Ornaments for Accurate and Efficient Allele-Specific Expression Estimation with Bias Correction

Allele-specific expression has been used to elucidate various biological mechanisms, such as genomic imprinting and gene expression variation caused by genetic changes in cis-regulatory elements. However, existing methods for obtaining allele-specific expression from RNA-seq reads do not adequately and efficiently remove various biases, such as reference bias, where reads containing the alternative allele do not map to the reference transcriptome, or ambiguous mapping bias, where reads containing the reference allele map differently from reads containing the alternative allele. We present Ornaments, a computational tool for rapid and accurate estimation of allele-specific expression at unphased heterozygous loci from RNA-seq reads while correcting for allele-specific read mapping bias. Ornaments removes reference bias by accounting for personalized transcriptome, and ambiguous mapping bias by probabilistically assigning reads to multiple transcripts and variant loci they map to. Ornaments is a lightweight extension of kallisto, a popular tool for fast RNA-seq quantification, that improves the efficiency and accuracy of WASP, a popular tool for bias correction in allele-specific read mapping. Our experiments on simulated and human lymphoblastoid cell-line RNA-seq reads with the genomes of the 1000 Genomes Project show that Ornaments is as efficient as kallisto, an order of magnitude faster than WASP, and more accurate than WASP and kallisto. In addition, Ornaments detected genes that are imprinted at transcript level with higher sensitivity, compared to WASP that detected the imprinted signals only at gene level.