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. 2017 Jan 3;18:8. doi: 10.1186/s12859-016-1417-7

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© The Author(s) 2017

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License(http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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Fig. 3 — Categories of variant calling errors depending on the quality of the alignment. The top panel (a and b) shows the error categories for the high confidence false positives (prediction sets with at least 95% precision). The bottom panel (c and d) shows the error categories for the high-frequency false negatives (ground truth allele frequency ≥25%). The left panel (a and c) displays the error sources when running default bowtie2 alignments, and the right panel (b and d) displays the error sources when running more sensitive alignments, which were performed with parameters —very-sensitive -k 20, and then choosing the primary alignment for each read with several alignments (samtools view -F 256), i.e. the “best” option. The definition of the categories can be found in Section “Analysis of error sources”