PipeIT: A Singularity Container for Molecular Diagnostic Somatic Variant Calling on the Ion Torrent Next-Generation Sequencing Platform.

Garofoli, Andrea; Paradiso, Viola; Montazeri, Hesam; Jermann, Philip M; Roma, Guglielmo; Tornillo, Luigi; Terracciano, Luigi M; Piscuoglio, Salvatore; Ng, Kiu Yan Charlotte (2019). PipeIT: A Singularity Container for Molecular Diagnostic Somatic Variant Calling on the Ion Torrent Next-Generation Sequencing Platform. The journal of molecular diagnostics, 21(5), pp. 884-894. Elsevier 10.1016/j.jmoldx.2019.05.001

[img] Text
1-s2.0-S1525157818303386-main.pdf - Published Version
Restricted to registered users only
Available under License Publisher holds Copyright.

Download (5MB) | Request a copy

The accurate identification of somatic mutations has become a pivotal component of tumor profiling and precision medicine. In molecular diagnostics laboratories, somatic mutation analyses on the Ion Torrent sequencing platform are typically performed on the Ion Reporter platform, which requires extensive manual review of the results and lacks optimized analysis workflows for custom targeted sequencing panels. Alternative solutions that involve custom bioinformatics pipelines involve the sequential execution of software tools with numerous parameters, leading to poor reproducibility and portability. We describe PipeIT, a stand-alone Singularity container of a somatic mutation calling and filtering pipeline for matched tumor-normal Ion Torrent sequencing data. PipeIT is able to identify pathogenic variants in BRAF, KRAS, PIK3CA, CTNNB1, TP53, and other cancer genes that the clinical-grade Oncomine workflow identified. In addition, PipeIT analysis of tumor-normal paired data generated on a custom targeted sequencing panel achieved 100% positive predictive value and 99% sensitivity compared with the 68% to 80% positive predictive value and 92% to 96% sensitivity using the default tumor-normal paired Ion Reporter workflow, substantially reducing the need for manual curation of the results. PipeIT can be rapidly deployed to and ensures reproducible results in any laboratory and can be executed with a single command with minimal input files from the users.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Pre-clinic Human Medicine > BioMedical Research (DBMR)

UniBE Contributor:

Ng, Kiu Yan Charlotte

Subjects:

600 Technology > 610 Medicine & health

ISSN:

1943-7811

Publisher:

Elsevier

Language:

English

Submitter:

Marla Rittiner

Date Deposited:

19 Dec 2019 15:45

Last Modified:

19 Dec 2019 15:45

Publisher DOI:

10.1016/j.jmoldx.2019.05.001

PubMed ID:

31229654

BORIS DOI:

10.7892/boris.136298

URI:

https://boris.unibe.ch/id/eprint/136298

Actions (login required)

Edit item Edit item
Provide Feedback