Socrates: identification of genomic rearrangements in tumour genomes by re-aligning soft clipped reads

Jan Schröder; Arthur Hsu; Samantha E Boyle; Geoff Macintyre; Marek Cmero; Richard W Tothill; Ricky W Johnstone; Mark Shackleton; Anthony T Papenfuss

doi:10.1093/bioinformatics/btt767

Socrates: identification of genomic rearrangements in tumour genomes by re-aligning soft clipped reads

Bioinformatics. 2014 Apr 15;30(8):1064-1072. doi: 10.1093/bioinformatics/btt767. Epub 2014 Jan 2.

Authors

Jan Schröder¹, Arthur Hsu¹, Samantha E Boyle¹, Geoff Macintyre¹, Marek Cmero², Richard W Tothill¹, Ricky W Johnstone¹, Mark Shackleton³, Anthony T Papenfuss³

Affiliations

¹ Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria 3052, Department of Medical Biology, University of Melbourne, Victoria 3010, Melanoma Research Laboratory, Peter MacCallum Cancer Centre, East Melbourne, Victoria 3002, Department of Pathology, The University of Melbourne, Victoria 3010, NICTA Victoria Laboratory, The University of Melbourne, Victoria 3010, Department of Computing and Information Systems, University of Melbourne, Victoria 3010, Cancer Therapeutics Program, Peter MacCallum Cancer Centre, East Melbourne, Victoria 3002, Sir Peter MacCallum Department of Oncology, The University of Melbourne, Victoria 3010, Department of Mathematics and Statistics, The University of Melbourne, Victoria 3010 and Bioinformatics and Cancer Genomics Laboratory, Peter MacCallum Cancer Centre, East Melbourne, Victoria 3002, Australia Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria 3052, Department of Medical Biology, University of Melbourne, Victoria 3010, Melanoma Research Laboratory, Peter MacCallum Cancer Centre, East Melbourne, Victoria 3002, Department of Pathology, The University of Melbourne, Victoria 3010, NICTA Victoria Laboratory, The University of Melbourne, Victoria 3010, Department of Computing and Information Systems, University of Melbourne, Victoria 3010, Cancer Therapeutics Program, Peter MacCallum Cancer Centre, East Melbourne, Victoria 3002, Sir Peter MacCallum Department of Oncology, The University of Melbourne, Victoria 3010, Department of Mathematics and Statistics, The University of Melbourne, Victoria 3010 and Bioinformatics and Cancer Genomics Laboratory, Peter MacCallum Cancer Centre, East Melbourne, Victoria 3002, Australia.
² Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria 3052, Department of Medical Biology, University of Melbourne, Victoria 3010, Melanoma Research Laboratory, Peter MacCallum Cancer Centre, East Melbourne, Victoria 3002, Department of Pathology, The University of Melbourne, Victoria 3010, NICTA Victoria Laboratory, The University of Melbourne, Victoria 3010, Department of Computing and Information Systems, University of Melbourne, Victoria 3010, Cancer Therapeutics Program, Peter MacCallum Cancer Centre, East Melbourne, Victoria 3002, Sir Peter MacCallum Department of Oncology, The University of Melbourne, Victoria 3010, Department of Mathematics and Statistics, The University of Melbourne, Victoria 3010 and Bioinformatics and Cancer Genomics Laboratory, Peter MacCallum Cancer Centre, East Melbourne, Victoria 3002, Australia.
³ Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria 3052, Department of Medical Biology, University of Melbourne, Victoria 3010, Melanoma Research Laboratory, Peter MacCallum Cancer Centre, East Melbourne, Victoria 3002, Department of Pathology, The University of Melbourne, Victoria 3010, NICTA Victoria Laboratory, The University of Melbourne, Victoria 3010, Department of Computing and Information Systems, University of Melbourne, Victoria 3010, Cancer Therapeutics Program, Peter MacCallum Cancer Centre, East Melbourne, Victoria 3002, Sir Peter MacCallum Department of Oncology, The University of Melbourne, Victoria 3010, Department of Mathematics and Statistics, The University of Melbourne, Victoria 3010 and Bioinformatics and Cancer Genomics Laboratory, Peter MacCallum Cancer Centre, East