| Added by | pcoopman |
|---|---|
| Group name | EquipePC |
| Item Type | Journal Article |
| Title | ifCNV: A novel isolation-forest-based package to detect copy-number variations from various targeted NGS datasets |
| Creator | Cabello-Aguilar et al. |
| Author | Simon Cabello-Aguilar |
| Author | Julie A. Vendrell |
| Author | Charles Van Goethem |
| Author | Mehdi Brousse |
| Author | Catherine Gozé |
| Author | Laurent Frantz |
| Author | Jérôme Solassol |
| Abstract | Copy-number variations (CNVs) are an essential component of genetic variation distributed across large parts of the human genome. CNV detection from next-generation sequencing data and artificial intelligence algorithms have progressed in recent years. However, only a few tools have taken advantage of machine-learning algorithms for CNV detection, and none propose using artificial intelligence to automatically detect probable CNV-positive samples. The most developed approach is to use a reference or normal dataset to compare with the samples of interest, and it is well known that selecting appropriate normal samples represents a challenging task that dramatically influences the precision of results in all CNV-detecting tools. With careful consideration of these issues, we propose here ifCNV, a new software based on isolation forests that creates its own reference, available in R and python with customizable parameters. ifCNV combines artificial intelligence using two isolation forests and a comprehensive scoring method to faithfully detect CNVs among various samples. It was validated using targeted next-generation sequencing (NGS) datasets from diverse origins (capture and amplicon, germline and somatic), and it exhibits high sensitivity, specificity, and accuracy. ifCNV is a publicly available open-source software (https://github.com/SimCab-CHU/ifCNV) that allows the detection of CNVs in many clinical situations. |
| Publication | Molecular Therapy. Nucleic Acids |
| Volume | 30 |
| Pages | 174-183 |
| Date | 2022-12-13 |
| Journal Abbr | Mol Ther Nucleic Acids |
| Language | eng |
| DOI | 10.1016/j.omtn.2022.09.009 |
| ISSN | 2162-2531 |
| Short Title | ifCNV |
| Library Catalog | PubMed |
| Extra | PMID: 36250203 PMCID: PMC9547229 |
| Tags | clinic, CNV detection, first-last-corresponding, localization scoring, machine learning, MT: Bioinformatics, Python open-source package, R open-source package |
| Date Added | 2023/11/15 - 12:51:14 |
| Date Modified | 2023/11/15 - 12:57:34 |
| Notes and Attachments | PubMed entry (Attachment) Texte intégral (Attachment) |
Institut de Recherche en Cancérologie de
