Tutorial OncodriveClust

luzgaral edited this page Jan 31, 2015 · 5 revisions
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INPUT


STEPS

1. Select your data
2. Select priorizitation parameters
3. Fill information job
4. Press Launch job button


OUTPUT


CITE





INPUT

Input data
  • Input data should be a matrix upload as the data type VCF 4.0. See data types here.
Online example

Here you can load a small dataset from our server. You can use them to run this example and see how the tool works. Click on the links to load the data: BRCA cancer set from TCGA.


STEPS

Select your data

First step is to select your data to analyze.

Select priorizitation parameters
  • Select Human Genome version: GRCh37 or GRCh38
Fill information job
  • Select the output folder
  • Choose a job name
  • Specify a description for the job if desired.
Press Launch job button

Press launch button and wait until the results is finished. A normal job may last approximately few minutes but the time may vary depending on the size of data. See the state of your job by clicking the jobs button in the top right at the panel menu. A box will appear at the right of the web browser with all your jobs. When the analysis is finished, you will see the label "Ready". Then, click on it and you will be redirected to the results page.


OUTPUT

Input parameters

In this section you will find a reminder of the parameters or settings you have used to run the analysis.

Output files

Significant results

Statistical information for significant genes:

GENE    CGC GENE_LEN    GENE_NUM_MUTS   MUTS_IN_CLUST   NUM_CLUSTERS    GENE_SCORE  ZSCORE  PVALUE  QVALUE
SIRPG       388 72  72  2   1.0 5.54615384615   1.46010950776e-08   2.27128145651e-08
C20orf96        364 7   7   1   1.0 5.54615384615   1.46010950776e-08   2.27128145651e-08
SIRPD       199 43  43  1   1.0 5.54615384615   1.46010950776e-08   2.27128145651e-08
NRSN2       205 5   5   1   1.0 5.54615384615   1.46010950776e-08   2.27128145651e-08
TBC1D20     404 3   3   1   1.0 5.54615384615   1.46010950776e-08   2.27128145651e-08
DEFB129     184 6   6   1   1.0 5.54615384615   1.46010950776e-08   2.27128145651e-08
SCRT2       308 7   7   1   1.0 5.54615384615   1.46010950776e-08   2.27128145651e-08
DEFB127     100 47  47  2   1.0 5.54615384615   1.46010950776e-08   2.27128145651e-08
SRXN1       138 3   3   1   1.0 5.54615384615   1.46010950776e-08   2.27128145651e-08
RAD21L1     557 77  76  3   0.987012987013  5.44625374625   2.57208688064e-08   3.6009216329e-08
DEFB128     94  36  35  1   0.972222222222  5.33247863248   4.84405862189e-08   6.16516551877e-08
TCF15       200 33  32  1   0.969696969697  5.31305361305   5.39016521274e-08   6.28852608152e-08
SIRPB1      399 157 157 7   0.917584836522  4.91219105017   4.50321147603e-07   4.84961235881e-07
DEFB132     96  3   3   1   0.784521187523  3.88862451941   5.04069720141e-05   5.04069720141e-05


CITE

Tamborero D, Gonzalez-Perez A, Lopez-Bigas N. OncodriveCLUST: exploiting the positional clustering of somatic mutations to identify cancer genes. Bioinformatics. 2013 Sep 15;29(18):2238-44. - Bioinformatics - PubMed - Site


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