Open Peer Review Any reports and responses or comments on the article can be found at the end of the article. METHOD ARTICLE MethylExtract: High-Quality methylation maps and SNV calling from whole genome bisulfite sequencing data [version 1; peer review: 2 approved, 1 approved with reservations] Guillermo Barturen , Antonio Rueda , José L. Oliver , Michael Hackenberg 1,2 Dpto. de Genética, Facultad de Ciencias, Universidad de Granada, Granada, 18071, Spain Lab. de Bioinformática, Inst. de Biotecnología, Centro de Investigación Biomédica, Granada, 18016, Spain Abstract Whole genome methylation profiling at a single cytosine resolution is now feasible due to the advent of high-throughput sequencing techniques together with bisulfite treatment of the DNA. To obtain the methylation value of each individual cytosine, the bisulfite-treated sequence reads are first aligned to a reference genome, and then the profiling of the methylation levels is done from the alignments. A huge effort has been made to quickly and correctly align the reads and many different algorithms and programs to do this have been created. However, the second step is just as crucial and non-trivial, but much less attention has been paid to the final inference of the methylation states. Important error sources do exist, such as sequencing errors, bisulfite failure, clonal reads, and single nucleotide variants. We developed , a user friendly tool to: i) generate high quality, MethylExtract whole genome methylation maps and ii) detect sequence variation within the same sample preparation. The program is implemented into a single script and takes into account all major error sources. detects MethylExtract variation (SNVs – Single Nucleotide Variants) in a similar way to ,a VarScan very sensitive method extensively used in SNV and genotype calling based on non-bisulfite-treated reads. The usefulness of is shown by MethylExtract means of extensive benchmarking based on artificial bisulfite-treated reads and a comparison to a recently published method, called . Bis-SNP is able to detect SNVs within High-Throughput Sequencing MethylExtract experiments of bisulfite treated DNA at the same time as it generates high quality methylation maps. This simultaneous detection of DNA methylation and sequence variation is crucial for many downstream analyses, for example when deciphering the impact of SNVs on differential methylation. An exclusive feature of , in comparison with existing software, MethylExtract is the possibility to assess the bisulfite failure in a statistical way. The source code, tutorial and artificial bisulfite datasets are available at and http://bioinfo2.ugr.es/MethylExtract/ , and also permanently http://sourceforge.net/projects/methylextract/ accessible from . 10.5281/zenodo.7144 1,2 1,2 1,2 1,2 1 2 Reviewer Status Invited Reviewers version 2 (revision) 21 Feb 2014 version 1 15 Oct 2013 1 2 3 report report report report report , Friedrich-Miescher Institute Michael B. Stadler for Biomedical Research, Basel, Switzerland 1 , University of Saarland, Jörn Walter Saarbrücken, Germany 2 , Babraham Institute, Babraham, Felix Krueger UK 3 15 Oct 2013, :217 First published: 2 https://doi.org/10.12688/f1000research.2-217.v1 21 Feb 2014, :217 Latest published: 2 https://doi.org/10.12688/f1000research.2-217.v2 v1 Page 1 of 22 F1000Research 2013, 2:217 Last updated: 21 MAY 2020