Your browser doesn't support javascript.
loading
AltHapAlignR: improved accuracy of RNA-seq analyses through the use of alternative haplotypes.
Lee, Wanseon; Plant, Katharine; Humburg, Peter; Knight, Julian C.
Affiliation
  • Lee W; Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK.
  • Plant K; Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK.
  • Humburg P; Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK.
  • Knight JC; Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK.
Bioinformatics ; 34(14): 2401-2408, 2018 07 15.
Article in En | MEDLINE | ID: mdl-29514179
ABSTRACT
Motivation Reliance on mapping to a single reference haplotype currently limits accurate estimation of allele or haplotype-specific expression using RNA-sequencing, notably in highly polymorphic regions such as the major histocompatibility complex.

Results:

We present AltHapAlignR, a method incorporating alternate reference haplotypes to generate gene- and haplotype-level estimates of transcript abundance for any genomic region where such information is available. We validate using simulated and experimental data to quantify input allelic ratios for major histocompatibility complex haplotypes, demonstrating significantly improved correlation with ground truth estimates of gene counts compared to standard single reference mapping. We apply AltHapAlignR to RNA-seq data from 462 individuals, showing how significant underestimation of expression of the majority of classical human leukocyte antigen genes using conventional mapping can be corrected using AltHapAlignR to allow more accurate quantification of gene expression for individual alleles and haplotypes. Availability and implementation Source code freely available at https//github.com/jknightlab/AltHapAlignR. Supplementary information Supplementary data are available at Bioinformatics online.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Haplotypes / Software / RNA / Gene Expression / Sequence Analysis, RNA / Gene Expression Profiling Limits: Humans Language: En Journal: Bioinformatics Journal subject: INFORMATICA MEDICA Year: 2018 Document type: Article Affiliation country: United kingdom

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Haplotypes / Software / RNA / Gene Expression / Sequence Analysis, RNA / Gene Expression Profiling Limits: Humans Language: En Journal: Bioinformatics Journal subject: INFORMATICA MEDICA Year: 2018 Document type: Article Affiliation country: United kingdom