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| || 1. Using tumor series to extract relevant genes || Open website: http://hgserver1.amc.nl/cgi-bin/r2/main.cgi || || | || 1. Research into childhood tumors. Array data analyzed using web-based R2. Biologists use tumor series to extract relevant genes. These are manipulated in tumor cell-lines using siRna and studied in time-series || Open website: http://hgserver1.amc.nl/cgi-bin/r2/main.cgi || || |
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|| 3. R2 portal shows; menu reflects all possibilities, || Click Timeseries || || || 4. Panel provides you with three choices: __Explore timeseries__: single gene in series; __TableBuilder__: Find genes in series based on tresholds; __Multiplo__: Limma statistics applied to replicates. Availability of other datasets under dropdown || Select TableBuilder || Keep default selection set_hg_mix, upcoming improved naming of these sets || || 5. || Choose cellline imr || || || 6. || Choose Notch1 || || || || || || |
|| 3. R2 portal shows; menu reflects all possibilities, lots of data (>17,000 arrays), clinical data, all types of stat analysis || Type MYCN || || || 4. Note || Click timeseries || || || 5. Panel provides you with three choices: __Explore timeseries__: single gene in series; __TableBuilder__: Find genes in series based on tresholds; __Multiplo__: Limma statistics applied to replicates. Availability of other datasets under dropdown || Select TableBuilder || Keep default selection set_hg_mix, upcoming improved naming of these sets || || 6. Tree reflects the cell-lines || Choose cellline imr || || || 7. Under cell-line the manipulated genes and type of manipulation; multiple selection possible || Choose Notch1 || Multiple selection is tricky! || || 8. There are several cut-offs and tresholds to set, hugoonce, guarantees only one hugo per probeset; ||Click hugo || || |
R2 and Cytoscape: Inferring gene targets by graph based integration and analysis of molecular biological data
Piet Molenaar
Academic Medical Center, University of Amsterdam, the Netherlands
Biological Use Case: In our lab we're doing research into the molecular networks involved in childhood cancer. To this end we've profiled a large set of childhood tumors. Guided by biological questions we set out to develop a web-based array analysis platform called R2. In order to make an educated guess what genes to test that appeared of importance in this analysis we needed additional network analysis.
Recipe
Cytoscape version: 2.4 - 2.6
Plugins to Load: R2Plugin, [http://chianti.ucsd.edu/cyto_web/plugins/index.php BiNGO], [http://baderlab.org/Software/NetMatch NetMatch]
GUI steps:
Story |
Action |
Remarks |
1. Research into childhood tumors. Array data analyzed using web-based R2. Biologists use tumor series to extract relevant genes. These are manipulated in tumor cell-lines using siRna and studied in time-series |
Open website: http://hgserver1.amc.nl/cgi-bin/r2/main.cgi |
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2. Access and datasets input still restricted; will change. For logon mail r2-support_at_amc.uva.nl |
Logon with: un pw |
If problem switch to ppt (Piet: todo provide restricted access logon) |
3. R2 portal shows; menu reflects all possibilities, lots of data (>17,000 arrays), clinical data, all types of stat analysis |
Type MYCN |
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4. Note |
Click timeseries |
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5. Panel provides you with three choices: Explore timeseries: single gene in series; TableBuilder: Find genes in series based on tresholds; Multiplo: Limma statistics applied to replicates. Availability of other datasets under dropdown |
Select TableBuilder |
Keep default selection set_hg_mix, upcoming improved naming of these sets |
6. Tree reflects the cell-lines |
Choose cellline imr |
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7. Under cell-line the manipulated genes and type of manipulation; multiple selection possible |
Choose Notch1 |
Multiple selection is tricky! |
8. There are several cut-offs and tresholds to set, hugoonce, guarantees only one hugo per probeset; |
Click hugo |
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Data Files: Supplied via website R2
Presentation: [attachment:PietMolenaar_ICSB_23_8_08.ppt R2AndCytoscape_PPT]
Webstart: Time permitting
Video: Time permitting