BioinformaticsBioinformaticsPeer-reviewed journal article
corto: a lightweight R package for Gene NetworkInference and Master Regulator Analysis
Daniele MercatelliiD, Gonzalo LópeziD, Federico Manuel GiorgiiD
Abstract
MotivationGene Network Inference and Master Regulator Analysis (MRA) have been widely adopted to define specific transcriptional perturbations from gene expression signatures. Several tools exist to perform such analyses, but most require a computer cluster or large amounts of RAM to be executed. ResultsWe developed corto, a fast and lightweight R package to infer gene networks and perform MRA from gene expression data, with optional corrections for Copy Number Variations (CNVs) and able to run on signatures generated from RNA-Seq or ATAC-Seq data. We extensively benchmarked it to infer context-specific gene networks in 39 human tumor and 27 normal tissue datasets. AvailabilityCross-platform and multi-threaded R package on CRAN (stable version) https://cran.rproject.org/package=corto and Github (development release) https://github.com/federicogiorgi/corto. Contactfederico.giorgi@unibo.it
- organism: human
- assay: bulk RNA-seq
- assay: ATAC-seq
- research focus: gene regulatory network inference
- research focus: benchmarking
- approach: statistical model
- Citations
- 77
- FWCI
- 2.92
- Field percentile
- top 7%
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