NGSmethDB: an updated genome resource for high quality, single-cytosine resolution methylomes
The updated release of 'NGSmethDB' (http://bioinfo2.ugr.es/NGSmethDB) is a repository for single-base whole-genome methylome maps for the best-assembled eukaryotic genomes. Short-read data sets from NGS bisulfite-sequencing projects of cell lines, fresh and pathological tissues are first p...
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Veröffentlicht in: | Nucleic acids research 2014-01, Vol.42 (Database issue), p.D53-D59 |
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creator | Geisen, Stefanie Barturen, Guillermo Alganza, Ángel M Hackenberg, Michael Oliver, José L |
description | The updated release of 'NGSmethDB' (http://bioinfo2.ugr.es/NGSmethDB) is a repository for single-base whole-genome methylome maps for the best-assembled eukaryotic genomes. Short-read data sets from NGS bisulfite-sequencing projects of cell lines, fresh and pathological tissues are first pre-processed and aligned to the corresponding reference genome, and then the cytosine methylation levels are profiled. One major improvement is the application of a unique bioinformatics protocol to all data sets, thereby assuring the comparability of all values with each other. We implemented stringent quality controls to minimize important error sources, such as sequencing errors, bisulfite failures, clonal reads or single nucleotide variants (SNVs). This leads to reliable and high-quality methylomes, all obtained under uniform settings. Another significant improvement is the detection in parallel of SNVs, which might be crucial for many downstream analyses (e.g. SNVs and differential-methylation relationships). A next-generation methylation browser allows fast and smooth scrolling and zooming, thus speeding data download/upload, at the same time requiring fewer server resources. Several data mining tools allow the comparison/retrieval of methylation levels in different tissues or genome regions. NGSmethDB methylomes are also available as native tracks through a UCSC hub, which allows comparison with a wide range of third-party annotations, in particular phenotype or disease annotations. |
doi_str_mv | 10.1093/nar/gkt1202 |
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Short-read data sets from NGS bisulfite-sequencing projects of cell lines, fresh and pathological tissues are first pre-processed and aligned to the corresponding reference genome, and then the cytosine methylation levels are profiled. One major improvement is the application of a unique bioinformatics protocol to all data sets, thereby assuring the comparability of all values with each other. We implemented stringent quality controls to minimize important error sources, such as sequencing errors, bisulfite failures, clonal reads or single nucleotide variants (SNVs). This leads to reliable and high-quality methylomes, all obtained under uniform settings. Another significant improvement is the detection in parallel of SNVs, which might be crucial for many downstream analyses (e.g. SNVs and differential-methylation relationships). A next-generation methylation browser allows fast and smooth scrolling and zooming, thus speeding data download/upload, at the same time requiring fewer server resources. Several data mining tools allow the comparison/retrieval of methylation levels in different tissues or genome regions. 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Published by Oxford University Press. 2013</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c447t-90bf7433dfa51c2514538e4376ab46d62b757b32a9b630c21843325c763dde7b3</citedby><cites>FETCH-LOGICAL-c447t-90bf7433dfa51c2514538e4376ab46d62b757b32a9b630c21843325c763dde7b3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3964946/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3964946/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,27901,27902,53766,53768</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/24271385$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Geisen, Stefanie</creatorcontrib><creatorcontrib>Barturen, Guillermo</creatorcontrib><creatorcontrib>Alganza, Ángel M</creatorcontrib><creatorcontrib>Hackenberg, Michael</creatorcontrib><creatorcontrib>Oliver, José L</creatorcontrib><title>NGSmethDB: an updated genome resource for high quality, single-cytosine resolution methylomes</title><title>Nucleic acids research</title><addtitle>Nucleic Acids Res</addtitle><description>The updated release of 'NGSmethDB' (http://bioinfo2.ugr.es/NGSmethDB) is a repository for single-base whole-genome methylome maps for the best-assembled eukaryotic genomes. 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A next-generation methylation browser allows fast and smooth scrolling and zooming, thus speeding data download/upload, at the same time requiring fewer server resources. Several data mining tools allow the comparison/retrieval of methylation levels in different tissues or genome regions. NGSmethDB methylomes are also available as native tracks through a UCSC hub, which allows comparison with a wide range of third-party annotations, in particular phenotype or disease annotations.