2012
DOI: 10.1007/s00335-012-9424-0
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High throughput sequencing approaches to mutation discovery in the mouse

Abstract: Phenotype driven approaches in mice are powerful strategies for the discovery of genes, gene functions and for unravelling complex biological mechanisms. Traditional methods for mutation discovery are reliable and robust, but they can also be laborious and time consuming. Recently, high throughput sequencing (HTS) technologies have revolutionised the process of forward genetics in mice by paving the way to rapid mutation discovery. However, successful application of HTS for mutation discovery is relies heavily… Show more

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Cited by 5 publications
(6 citation statements)
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“…Single‐nucleotide variant (SNV) cells were made using a customized version of The Genome Analysis Toolkit (GATK) with default parameters. Several triaging steps were made to reduce false positives . The 17 Mouse Genome data set was used to filter inbred SNP sites from the RCALC1 SNV data set, and common sites were removed from further investigation.…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…Single‐nucleotide variant (SNV) cells were made using a customized version of The Genome Analysis Toolkit (GATK) with default parameters. Several triaging steps were made to reduce false positives . The 17 Mouse Genome data set was used to filter inbred SNP sites from the RCALC1 SNV data set, and common sites were removed from further investigation.…”
Section: Methodsmentioning
confidence: 99%
“…Several triaging steps were made to reduce false positives. (33) The 17 Mouse Genome data set (34) was used to filter inbred SNP sites from the RCALC1 SNV data set, and common sites were removed from further investigation. The remaining SNVs were further filtered by removing sites with an allele frequency <35% and >80%, a read depth <3, and a quality score <200.…”
Section: Exome Sequence Analysismentioning
confidence: 99%
“…Single‐nucleotide variant (SNV) calls were made using a customized version of The Genome Analysis Toolkit (GATK) with default parameters. Several triaging steps were made to reduce false positives . The 17 Mouse Genome dataset was used to filter inbred SNP sites from the RCALC2 SNV dataset, and common sites were removed from further investigation.…”
Section: Methodsmentioning
confidence: 99%
“…Several triaging steps were made to reduce false positives. (26) The 17 Mouse Genome dataset (27) was used to filter inbred SNP sites from the RCALC2 SNV dataset, and common sites were removed from further investigation. The remaining SNVs were further filtered by removing sites with an allele frequency <35% and >80%, a read depth <3 and a quality score >200.…”
Section: Exome Sequence Analysismentioning
confidence: 99%
“…Over the years a number of typical steps have been employed to remove the false positives. These steps include one or more of the following: a read depth threshold where variants found in less than the allotted number of reads are ignored, a quality threshold where variants in poorly mapped reads are ignored and inbred SNP identification where variants overlapping background SNV sites are ignored (Simon et al 2012 ). This prioritisation and filtering of SNVs is a crucial step in the NGS pipeline as false discovery of erroneous SNVs masquerading as real ENU variants can result in incorrect candidate genes, whereas over-filtering can result in the exclusion of the real causal mutation, resulting in the failure of the experiment.…”
Section: Next Generation Sequencingmentioning
confidence: 99%