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HapIso: An Accurate Method for the Haplotype-Specific Isoforms Reconstruction from Long Single-Molecule Reads

Serghei Mangul, Harry (Taegyun) Yang, Farhad Hormozdiari, Elizabeth Tseng, Alex Zelikovsky, Eleazar Eskin
doi: https://doi.org/10.1101/050906
Serghei Mangul
1Department of Computer Science, University of California, Los Angeles, CA. USA
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  • For correspondence: smangul@ucla.edu harrydgnt@g.ucla.edu
Harry (Taegyun) Yang
1Department of Computer Science, University of California, Los Angeles, CA. USA
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Farhad Hormozdiari
1Department of Computer Science, University of California, Los Angeles, CA. USA
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Elizabeth Tseng
2Pacific Biosciences, Menlo Park, CA. USA
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Alex Zelikovsky
3Department of Computer Science, Georgia State University, Atlanta, GA. USA
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Eleazar Eskin
1Department of Computer Science, University of California, Los Angeles, CA. USA
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Abstract

Sequencing of RNA provides the possibility to study an individual’s transcriptome landscape and determine allelic expression ratios. Single-molecule protocols generate multi-kilobase reads longer than most transcripts allowing sequencing of complete haplotype isoforms. This allows partitioning the reads into two parental haplotypes. While the read length of the single-molecule protocols is long, the relatively high error rate limits the ability to accurately detect the genetic variants and assemble them into the haplotype-specific isoforms. In this paper, we present HapIso (Haplotype-specific Isoform Reconstruction), a method able to tolerate the relatively high error-rate of the single-molecule platform and partition the isoform reads into the parental alleles. Phasing the reads according to the allele of origin allows our method to efficiently distinguish between the read errors and the true biological mutations. HapIso uses a k-means clustering algorithm aiming to group the reads into two meaningful clusters maximizing the similarity of the reads within cluster and minimizing the similarity of the reads from different clusters. Each cluster corresponds to a parental haplotype. We use family pedigree information to evaluate our approach. Experimental validation suggests that HapIso is able to tolerate the relatively high error-rate and accurately partition the reads into the parental alleles of the isoform transcripts. Furthermore, our method is the first method able to reconstruct the haplotype-specific isoforms from long single-molecule reads.

The open source Python implementation of HapIso is freely available for download at https://github.com/smangul1/HapIso/

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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Posted May 09, 2016.
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HapIso: An Accurate Method for the Haplotype-Specific Isoforms Reconstruction from Long Single-Molecule Reads
Serghei Mangul, Harry (Taegyun) Yang, Farhad Hormozdiari, Elizabeth Tseng, Alex Zelikovsky, Eleazar Eskin
bioRxiv 050906; doi: https://doi.org/10.1101/050906
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HapIso: An Accurate Method for the Haplotype-Specific Isoforms Reconstruction from Long Single-Molecule Reads
Serghei Mangul, Harry (Taegyun) Yang, Farhad Hormozdiari, Elizabeth Tseng, Alex Zelikovsky, Eleazar Eskin
bioRxiv 050906; doi: https://doi.org/10.1101/050906

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