{"id":1560,"date":"2016-06-20T07:53:28","date_gmt":"2016-06-20T05:53:28","guid":{"rendered":"http:\/\/bioinfo2.ugr.es\/NGSmethDB\/?page_id=1560"},"modified":"2016-09-11T11:06:34","modified_gmt":"2016-09-11T09:06:34","slug":"tools","status":"publish","type":"page","link":"https:\/\/bioinfo2.ugr.es\/NGSmethDB\/tools\/","title":{"rendered":"Working examples"},"content":{"rendered":"

{{How to cite NGSmethDB}}<\/h4>\n

Retrieving and analyzing NGSmethDB<\/em> data through UCSC track hubs and the Galaxy platform<\/h3>\n

We provide here some examples for retrieving NGSmethDB <\/em>data from UCSC Table Browser<\/a> and Data Integrator<\/a> and analyzing them in the Galaxy platform<\/a>. One of the ways in which NGSmethDB<\/em> data are distributed to the community is through standard track hubs, <\/a>which can be then uploaded into the main genome platforms, as UCSC<\/a> (Kent et al., 2002) or ENSEMBL<\/a> (Yates et al., 2016) genome browsers, where they can be easily browsed in the form of genome-wide methylation maps. In addition, numerical data in tabular form can be easily retrieved to the local computer through the standard tools built in these platforms (UCSC Table Browser<\/a> or Data Integrator<\/a>) or sent to other software platforms (Galaxy<\/a> (Afgan et al., 2016), GREAT<\/a> \u00a0(McLean et al., 2010) or GenomeSpace<\/a> (Qu et al., 2016)) for downstream analyses. We describe below some working examples using these tools to retrieve NGSmethDB<\/em> numerical data, as well some Galaxy workflows<\/a> to carry out some simple tasks.<\/p>\n

    \n
  1. Retrieve a list of methylation levels at single cytosines for a given tissue in a particular gene, genome region, chromosome or entire genome<\/a><\/li>\n
  2. Retrieve a list of differentially methylated cytosines (DMCs) for a given tissue in a particular gene, genome region, chromosome or entire genome<\/a><\/li>\n
  3. Compare the cytosine methylation levels in a set of tissue samples from the same or different individuals<\/a><\/li>\n
  4. Average methylation in the genes from a given region<\/a><\/li>\n<\/ol>\n

    Note<\/strong>: For examples of retrieving NGSmethDB<\/em> data using programmatic and HTTP access see the NGSmethDB Manual<\/a>.<\/p>\n

    References<\/h3>\n

    Afgan, E., Baker, D., van den Beek, M., Blankenberg, D., Bouvier, D., \u010cech, M., \u2026 Goecks, J. (2016). The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2016 update. Nucleic Acids Research<\/em>, gkw343. http:\/\/doi.org\/10.1093\/nar\/gkw343<\/p>\n

    Kent, W. J., Sugnet, C. W., Furey, T. S., Roskin, K. M., Pringle, T. H., Zahler, A. M., & Haussler,\u00a0 a. D. (2002). The Human Genome Browser at UCSC. Genome Research<\/em>, 12<\/em>(6), 996\u20131006. http:\/\/doi.org\/10.1101\/gr.229102<\/p>\n

    McLean, C. Y., Bristor, D., Hiller, M., Clarke, S. L., Schaar, B. T., Lowe, C. B., \u2026 Bejerano, G. (2010). GREAT improves functional interpretation of cis-regulatory regions. Nature Biotechnology<\/em>, 28<\/em>(5), 495\u2013501. http:\/\/doi.org\/10.1038\/nbt.1630<\/p>\n

    Qu, K., Garamszegi, S., Wu, F., Thorvaldsdottir, H., Liefeld, T., Ocana, M., \u2026 Mesirov, J. P. (2016). Integrative genomic analysis by interoperation of bioinformatics tools in GenomeSpace. Nature Methods<\/em>, 13<\/em>(3), 245\u2013247. http:\/\/doi.org\/10.1038\/nmeth.3732<\/p>\n

    Yates, A., Akanni, W., Amode, M. R., Barrell, D., Billis, K., Carvalho-Silva, D., \u2026 Flicek, P. (2016). Ensembl 2016. Nucleic Acids Research<\/em>, 44<\/em>(D1), D710\u20136. http:\/\/doi.org\/10.1093\/nar\/gkv1157<\/p>\n

    [[How to cite NGSmethDB]]<\/p>\n