Author: Pandya, Gagan A.; Holmes, Michael H.; Sunkara, Sirisha; Sparks, Andrew; Bai, Yun; Verratti, Kathleen; Saeed, Kelly; Venepally, Pratap; Jarrahi, Behnam; Fleischmann, Robert D.; Peterson, Scott N.
Title: A bioinformatic filter for improved base-call accuracy and polymorphism detection using the Affymetrix GeneChip® whole-genome resequencing platform Document date: 2007_11_15
ID: 16tii0ha_22
Snippet: pair at a particular locus (4), so calls with low quality scores are more likely to be incorrect than high-scoring calls. We have found that filtering out SNP calls with quality scores less than 12.0 removes a large number of false positives, at a relatively small cost in terms of true positives rejected. A receiver operating characteristic (ROC) curve that illustrates the effect of different quality threshold values is shown in Figure 3 . (For t.....
Document: pair at a particular locus (4), so calls with low quality scores are more likely to be incorrect than high-scoring calls. We have found that filtering out SNP calls with quality scores less than 12.0 removes a large number of false positives, at a relatively small cost in terms of true positives rejected. A receiver operating characteristic (ROC) curve that illustrates the effect of different quality threshold values is shown in Figure 3 . (For the analysis in Figure 3 only, we used our own quality filter in preference to the quality filter in the GSEQ software, so that we could easily test the effect of different quality thresholds. For all other analyses, the quality filter incorporated in GSEQ was used. The GSEQ software is run before our filters, so the quality filter was actually the first filter applied, except in the case of Figure 3 .)
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