SEESAW: Statistical Estimation Of Allelic Expression Using Salmon And Swish**

SEESAW: Statistical Estimation Of Allelic Expression Using Salmon And Swish**

Author(s): Euphy Wu, Noor Pratap Singh, Mohsen Zakeri, Rob Patro, Michael I Love

Affiliation(s): UNC-Chapel Hill

Twitter: @mikelove

There are a number of existing bioinformatic pipelines for assessing allelic imbalance of expression. These often consist of genomic alignment of RNA-seq reads, removal of multi-mapping bias, counting of reference and alternate alleles, statistical inference on the allelic ratio: null hypothesis testing of the ratio representing balanced expression of the two alleles. In this software demo, we will demonstrate a new suite of tools, SEESAW (Statistical Estimation of allelic Expression using Salmon and sWish). Here we leverage the Bioconductor packages tximeta and fishpond, to import and analyze Salmon isoform-level quantification of allelic expression with uncertainty estimates accounting for genomic/isoform/allelic multi-mapping reads. SEESAW makes use of existing and new functionality in the swish() function in the fishpond package, enabling detection of either global allelic imbalance or trends in imbalance across continuous or categorical covariates. A biological interest driving the development of SEESAW is to enable identification of isoform-specific allelic imbalance as a result of cis-acting genetic variants. We propose to run Swish on isoform quantification data aggregated at the level of transcription start sites (TSS). This aggregation increases statistical power in differential testing, while providing biologically meaningful feature sets. We will demonstrate new plotting functions in the fishpond package that facilitate visualization of allelic and isoform changes at different resolutions, alongside gene models.

Package demo details

Source code


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