A high-fidelity simulation validation framework for high-throughput genome sequencing with cancer applications Long Description (required) VarSim is a framework for assessing alignment and variant calling accuracy in high-throughput genome sequencing through simulation or real data. In contrast to simulating a random mutation spectrum, it synthesizes diploid genomes with germline and somatic mutations based on a realistic model. This model leverages information such as previously reported mutations to make the synthetic genomes biologically relevant. VarSim simulates and validates a wide range of variants, including single nucleotide variants, small indels and large structural variants. It is an automated, comprehensive compute framework supporting parallel computation and multiple read simulators. Furthermore, we developed a novel map data structure to validate read alignments, a strategy to compare variants binned in size ranges and a lightweight, interactive, graphical report to visualize validation results with detailed statistics. Thus far, it is the most comprehensive validation tool for secondary analysis in next generation sequencing. https://github.com/bioinform/varsim Step 1: Use the attribute tree to add new attributes or remove pre-selected attributes to describe the simulator. Every sub-attribute is selected Not all sub-attributes are selected Fill Clear Expand Collapse Reset Summary of Proposed Changes Step 2: Review list of proposed attribute addition(s) and subtraction(s). Can't Find the Attribute You Are Looking For?
If you would like to propose an attribute that you cannot find in the tree above, or if you would like to add a clarification to one or more attributes for this simulator (e.g. a specific file format for attribute /Output/File Format/Other), please list them in the
Additional Comment box of the Submit tab. Summary of Proposed Changes Current Citations/Applications
VarSim: a high-fidelity simulation and validation framework for high-throughput genome sequencing with cancer applications. Bioinformatics,
https://www.ncbi.nlm.nih.gov/pubmed/?term=25524895, Primary Citation