An accurate and fast error-model based simulator for SNPs, Indels and CNVs coupled with a read generator for short-read sequence data Long Description (required)
An open-source variant simulator and read generator capable of simulating all the three common types of biological variants taking into account a distribution of base quality score from a most commonly used next-generation sequencing instrument from Illumina. SInC is capable of generating single- and paired-end reads with user-defined insert size and with high efficiency compared to the other existing tools. SInC, due to its multi-threaded capability during read generation, has a low time footprint. SInC is currently optimised to work in limited infrastructure setup and can efficiently exploit the commonly used quad-core desktop architecture to simulate short sequence reads with deep coverage for large genomes. https://sourceforge.net/projects/sincsimulator/
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Summary of Proposed Changes Current Citations/Applications
[Pubmed ID: 24495296 ],
Pattnaik S, Gupta S, Rao AA, Panda B ,
SInC: an accurate and fast error-model based simulator for SNPs, Indels and CNVs coupled with a read generator for short-read sequence data. ,
BMC Bioinformatics ,
02-05-2014 ,
https://www.ncbi.nlm.nih.gov/pubmed/?term=24495296, Primary Citation
[Pubmed ID: 35345526 ],
Wang S, Li J, Haque AKA, Zhao H, Yang L, Yuan X ,
svBreak: A New Approach for the Detection of Structural Variant Breakpoints Based on Convolutional Neural Network. ,
Biomed Res Int ,
03-19-2022 ,
https://www.ncbi.nlm.nih.gov/pubmed/?term=35345526, , Application
[Pubmed ID: 36532569 ],
Zhang T, Dong J, Jiang H, Zhao Z, Zhou M, Yuan T ,
CNV-PCC: An efficient method for detecting copy number variations from next-generation sequencing data. ,
Front Bioeng Biotechnol ,
12-01-2022 ,
https://www.ncbi.nlm.nih.gov/pubmed/?term=36532569, , Application