Allele-Specic QTL fine-mapping with PLASMA
Name
1237565656-MIT.pdf
Size
12.72 MB
Format
Adobe PDF
Checksum (MD5)
a94857a63b7f18a4e393b82557170b5e
Author(s)
Wang, Austin T.
Advisor(s)
Manolis Kellis and Alexander Gusev.
Alternative Title
Allele-specic quantitative trait loci fine-mapping with PopuLation Allele-Specic MApping
Date Issued
2020
Publisher
Massachusetts Institute of Technology
Abstract
We introduce PLASMA (PopuLation Allele-Specic MApping), a statistical ne- mapping method that leverages allele-specic (AS) genomic data to improve detection of quantitative trait loci (QTLs) with causal effects on molecular traits. In simulations, PLASMA accurately prioritizes causal QTL variants over a wide range of genetic architectures. Applied to RNA-Seq data from 524 kidney tumor samples, PLASMA achieves a greater power at 50 samples than conventional QTL-based ne-mapping at 500 samples: with over 17% of loci ne-mapped to within 5 causal variants compared to 2% by QTL-based ne-mapping, and a 6.9-fold overall reduction in median credible set size. PLASMA offers high accuracy even at small sample sizes, yielding a 1.3-fold reduction in median credible set size compared to QTL-based ne-mapping when applied to H3K27AC ChIP-Seq from just 28 prostate tumor/normal samples. Our results demonstrate how integrating AS activity can substantially improve the detection of causal variants from existing molecular data.
Description
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, February, 2020
Cataloged from student-submitted PDF of thesis.
Includes bibliographical references (pages 35-37).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided.
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