</description><subject>Animals</subject><subject>Cell Line</subject><subject>Cytosine - metabolism</subject><subject>Databases, Nucleic Acid</subject><subject>DNA Methylation</subject><subject>Epigenesis, Genetic</subject><subject>Genetic Variation</subject><subject>Genome</subject><subject>Genomics</subject><subject>High-Throughput Nucleotide Sequencing - methods</subject><subject>High-Throughput Nucleotide Sequencing - standards</subject><subject>Humans</subject><subject>I. Nucleic acid sequence, structure and regulation</subject><subject>Internet</subject><subject>Mice</subject><subject>Sequence Alignment</subject><subject>Sequence Analysis, DNA - methods</subject><subject>Sequence Analysis, DNA - standards</subject><issn>0305-1048</issn><issn>1362-4962</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNpVkU1LxDAQhoMouq6evEuOglbzna0HQddPED2oRwlpmnarbbObpEL_vV12FT3NwDzzzMALwAFGpxil9KzV_qz8jJggsgFGmAqSsFSQTTBCFPEEIzbZAbshfCCEGeZsG-wQRiSmEz4C7093L42Ns-urc6hb2M1zHW0OS9u6xkJvg-u8sbBwHs6qcgYXna6r2J_AULVlbRPTRze0K7TuYuVauPT19bAf9sBWoetg99d1DN5ub16n98nj893D9PIxMYzJmKQoKySjNC80x4ZwzDidWEal0BkTuSCZ5DKjRKeZoMgQPBlgwo0UNM_tMBmDi5V33mWNzY1to9e1mvuq0b5XTlfq_6StZqp0X4qmgqVMDIKjtcC7RWdDVE0VjK1r3VrXBYVZiiQjTPIBPV6hxrsQvC1-z2CkloGoIRC1DmSgD_9-9sv-JEC_AQKTiS8</recordid><startdate>20140101</startdate><enddate>20140101</enddate><creator>Geisen, Stefanie</creator><creator>Barturen, Guillermo</creator><creator>Alganza, Ángel M</creator><creator>Hackenberg, Michael</creator><creator>Oliver, José L</creator><general>Oxford University Press</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20140101</creationdate><title>NGSmethDB: an updated genome resource for high quality, single-cytosine resolution methylomes</title><author>Geisen, Stefanie ; Barturen, Guillermo ; Alganza, Ángel M ; Hackenberg, Michael ; Oliver, José L</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c447t-90bf7433dfa51c2514538e4376ab46d62b757b32a9b630c21843325c763dde7b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Animals</topic><topic>Cell Line</topic><topic>Cytosine - metabolism</topic><topic>Databases, Nucleic Acid</topic><topic>DNA Methylation</topic><topic>Epigenesis, Genetic</topic><topic>Genetic Variation</topic><topic>Genome</topic><topic>Genomics</topic><topic>High-Throughput Nucleotide Sequencing - methods</topic><topic>High-Throughput Nucleotide Sequencing - standards</topic><topic>Humans</topic><topic>I. Nucleic acid sequence, structure and regulation</topic><topic>Internet</topic><topic>Mice</topic><topic>Sequence Alignment</topic><topic>Sequence Analysis, DNA - methods</topic><topic>Sequence Analysis, DNA - standards</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Geisen, Stefanie</creatorcontrib><creatorcontrib>Barturen, Guillermo</creatorcontrib><creatorcontrib>Alganza, Ángel M</creatorcontrib><creatorcontrib>Hackenberg, Michael</creatorcontrib><creatorcontrib>Oliver, José L</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Nucleic acids research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Geisen, Stefanie</au><au>Barturen, Guillermo</au><au>Alganza, Ángel M</au><au>Hackenberg, Michael</au><au>Oliver, José L</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>NGSmethDB: an updated genome resource for high quality, single-cytosine resolution methylomes</atitle><jtitle>Nucleic acids research</jtitle><addtitle>Nucleic Acids Res</addtitle><date>2014-01-01</date><risdate>2014</risdate><volume>42</volume><issue>Database issue</issue><spage>D53</spage><epage>D59</epage><pages>D53-D59</pages><issn>0305-1048</issn><eissn>1362-4962</eissn><abstract>The updated release of 'NGSmethDB' (http://bioinfo2.ugr.es/NGSmethDB) is a repository for single-base whole-genome methylome maps for the best-assembled eukaryotic genomes. Short-read data sets from NGS bisulfite-sequencing projects of cell lines, fresh and pathological tissues are first pre-processed and aligned to the corresponding reference genome, and then the cytosine methylation levels are profiled. One major improvement is the application of a unique bioinformatics protocol to all data sets, thereby assuring the comparability of all values with each other. We implemented stringent quality controls to minimize important error sources, such as sequencing errors, bisulfite failures, clonal reads or single nucleotide variants (SNVs). This leads to reliable and high-quality methylomes, all obtained under uniform settings. Another significant improvement is the detection in parallel of SNVs, which might be crucial for many downstream analyses (e.g. SNVs and differential-methylation relationships). A next-generation methylation browser allows fast and smooth scrolling and zooming, thus speeding data download/upload, at the same time requiring fewer server resources. Several data mining tools allow the comparison/retrieval of methylation levels in different tissues or genome regions. NGSmethDB methylomes are also available as native tracks through a UCSC hub, which allows comparison with a wide range of third-party annotations, in particular phenotype or disease annotations.</abstract><cop>England</cop><pub>Oxford University Press</pub><pmid>24271385</pmid><doi>10.1093/nar/gkt1202</doi><oa>free_for_read</oa></addata></record> |
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subjects | Animals Cell Line Cytosine - metabolism Databases, Nucleic Acid DNA Methylation Epigenesis, Genetic Genetic Variation Genome Genomics High-Throughput Nucleotide Sequencing - methods High-Throughput Nucleotide Sequencing - standards Humans I. Nucleic acid sequence, structure and regulation Internet Mice Sequence Alignment Sequence Analysis, DNA - methods Sequence Analysis, DNA - standards |
title | NGSmethDB: an updated genome resource for high quality, single-cytosine resolution methylomes |
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