SUMMARY: Small insertions and deletions (indels) in nucleotide sequence may be represented differently between mapping algorithms and variant callers, or in the flanking sequence context. Representational ambiguity is especially profound for complex indels, complicating comparisons between multiple mappings and call sets. Complex indels may additionally suffer from incomplete allele representation, potentially leading to critical misannotation of variant effect. We present indelPost, a Python library that harmonizes these ambiguities for simple and complex indels via realignment and read-based phasing. We demonstrate that indelPost enables accurate analysis of ambiguous data and can derive the correct complex indel alleles from the simple indel predictions provided by standard small variant detectors, with improved performance over a specialized tool for complex indel analysis. AVAILABILITY AND IMPLEMENTATION: indelPost is freely available at: https://github.com/stjude/indelPost. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MOTIVATION: Reliable identification of expressed somatic insertions/deletions (indels) is an unmet need due to artifacts generated in PCR-based RNA-Seq library preparation and the lack of normal RNA-Seq data, presenting analytical challenges for discovery of somatic indels in tumor transcriptome. RESULTS: We present RNAIndel, a tool for predicting somatic, germline and artifact indels from tumor RNA-Seq data. RNAIndel leverages features derived from indel sequence context and biological effect in a machine-learning framework. Except for tumor samples with microsatellite instability, RNAIndel robustly predicts 88-100% of somatic indels in five diverse test datasets of pediatric and adult cancers, even recovering subclonal (VAF range 0.01-0.15) driver indels missed by targeted deep-sequencing, outperforming the current best-practice for RNA-Seq variant calling which had 57% sensitivity but with 14 times more false positives. AVAILABILITY AND IMPLEMENTATION: RNAIndel is freely available at https://github.com/stjude/RNAIndel. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Bioinformatics (2019) doi: 10.1093/bioinformatics/btz753 In the above paper, Table 4 has been corrected as follows. Original: Corrected version: