RnaChipIntegrator: analyse ‘genes’ with ‘peak’ data
RnaChipIntegrator is a Python bioinformatics utility that performs
integrated analyses of ‘gene’ data (a set of genes or genomic features,
for example gene expression data or canonical gene lists) with ‘peak’ data
(a set of regions, for example ChIP peaks) to identify the nearest
genes or features to each peak, and vice versa.
- What it does
- Getting started
- Usage
- Simple usage
- Specifying distance cutoff (
--cutoff) - Specifying how distances are measured between peaks and genes (
--edge) - Only using differentially expressed genes (
--only-DE) - Limiting the number of results to report (
--number) - Specifying the promoter region (
--promoter_region) - Running either peak-centric or gene-centric analysis only (
--analyses) - Specifying multiple distance cutoffs (
--cutoffs) - Specifying multiple peaks and/or genes files (
--peaksand--genes) - Specifying multiple cores in batch modes (
--nprocessors) - Changing the output files and formats
- Using RnaChipIntegrator in Galaxy
- Input files
- Output files
- Overview
- Genes associated with each peak (‘peak-centric’ output)
- Peaks associated with each gene (‘gene-centric’ output)
- Summary files (
--summary) - Excel spreadsheet (
--xlsx) - Compact output format (
--compact) - Output padding (
--pad) - Specifying feature type other than ‘gene’ etc (
--feature) - Specifying an ID for input peaks (
--peak_id) - Writing results to separate files in batch mode (
--split-outputs) - Additional fields for batch operation
- Interpreting ‘upstream’ and ‘downstream’
- Known problems
- Citing RnaChipIntegrator
- Additional information