	Prefix for output CSV files: files will be named "{prefix}_{cell_group}.csv"

Name

Type & Properties

--output

-o

file

required

output

--output_prefix

string

Run this component

Run the following command to execute this component with Nextflow:

cat > params.yaml <<'EOM'  
modality: [ "rna" ]  
aggregation_method: [ "sum" ]  
random_state: [ 0 ]  
min_obs_per_sample: [ 30 ]  
p_adj_threshold: [ 0.05 ]  
log2fc_threshold: [ 0 ]  
output: "$id.$key.output"  
output_prefix: [ "deseq2_analysis" ]  
id: "run"  
publish_dir: "output/"  
EOM

nextflow run https://packages.viash-hub.com/vsh/openpipeline.git \  
  -revision v4.2.0 \  
  -main-script target/nextflow/workflows/differential_expression/pseudobulk_deseq2/main.nf \  
  -params-file params.yaml

workflows/differential_expression/pseudobulk_deseq2

Inputs

Pseudobulk Options

Filtering options

DGEA options

Outputs

Run this component

Relationships

Used by

Uses