MBV: a method to solve sample mislabeling and detect technical bias in large combined genotype and sequencing assay datasets | Zendy

Alexandre Fort | Zendy; Nikolaos Panousis | Zendy; Marco Garieri | Zendy; Stylianos E. Antonarakis | Zendy; Tuuli Lappalainen | Zendy; Emmanouil T. Dermitzakis | Zendy; Olivier Delaneau | Zendy

Open Access

MBV: a method to solve sample mislabeling and detect technical bias in large combined genotype and sequencing assay datasets

Author(s) -

Alexandre Fort,

Nikolaos Panousis,

Marco Garieri,

Stylianos E. Antonarakis,

Tuuli Lappalainen,

Emmanouil T. Dermitzakis,

Olivier Delaneau

Publication year - 2017

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btx074

Subject(s) - computer science , software , genotype , r package , sample (material) , software package , expression quantitative trait loci , matching (statistics) , computational biology , biology , data mining , statistics , genetics , mathematics , gene , single nucleotide polymorphism , chemistry , computational science , chromatography , programming language

Large genomic datasets combining genotype and sequence data, such as for expression quantitative trait loci (eQTL) detection, require perfect matching between both data types.

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