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Figure 1 | Genome Biology

Figure 1

From: Improved variant discovery through local re-alignment of short-read next-generation sequencing data using SRMA

Figure 1

Local re-alignment receiver operator characteristic curves for simulated human genome re-sequencing data. A synthetic diploid human genome with SNPs, deletions, and insertions was created from a reference human genome (hg18) as described in main text. One billion paired 50-mer reads for both base space and color space were simulated from this synthetic genome to assess the true positive and false positive rates of variant calling after re-sequencing. An increasing SNP quality filter was used to generate each curve. The simulated dataset was aligned with BWA (v.0.5.7-5) with the default parameters [9]. The alignments from BWA and SRMA were variant called using the MAQ consensus model implemented in SAMtools (v.0.1.17) using the default settings [10, 20]. For the simulated datasets, the resulting variant calls were assessed for accuracy by comparing the called variants against the known introduced sites of variation. The BWA alignments were locally re-aligned with SRMA with variant inclusive settings (c = 2 and p = 0.1).

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