henhaobio
Sign in

Genome ResearchBioinformaticsPeer-reviewed journal article

GRIDSS: sensitive and specific genomic rearrangement detection using positional de Bruijn graph assembly

Daniel CameroniD, Jan SchröderiD, Jocelyn Sietsma PeningtoniD, Hongdo DoiD, Ramyar MolaniaiD, Alexander DobroviciD, Terence Paul SpeediD, Anthony T. PapenfussiD

PDFDOIPreprintCode
Citations
387

Abstract

The identification of genomic rearrangements, particularly in cancers, with high sensitivity and specificity using massively parallel sequencing remains a major challenge. Here, we describe the Genome Rearrangement IDentification Software Suite (GRIDSS), a high-speed structural variant (SV) caller that performs efficient genome-wide break-end assembly prior to variant calling using a novel positional de Bruijn graph assembler. By combining assembly, split read and read pair evidence using a probabilistic scoring, GRIDSS achieves high sensitivity and specificity on simulated, cell line and patient tumour data, recently winning SV sub-challenge #5 of the ICGC-TCGA DREAM Somatic Mutation Calling Challenge. On human cell line data, GRIDSS halves the false discovery rate compared to other recent methods. GRIDSS identifies non-template sequence insertions, micro-homologies and large imperfect homologies, and supports multi-sample analysis. GRIDSS is freely available at https://github.com/PapenfussLab/gridss.

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISCameron '20Cameron '19Wala '18Spies '16Kara '26Hao '26
64% semantic matchBioinformatics
Daniel Cameron, Jonathan Baber, Charles Shale+7 more·bioRxiv·Jul 9, 2020· 9 citations