Nextflow Modules
Showing module(s) with keyword "rna-seq"
| Module | Kind | Keywords | Description |
|---|---|---|---|
| nf-core/bam_stringtie_merge | Workflow | rna-seq transcript-assembly transcript-merge stringtie gtf | Assemble transcripts from sorted BAM alignments using StringTie, then merge per-sample transcript GTFs into a unified annotation. |
| nf-core/deseq2/differential | Process | differential expression rna-seq deseq2 | runs a differential expression analysis with DESeq2 |
| nf-core/dexseq/dtu | Process | dexseq transcript differential transcript usage alternative splicing rna-seq | Test a contrast for differential transcript usage with DEXSeq, from a table of transcript counts |
| nf-core/dexseq/exon | Process | dexseq exon differential exon usage alternative splicing rna-seq | Test a contrast for differential exon usage with DEXSeq, from the exon counts of dexseq/count |
| nf-core/disambiguate | Process | disambiguation xenograft explant rna-seq alignment bam | Disambiguates reads aligned to two different organisms (e.g. human and mouse) from the same source of FASTQ files. Useful in explant RNA/DNA-Seq workflows where reads from two species are present. For reads aligned to both organisms, the algorithm compares alignment quality scores to determine the most likely species of origin. Produces four BAM files (uniquely assigned to species A or B, ambiguous for species A or B) and a summary file. |
| nf-core/edger/differential | Process | differential expression rna-seq counts edger | Runs a differential expression analysis on count data with edgeR. Options are passed via `ext.args` as `--option value` pairs: `gene_id_col` (default `gene_id`), `sample_id_col` (`experiment_accession`), `blocking_variables` (`;`-separated sample sheet columns, not combinable with a formula), `subset_to_contrast_samples` (`FALSE`, needs a contrast variable), `exclude_samples_col` and `exclude_samples_values` (`;`-separated), `filter_by_expr` (`FALSE`), `min_count` (`10`), `norm_method` (`TMM`), `test_method` (`qlf` for glmQLFit/glmQLFTest or `lrt` for glmFit/glmLRT), `robust` (`TRUE`), `prior_count` (`2`), `adjust_method` (`BH`) and `round_digits` (no rounding). Defaults that differ from edgeR's own: `robust` is `TRUE` for both `estimateDisp` and `glmQLFit` (edgeR default `FALSE`), and `filterByExpr` is off by default because pipelines usually filter upstream; when enabled, `min_count` is passed as `min.count`. Sample sheet column names, including those used in a formula, are converted with `make.names()`. |
| nf-core/seq2hla | Process | hla typing rna-seq genomics immunogenetics | Precision HLA typing and expression from RNA-seq data using seq2HLA |
| nf-core/shinyngs/app | Process | differential expression rna-seq deseq2 | build and deploy Shiny apps for interactively mining differential abundance data |
| nf-core/slamdunk/all | Process | slamseq rna-seq mapping snp quantification | Complete SLAMseq analysis pipeline including read mapping, filtering, SNP calling, and quantification |
| nf-core/slamdunk/map | Process | slamseq rna-seq mapping | Slamdunk read mapping using NextGenMap’s SLAMSeq alignment settings. |