Integrated analysis of whole-genome paired-end and mate-pair sequencing data for identifying genomic structural variations in multiple myeloma

Rendong Yang, Li Chen, Scott Newman, Khanjan Gandhi, Gregory Doho, Carlos S. Moreno, Paula M. Vertino, Leon Bernal-Mizarchi, Sagar Lonial, Lawrence H. Boise, Michael Rossi, Jeanne Kowalski, Zhaohui S. Qin

Research output: Contribution to journalReview articlepeer-review

10 Scopus citations

Abstract

We present a pipeline to perform integrative analysis of mate-pair (MP) and paired-end (PE) genomic DNA sequencing data. Our pipeline detects structural variations (SVs) by taking aligned sequencing read pairs as input and classifying these reads into properly paired and discordantly paired categories based on their orientation and inferred insert sizes. Recurrent SV was identified from the discordant read pairs. Our pipeline takes into account genomic annotation and genome repetitive element information to increase detection specificity. Application of our pipeline to whole-genome MP and PE sequencing data from three multiple myeloma cell lines (KMS11, MM.1S, and RPMI8226) recovered known SVs, such as heterozygous TRAF3 deletion, as well as a novel experimentally validated SPI1-ZNF287 inter-chromosomal rearrangement in the RPMI8226 cell line.

Original languageEnglish (US)
Pages (from-to)49-53
Number of pages5
JournalCancer Informatics
Volume13
DOIs
StatePublished - Sep 21 2014

Keywords

  • Multiple myeloma
  • Structural variations
  • Variant detection
  • Whole-genome sequencing

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

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