Estimating error models for whole genome sequencing using mixtures of Dirichlet-multinomial distributions

STEVEN HUNG-HSI WU; Schwartz, R.S; Winter, D.J; Conrad, D.F; Cartwright, R.A.; Wu, S.H;Schwartz, R.S;Winter, D.J;Conrad, D.F;Cartwright, R.A.

doi:10.1093/bioinformatics/btx133

Estimating error models for whole genome sequencing using mixtures of Dirichlet-multinomial distributions

Journal

Bioinformatics

Journal Volume

33

Journal Issue

15

Date Issued

2017

Author(s)

STEVEN HUNG-HSI WU

Schwartz, R.S

Winter, D.J

Conrad, D.F

Cartwright, R.A.

DOI

10.1093/bioinformatics/btx133

URI

https://scholars.lib.ntu.edu.tw/handle/123456789/578168

URL

http://dx.doi.org/10.1093/bioinformatics/btx133

Abstract

Accurate identification of genotypes is an essential part of the analysis of genomic data, including in identification of sequence polymorphisms, linking mutations with disease and determining mutation rates. Biological and technical processes that adversely affect genotyping include copy-number-variation, paralogous sequences, library preparation, sequencing error and reference-mapping biases, among others.

Publisher

Oxford University Press

Type

journal article

File(s)

Name

Estimating error models for whole genome sequencing using mixtures of Dirichlet-multinomial distributions

Size

510.13 KB

Format

Adobe PDF

Checksum

(MD5):2f575bc9f9ccbd41b3fb1019f2f35d75

Estimating error models for whole genome sequencing using mixtures of Dirichlet-multinomial distributions

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