IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v7y2016i1d10.1038_ncomms12817.html
   My bibliography  Save this article

Rare variant phasing and haplotypic expression from RNA sequencing with phASER

Author

Listed:
  • Stephane E. Castel

    (New York Genome Center
    Columbia University)

  • Pejman Mohammadi

    (New York Genome Center
    Columbia University)

  • Wendy K. Chung

    (Columbia University)

  • Yufeng Shen

    (Columbia University
    Columbia University)

  • Tuuli Lappalainen

    (New York Genome Center
    Columbia University)

Abstract

Haplotype phasing of genetic variants is important for clinical interpretation of the genome, population genetic analysis and functional genomic analysis of allelic activity. Here we present phASER, an accurate approach for phasing variants that are overlapped by sequencing reads, including those from RNA sequencing (RNA-seq), which often span multiple exons due to splicing. Using diverse RNA-seq data we demonstrate that this provides more accurate phasing of rare variants compared with population-based phasing and allows phasing of variants in the same gene up to hundreds of kilobases away that cannot be obtained from DNA sequencing (DNA-seq) reads. We show that in the context of medical genetic studies this improves the resolution of compound heterozygotes. Additionally, phASER provides measures of haplotypic expression that increase power and accuracy in studies of allelic expression. In summary, phasing using RNA-seq and phASER is accurate and improves studies where rare variant haplotypes or allelic expression is needed.

Suggested Citation

  • Stephane E. Castel & Pejman Mohammadi & Wendy K. Chung & Yufeng Shen & Tuuli Lappalainen, 2016. "Rare variant phasing and haplotypic expression from RNA sequencing with phASER," Nature Communications, Nature, vol. 7(1), pages 1-6, November.
  • Handle: RePEc:nat:natcom:v:7:y:2016:i:1:d:10.1038_ncomms12817
    DOI: 10.1038/ncomms12817
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/ncomms12817
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/ncomms12817?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Liina Nagirnaja & Alexandra M. Lopes & Wu-Lin Charng & Brian Miller & Rytis Stakaitis & Ieva Golubickaite & Alexandra Stendahl & Tianpengcheng Luan & Corinna Friedrich & Eisa Mahyari & Eloise Fadial &, 2022. "Diverse monogenic subforms of human spermatogenic failure," Nature Communications, Nature, vol. 13(1), pages 1-18, December.
    2. Nava Ehsan & Bence M. Kotis & Stephane E. Castel & Eric J. Song & Nicholas Mancuso & Pejman Mohammadi, 2024. "Haplotype-aware modeling of cis-regulatory effects highlights the gaps remaining in eQTL data," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
    3. Andrea Wilderman & Eva D’haene & Machteld Baetens & Tara N. Yankee & Emma Wentworth Winchester & Nicole Glidden & Ellen Roets & Jo Dorpe & Sandra Janssens & Danny E. Miller & Miranda Galey & Kari M. B, 2024. "A distant global control region is essential for normal expression of anterior HOXA genes during mouse and human craniofacial development," Nature Communications, Nature, vol. 15(1), pages 1-23, December.
    4. Xena Marie Mapel & Naveen Kumar Kadri & Alexander S. Leonard & Qiongyu He & Audald Lloret-Villas & Meenu Bhati & Maya Hiltpold & Hubert Pausch, 2024. "Molecular quantitative trait loci in reproductive tissues impact male fertility in cattle," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    5. Asia Mendelevich & Svetlana Vinogradova & Saumya Gupta & Andrey A. Mironov & Shamil R. Sunyaev & Alexander A. Gimelbrant, 2021. "Replicate sequencing libraries are important for quantification of allelic imbalance," Nature Communications, Nature, vol. 12(1), pages 1-13, December.
    6. Iker Núñez-Carpintero & Maria Rigau & Mattia Bosio & Emily O’Connor & Sally Spendiff & Yoshiteru Azuma & Ana Topf & Rachel Thompson & Peter A. C. ’t Hoen & Teodora Chamova & Ivailo Tournev & Velina Gu, 2024. "Rare disease research workflow using multilayer networks elucidates the molecular determinants of severity in Congenital Myasthenic Syndromes," Nature Communications, Nature, vol. 15(1), pages 1-15, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:7:y:2016:i:1:d:10.1038_ncomms12817. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.