Melbourne, Victoria 3002, Australia Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria 3052, Department of Medical Biology, University of Melbourne, Victoria 3010, Melanoma Research Laboratory, Peter MacCallum Cancer Centre, East Melbourne, Victoria 3002, Department of Pathology, The University of Melbourne, Victoria 3010, NICTA Victoria Laboratory, The University of Melbourne, Victoria 3010, Department of Computing and Information Systems, University of Melbourne, Victoria 3010, Cancer Therapeutics Program, Peter MacCallum Cancer Centre, East Melbourne, Victoria 3002, Sir Peter MacCallum Department of Oncology, The University of Melbourne, Victoria 3010, Department of Mathematics and Statistics, The University of Melbourne, Victoria 3010 and Bioinformatics and Cancer Genomics Laboratory, Peter MacCallum Cancer Centre, East Melbourne, Victoria 3002, Australia Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria 3052, Department of Medical Biology, University of Melbourne, Victoria 3010, Melanoma Research Laboratory, Peter MacCallum Cancer Centre, East Melbourne, Victoria 3002, Department of Pathology, The University of Melbourne, Victoria 3010, NICTA Victoria Laboratory, The University of Melbourne, Victoria 3010, Department of Computing and Information Systems, University of Melbourne, Victoria 3010, Cancer Therapeutics Program, Peter MacCallum Cancer Centre, East Melbourne, Victoria 3002, Sir Peter MacCallum Department of Oncology, The University of Melbourne, Victoria 3010, Department of Mathematics and Statistics, The University of Melbourne, Victoria 3010 and Bioinformatics and Cancer Genomics Laboratory, Peter MacCallum Cancer Centre, East Melbourne, Victoria 3002, Australia Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria 3052, Department of Medical Biology, University of Melbourne, Victoria 3010, Melanoma Research Laboratory, Peter MacCallum Cancer Centre, East Melbourne, Victoria 3002, Department of Pathology, The University of Melbourne, Victoria 3010, NICTA Victoria Laboratory, The University of Melbourne, Victoria 3010, Department of Computing and Information Systems, University of Melbourne, Victoria 3010, Cancer Therapeutics Program, Peter MacCallum Cancer Centre, East Melbourne, Victoria 3002, Sir Peter MacCallum Department of Oncology, The University of Melbourne, Victoria 3010, Department of Mathematics and Statistics, The University of Melbourne, Victoria 3010 and Bioinformatics and Cancer Genomics Laboratory, Peter MacCallum Cancer Centre, East Melbourne, Victoria 3002, Australia.

Abstract

Motivation: Methods for detecting somatic genome rearrangements in tumours using next-generation sequencing are vital in cancer genomics. Available algorithms use one or more sources of evidence, such as read depth, paired-end reads or split reads to predict structural variants. However, the problem remains challenging due to the significant computational burden and high false-positive or false-negative rates.

Results: In this article, we present Socrates (SOft Clip re-alignment To idEntify Structural variants), a highly efficient and effective method for detecting genomic rearrangements in tumours that uses only split-read data. Socrates has single-nucleotide resolution, identifies micro-homologies and untemplated sequence at break points, has high sensitivity and high specificity and takes advantage of parallelism for efficient use of resources. We demonstrate using simulated and real data that Socrates performs well compared with a number of existing structural variant detection tools.

Availability and implementation: Socrates is released as open source and available from http://bioinf.wehi.edu.au/socrates CONTACT: papenfuss@wehi.edu.au Supplementary information: Supplementary data are available at Bioinformatics online.

MeSH terms

Algorithms
Computational Biology
Genomics / methods
High-Throughput Nucleotide Sequencing / methods
Humans
Neoplasms / genetics*
Sequence Analysis, DNA / methods
Software*