ASElux: an ultra-fast and accurate allelic reads counter.
Bioinformatics
; 34(8): 1313-1320, 2018 04 15.
Article
in En
| MEDLINE
| ID: mdl-29186329
ABSTRACT
Motivation Mapping bias causes preferential alignment to the reference allele, forming a major obstacle in allele-specific expression (ASE) analysis. The existing methods, such as simulation and SNP-aware alignment, are either inaccurate or relatively slow. To fast and accurately count allelic reads for ASE analysis, we developed a novel approach, ASElux, which utilizes the personal SNP information and counts allelic reads directly from unmapped RNA-sequence (RNA-seq) data. ASElux significantly reduces runtime by disregarding reads outside single nucleotide polymorphisms (SNPs) during the alignment. Results:
When compared to other tools on simulated and experimental data, ASElux achieves a higher accuracy on ASE estimation than non-SNP-aware aligners and requires a much shorter time than the benchmark SNP-aware aligner, GSNAP with just a slight loss in performance. ASElux can process 40 million read-pairs from an RNA-sequence (RNA-seq) sample and count allelic reads within 10 min, which is comparable to directly counting the allelic reads from alignments based on other tools. Furthermore, processing an RNA-seq sample using ASElux in conjunction with a general aligner, such as STAR, is more accurate and still â¼4× faster than STAR + WASP, and â¼33× faster than the lead SNP-aware aligner, GSNAP, making ASElux ideal for ASE analysis of large-scale transcriptomic studies. We applied ASElux to 273 lung RNA-seq samples from GTEx and identified a splice-QTL rs11078928 in lung which explains the mechanism underlying an asthma GWAS SNP rs11078927. Thus, our analysis demonstrated ASE as a highly powerful complementary tool to cis-expression quantitative trait locus (eQTL) analysis. Availability and implementation The software can be downloaded from https//github.com/abl0719/ASElux. Contact zmiao@ucla.edu or a5ko@ucla.edu. Supplementary information Supplementary data are available at Bioinformatics online.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Software
/
Gene Expression Profiling
/
Polymorphism, Single Nucleotide
/
Quantitative Trait Loci
/
Alleles
Type of study:
Prognostic_studies
Limits:
Humans
Language:
En
Journal:
Bioinformatics
Journal subject:
INFORMATICA MEDICA
Year:
2018
Type:
Article
Affiliation country:
United States