{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,11]],"date-time":"2025-11-11T15:55:07Z","timestamp":1762876507039},"reference-count":22,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,6,5]],"date-time":"2024-06-05T00:00:00Z","timestamp":1717545600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,6,5]],"date-time":"2024-06-05T00:00:00Z","timestamp":1717545600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"the Agricultural Science and Technology Innovation Program of Chinese Academy of Agricultural Sciences"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Bioinformatics"],"abstract":"<jats:title>Abstract<\/jats:title><jats:sec>\n                <jats:title>Background<\/jats:title>\n                <jats:p>Bisulfite sequencing (BS-Seq) is a fundamental technique for characterizing DNA methylation profiles. Genotype calling from bisulfite-converted BS-Seq data allows allele-specific methylation analysis and the concurrent exploration of genetic and epigenetic profiles. Despite various methods have been proposed, single nucleotide polymorphisms (SNPs) calling from BS-Seq data, particularly for SNPs on chromosome X and in the presence of contaminative data, poses ongoing challenges.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>We introduce bsgenova, a novel SNP caller tailored for bisulfite sequencing data, employing a Bayesian multinomial model. The performance of bsgenova is assessed by comparing SNPs called from real-world BS-Seq data with those from corresponding whole-genome sequencing (WGS) data across three human cell lines. bsgenova is both sensitive and precise, especially for chromosome X, compared with three existing methods. Moreover, in the presence of low-quality reads, bsgenova outperforms other methods notably. In addition, bsgenova is meticulously implemented, leveraging matrix imputation and multi-process parallelization. Compared to existing methods, bsgenova stands out for its speed and efficiency in memory and disk usage. Furthermore, bsgenova integrates bsextractor, a methylation extractor, enhancing its flexibility and expanding its utility.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusions<\/jats:title>\n                <jats:p>We introduce bsgenova for SNP calling from bisulfite-sequencing data. The source code is available at <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"uri\" xlink:href=\"https:\/\/github.com\/hippo-yf\/bsgenova\">https:\/\/github.com\/hippo-yf\/bsgenova<\/jats:ext-link> under license GPL-3.0.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1186\/s12859-024-05821-7","type":"journal-article","created":{"date-parts":[[2024,6,5]],"date-time":"2024-06-05T09:16:19Z","timestamp":1717578979000},"update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["bsgenova: an accurate, robust, and fast genotype caller for bisulfite-sequencing data"],"prefix":"10.1186","volume":"25","author":[{"given":"Yance","family":"Feng","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fei","family":"Gao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,6,5]]},"reference":[{"issue":"1","key":"5821_CR1","doi-asserted-by":"publisher","first-page":"5238","DOI":"10.1038\/s41467-020-19077-1","volume":"11","author":"J Abante","year":"2020","unstructured":"Abante J, et al. 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