corto: a lightweight R package for gene network inference and master regulator analysis
| Autor: | Gonzalo Lopez-Garcia, Daniele Mercatelli, Federico M. Giorgi |
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| Přispěvatelé: | Mercatelli, Daniele, Lopez-Garcia, Gonzalo, Giorgi, Federico M |
| Rok vydání: | 2020 |
| Předmět: |
Statistics and Probability
Bioinformatics Computer science 030303 biophysics Gene regulatory network Inference Computational biology computer.software_genre Biochemistry 03 medical and health sciences Computer cluster Neoplasms Gene expression Humans Gene Regulatory Networks Copy-number variation Molecular Biology 030304 developmental biology 0303 health sciences Master regulator Computer Science Applications Human tumor Computational Mathematics R package ComputingMethodologies_PATTERNRECOGNITION Computational Theory and Mathematics Data mining Transcriptome computer Software |
| Zdroj: | Bioinformatics (Oxford, England). 36(12) |
| ISSN: | 1367-4811 |
| Popis: | 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 |
| Databáze: | OpenAIRE |
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