ArticleBriefings in bioinformatics2021
iWhale: a computational pipeline based on Docker and SCons for detection and annotation of somatic variants in cancer WES data.
Article in Briefings in bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- hDNApipe: streamlining human genome analysis and interpretation with an intuitive and user-friendly interface.NAR genomics and bioinformatics · 2025Article
- Variant Impact Predictor database (VIPdb), version 2: Trends from 25 years of genetic variant impact predictors.bioRxiv : the preprint server for biology · 2024Article
- Var∣Decrypt: a novel and user-friendly tool to explore and prioritize variants in whole-exome sequencing data.Epigenetics & chromatin · 2023Article
- Clinical significance of circulating tumor cells and cell-free DNA in pediatric rhabdomyosarcoma.Molecular oncology · 2022Article
- A Novel Ferroptosis-Related LncRNA Pair Prognostic Signature Predicts Immune Landscapes and Treatment Responses for Gastric Cancer Patients.Frontiers in genetics · 2022Article
- Comprehensive analysis of the prognostic value and immune implications of the TTK gene in lung adenocarcinoma: a meta-analysis and bioinformatics analysis.Animal cells and systems · 2022Article
- DIVIS: Integrated and Customizable Pipeline for Cancer Genome Sequencing Analysis and Interpretation.Frontiers in oncology · 2021Article
- A high definition picture of somatic mutations in chronic lymphoproliferative disorder of natural killer cells.Blood cancer journal · 2020Article
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Authors and funding
4 authors.
Funding
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Abstract
Whole exome sequencing (WES) is a powerful approach for discovering sequence variants in cancer cells but its time effectiveness is limited by the complexity and issues of WES data analysis. Here we present iWhale, a customizable pipeline based on Docker and SCons, reliably detecting somatic variants by three complementary callers (MuTect2, Strelka2 and VarScan2). The results are combined to obtain a single variant call format file for each sample and variants are annotated by integrating a wide range of information extracted from several reference databases, ultimately allowing variant and gene prioritization according to different criteria. iWhale allows users to conduct a complex series of WES analyses with a powerful yet customizable and easy-to-use tool, running on most operating systems (macOs, GNU/Linux and Windows). iWhale code is freely available at https://github.com/alexcoppe/iWhale and the docker image is downloadable from https://hub.docker.com/r/alexcoppe/iwhale.
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