Supporting data for "ScanITD: detecting internal tandem duplication with robust variant allele frequency estimation"

Internal tandem duplications (ITDs) are tandem duplications within coding exons and are important prognostic markers and drug targets for acute myeloid leukemia (AML). Next generation sequencing has enabled the discovery of ITD at single nucleotide resolution. ITD allele frequency is used in the risk stratification of AML patients, higher ITD allele frequency has been proved for its association with poorer clinical outcomes. However, the ITD allele frequency data is often unavailable to treating physicians and the detection of ITDs with accurate variant allele frequency (VAF) estimation remains challenging for short read sequencing.<br>Here we present ScanITD approach that performs a stepwise seed-and-realignment procedure for ITD detection with accurate VAF prediction. The evaluations on simulated and real data demonstrate that ScanITD outperforms three state-of-the-art ITD detectors, especially for VAF estimation. Importantly, ScanITD yields better accuracy than general-purpose structural variations callers for predicting ITD size range duplications. <br>ScanITD enables the accurate identification of ITDs with robust VAF estimation. ScanITD is written in Python, and is open-source software and freely accessible at GitHub.