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Internal tandem duplication identification software tools | Whole-exome sequencing data analysis

Detection of tandem duplication within coding exons, referred to as internal tandem duplication (ITD), remains challenging due to inefficiencies in alignment of ITD-containing reads to the reference genome. There is a critical need to develop efficient methods to recover these important mutational events. Source text: Rustagi et al., 2016.

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Genomon ITDetector
Detects somatic internal tandem duplications (ITDs) from cancer genome sequencing data. Genomon ITDectector performs genome-wide identification of ITDs in the target tumor sample and filters out uncertain candidates to remove false positives because of the mis-alignments brought by the redundancy of the genome. This software is specifically designed for performing sensitive and genome-wide detection of somatic ITDs spanning several tens to several hundreds of base pairs.
DB2 / Distribution Based detection of Duplication Boundaries
Uses discordantly aligned reads, taking into account the distribution of fragment length to predict tandem duplications along with their breakpoints on a donor genome. DB2 method fine tunes the breakpoint calls by applying a novel probabilistic framework that incorporates the empirical fragment length distribution to score each feasible breakpoint. DB2 method is not very susceptible to the effects of base calling errors in terms of making false tandem duplication predictions and false boundary detections. One other important aspect of DB2 algorithm is that its performance is stable even when the properties of the sequencing library or the size of tandem duplications in the target genome change.
ITD assembler
A highly sensitive algorithm for identification of (partial) tandem duplication events from massively parallel sequencing data. ITD Assembler evaluates all unmapped and partially mapped reads from whole exome NGS data using a De Bruijn graphs approach to select reads that harbor cycles of appropriate length, followed by assembly using overlap-layout-consensus. It is scalable to run on exome capture sequencing data, and sensitively detects partial, large and complex tandem duplications either adjoining or separated by short nucleotide distances.
SV-AUTOPILOT / Structural Variation AUTOmated PIpeLine Optimization Tool
Standardizes the Structural Variation (SV) detection pipeline. SV-AUTOPILOT is a pipeline that can be used on existing computing infrastructure in the form of a Virtual Machine (VM) Image. It provides a “meta-tool” platform for using multiple SV-tools, to standardize benchmarking of tools, and to provide an easy, out-of-the-box SV detection program. In addition, the user can choose which of several alignment algorithms is used in their analysis.
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