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

Author:

Cameron Daniel L.ORCID,Schröder JanORCID,Penington Jocelyn SietsmaORCID,Do Hongdo,Molania Ramyar,Dobrovic AlexanderORCID,Speed Terence P.ORCID,Papenfuss Anthony T.ORCID

Abstract

The identification of genomic rearrangements with high sensitivity and specificity using massively parallel sequencing remains a major challenge, particularly in precision medicine and cancer research. Here, we describe a new method for detecting rearrangements, GRIDSS (Genome Rearrangement IDentification Software Suite). GRIDSS is a multithreaded structural variant (SV) caller that performs efficient genome-wide break-end assembly prior to variant calling using a novel positional de Bruijn graph-based 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 tumor data, recently winning SV subchallenge #5 of the ICGC-TCGA DREAM8.5 Somatic Mutation Calling Challenge. On human cell line data, GRIDSS halves the false discovery rate compared to other recent methods while matching or exceeding their sensitivity. GRIDSS identifies nontemplate sequence insertions, microhomologies, and large imperfect homologies, estimates a quality score for each breakpoint, stratifies calls into high or low confidence, and supports multisample analysis.

Funder

Australian National Health and Medical Research Council (NHMRC) Program

NHMRC Senior Research Fellowship

Australian Postgraduate Award

Victorian State Government Operational Infrastructure Support and Australian Government NHMRC Independent Research Institute Infrastructure Support

Publisher

Cold Spring Harbor Laboratory

Subject

Genetics (clinical),Genetics

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