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RNA-seq alignment to individualized genomes

ABSTRACT: The source of most errors in RNA sequencing (RNA-seq) read alignment is in the repetitive structure of the genome and not with the alignment algorithm. Genetic variation away from the reference sequence exacerbates this problem causing reads to be assigned to the wrong location. We developed a method, implemented as the software package Seqnature, to construct the imputed genomes of individuals (individualized genomes) of experimental model organisms including inbred mouse strains and genetically unique outbred animals. Alignment to individualized genomes increases read mapping accuracy and improves transcript abundance estimates. In an application to expression QTL mapping, this approach corrected erroneous linkages and unmasked thousands of hidden associations. Individualized genomes accounting for genetic variation will be useful for human short-read sequencing and other sequencing applications including ChIP-seq.

ORGANISM(S): Mus musculus

PROVIDER: GSE45684 | GEO | 2014/06/10

SECONDARY ACCESSION(S): PRJNA196894

REPOSITORIES: GEO

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