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While many algorithms have been developed for tasks such as alignment, comprehensive end-to-end pipelines are still sparse. Furthermore, previous pipelines lack features or show technical deficiencies, thus impeding analyses.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      We developed wg-blimp (\n                      <jats:underline>w<\/jats:underline>\n                      hole\n                      <jats:underline>g<\/jats:underline>\n                      enome\n                      <jats:underline>b<\/jats:underline>\n                      isu\n                      <jats:underline>l<\/jats:underline>\n                      f\n                      <jats:underline>i<\/jats:underline>\n                      te sequencing\n                      <jats:underline>m<\/jats:underline>\n                      ethylation analysis\n                      <jats:underline>p<\/jats:underline>\n                      ipeline) as an end-to-end pipeline to ease whole genome bisulfite sequencing data analysis. It integrates established algorithms for alignment, quality control, methylation calling, detection of differentially methylated regions, and methylome segmentation, requiring only a reference genome and raw sequencing data as input. Comparing wg-blimp to previous end-to-end pipelines reveals similar setups for common sequence processing tasks, but shows differences for post-alignment analyses. We improve on previous pipelines by providing a more comprehensive analysis workflow as well as an interactive user interface. To demonstrate wg-blimp\u2019s ability to produce correct results we used it to call differentially methylated regions for two publicly available datasets. We were able to replicate 112 of 114 previously published regions, and found results to be consistent with previous findings. We further applied wg-blimp to a publicly available sample of embryonic stem cells to showcase methylome segmentation. As expected, unmethylated regions were in close proximity of transcription start sites. Segmentation results were consistent with previous analyses, despite different reference genomes and sequencing techniques.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>wg-blimp provides a comprehensive analysis pipeline for whole genome bisulfite sequencing data as well as a user interface for simplified result inspection. We demonstrated its applicability by analysing multiple publicly available datasets. Thus, wg-blimp is a relevant alternative to previous analysis pipelines and may facilitate future epigenetic research.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s12859-020-3470-5","type":"journal-article","created":{"date-parts":[[2020,5,1]],"date-time":"2020-05-01T11:03:27Z","timestamp":1588331007000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["wg-blimp: an end-to-end analysis pipeline for whole genome bisulfite sequencing data"],"prefix":"10.1186","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4994-8380","authenticated-orcid":false,"given":"Marius","family":"W\u00f6ste","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Elsa","family":"Leit\u00e3o","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sandra","family":"Laurentino","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bernhard","family":"Horsthemke","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sven","family":"Rahmann","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christopher","family":"Schr\u00f6der","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2020,5,1]]},"reference":[{"key":"3470_CR1","doi-asserted-by":"publisher","unstructured":"Schr\u00f6der C, Leit\u00e3o E, Wallner S, Schmitz G, Klein-Hitpass L, Sinha A, J\u00f6ckel K-H, Heilmann-Heimbach S, Hoffmann P, N\u00f6then MM, et al.Regions of common inter-individual dna methylation differences in human monocytes: genetic basis and potential function. 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