AlleleSeq: Analysis of allele-specific expression and binding in a network framework

Joel Rozowsky, Alexej Abyzov, Jing Wang, Pedro Alves, Debasish Raha, Arif Harmanci, Jing Leng, Robert Bjornson, Yong Kong, Naoki Kitabayashi, Nitin Bhardwaj, Mark Rubin, Michael Snyder, Mark Gerstein

Research output: Contribution to journalArticlepeer-review

179 Scopus citations


To study allele-specific expression (ASE) and binding (ASB), that is, differences between the maternally and paternally derived alleles, we have developed a computational pipeline (AlleleSeq). Our pipeline initially constructs a diploid personal genome sequence (and corresponding personalized gene annotation) using genomic sequence variants (SNPs, indels, and structural variants), and then identifies allele-specific events with significant differences in the number of mapped reads between maternal and paternal alleles. There are many technical challenges in the construction and alignment of reads to a personal diploid genome sequence that we address, for example, bias of reads mapping to the reference allele. We have applied AlleleSeq to variation data for NA12878 from the 1000 Genomes Project as well as matched, deeply sequenced RNA-Seq and ChIP-Seq data sets generated for this purpose. In addition to observing fairly widespread allele-specific behavior within individual functional genomic data sets (including results consistent with X-chromosome inactivation), we can study the interaction between ASE and ASB. Furthermore, we investigate the coordination between ASE and ASB from multiple transcription factors events using a regulatory network framework. Correlation analyses and network motifs show mostly coordinated ASB and ASE.

Original languageEnglish (US)
Article number522
JournalMolecular Systems Biology
StatePublished - 2011


  • ChIP-Seq
  • RNA-Seq
  • allele-specific
  • networks

ASJC Scopus subject areas

  • Information Systems
  • General Immunology and Microbiology
  • Applied Mathematics
  • General Biochemistry, Genetics and Molecular Biology
  • General Agricultural and Biological Sciences
  • Computational Theory and Mathematics


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