https://bioinfo.cipf.es/WODA/ 2026-04-05T17:05:56+0200 https://bioinfo.cipf.es/WODA/ https://bioinfo.cipf.es/WODA/lib/tpl/prsnl10/images/favicon.ico text/html 2021-02-24T19:26:09+0200 Anonymous (anonymous@undisclosed.example.com) https://bioinfo.cipf.es/WODA/doku.php/unsupervised.class/exercises/ej1?rev=1614191169&do=diff Online example * Go to the Babelomics page (<http://babelomics.bioinfo.cipf.es/>) and select the Clustering option from the Expression menu. * Press the online example and you will see how the parameters and form fields are now filled. As you can notice, this example is prepared to perform a clustering analysis on genes (rows) and conditions (columns) using the K-means algorithm with 5 sample-clusters and 15 gene-clusters. Here, the selected distance is Euclidean (square). text/html 2021-03-06T11:20:05+0200 Anonymous (anonymous@undisclosed.example.com) https://bioinfo.cipf.es/WODA/doku.php/unsupervised.class/exercises/ej1b?rev=1615026005&do=diff Clustering analysis for expression data in arthritis The etiology of rheumatoid arthritis is not known with certainty. In order to generate information that clarifies this point, a study of expression microarrays has been proposed, which will allow characterizing this disease at the molecular level and finding some key mechanisms that will improve its prevention and treatment. text/html 2019-03-02T08:52:30+0200 Anonymous (anonymous@undisclosed.example.com) https://bioinfo.cipf.es/WODA/doku.php/unsupervised.class/exercises/ej2?rev=1551513150&do=diff RNA-Seq data analysis: unsupervised classification or clustering Goal Detect homogenous groups of subjects according to their transcriptomic profile. Data We are studying a complex disease in which we know that a certain hormone has an important role. For them, we designed an experiment with RNA-Seq in mice with two groups: 6 wild type mice (WT) and 6 mice treated with T3 hormone. text/html 2019-03-02T09:42:51+0200 Anonymous (anonymous@undisclosed.example.com) https://bioinfo.cipf.es/WODA/doku.php/unsupervised.class/exercises/ej3?rev=1551516171&do=diff Clustering analysis on the group differentially expressed genes Goal To detect common expression patterns in samples and genes on the results of differential expression analysis that we had previously obtained, in the case-control experiment where we used RNA-Seq in mice, and in which we were interested in detecting genes differentially expressed between these 2 groups: wild type (WT) and treated with hormone T3. text/html 2019-03-03T14:16:12+0200 Anonymous (anonymous@undisclosed.example.com) https://bioinfo.cipf.es/WODA/doku.php/unsupervised.class/exercises/ej4?rev=1551618972&do=diff RNA-Seq data from Breast Invasive Carcinoma (BRCA) 1. Open this file and explore the content: [tcga_rnaseq.txt]. Description: * RNA-Seq data of BRCA samples taken from The Cancer Genome Atlas (TCGA) data portal. (<http://cancergenome.nih.gov/>) * Contains 10 normal samples, 20 tumor samples with 2 subtypes (Basal-like and Her2-enriched).