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Tools and best practices for data processing in allelic expression analysis
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Tools and best practices for data processing in allelic expression analysis
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Journal Article
Tools and best practices for data processing in allelic expression analysis
2015
Overview
Allelic expression analysis has become important for integrating genome and transcriptome data to characterize various biological phenomena such as
cis
-regulatory variation and nonsense-mediated decay. We analyze the properties of allelic expression read count data and technical sources of error, such as low-quality or double-counted RNA-seq reads, genotyping errors, allelic mapping bias, and technical covariates due to sample preparation and sequencing, and variation in total read depth. We provide guidelines for correcting such errors, show that our quality control measures improve the detection of relevant allelic expression, and introduce tools for the high-throughput production of allelic expression data from RNA-sequencing data.
Publisher
BioMed Central,Springer Nature B.V
Subject
/ Animal Genetics and Genomics
/ Bias
/ Biomedical and Life Sciences
/ Data Interpretation, Statistical
/ DNA
/ Gene Expression Profiling - methods
/ Gene Expression Profiling - standards
/ genome
/ Genomes
/ Genomics
/ Genotyping Techniques - standards
/ Humans
/ Method
/ Microbial Genetics and Genomics
/ Proteins
/ RNA
/ Software
