Tutorial OncodriveClust
#### STEPS [1. Select your data](tutorial-oncodriveclust#select-your-data)
[2. Select priorizitation parameters](tutorial-oncodriveclust#select-priorizitation-parameters)
[3. Fill information job](tutorial-oncodriveclust#fill-information-job)
[4. Press *Launch job* button](tutorial-oncodriveclust#press-launch-job-button)
#### OUTPUT - [Input parameters](tutorial-oncodriveclust#input-parameters) - [Output files](tutorial-oncodriveclust#output-files)
#### CITE
#####Input data
- Input data should be a matrix upload as the data type VCF 4.0. See data types [here](Data Types).
#####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.
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
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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