[BiO BB] gene expression software for mere biologists?

Sole Acha, Xavi x.sole at iconcologia.net
Mon Dec 22 14:51:05 EST 2008


This is a difficult problem to solve. Maybe you can have a look a these three suites, I believe they may be the most complete ones you can find elsewhere.

- dChip, from Harvard (http://biosun1.harvard.edu/complab/dchip/)
- TM4 Suite from TIGR (http://www.tm4.org/)
- GEPAS (http://gepas.bioinfo.cipf.es/)

Obviously there is a trade-off between versatility and ease-of-use. With R (and Bioconductor), you will always be able to write your own procedures and perform your own analyses. Maybe it should be worth trying to teach R (and a bit of basic algorithmics theory) to your biologists. But that depends on how eager they are to learn.

Hope this helps a little.

Xavier Solé Acha
Unitat de Bioestadística i Bioinformàtica // Biostatistics and Bioinformatics Unit
Institut Català d'Oncologia // Catalan Institute of Oncology
Av. Gran Via s/n km 2,7
08907 L'Hospitalet de Llobregat, Barcelona, Spain.
Phone: +34 93 260 71 86 / +34 93 335 90 11 (ext. 3189)
Fax: +34 93 260 71 88
E-mail: x.sole at iconcologia.net

 

-----Mensaje original-----
De: bbb-bounces at bioinformatics.org [mailto:bbb-bounces at bioinformatics.org] En nombre de Harry Mangalam
Enviado el: dilluns, 22 / desembre / 2008 19:40
Para: BBB
Asunto: [BiO BB] gene expression software for mere biologists?

Hi All,

This may be a difficult query for this group to answer as the readership is canted heavily in the geek direction, but what gene expression software are you and your users relying on for gene expression and pathway analysis?

I tilt heavily towards R/Bioconductor and other free software, so I'm aware of the advantages of it, but we have non-commandline tool researchers who are in need of tools they can use to examine the results of gene expression studies.

This is something of a no-win - those tools that are very easy to use tend to hide the very complexity that the user has to address, and so the 'ease of use' / 'ease of thought' tends to weaken an already iffy analysis.

That said, are there tools (commercial or free) that provide fairly good tradeoffs between power and ease of use for a non-geek biologist user.  ie runs on Mac & Windows and is mostly GUI? (If you have experience in introducing such users to R, I'd also be interested in your experiences).

Due to some aggressive pushing from the local SAS consulting group, we are in the startup phase of a campus-wide, 1 year trial of JMP/Genomics.  JMP is a fairly cheap, nicely designed, multiplatform GUI stats package from SAS.  The Genomics part tho is an expensive add-on that runs only on Windows and depends on an optional, even more expensive Pathways package from InGenuity.  The local research community does not have a problem paying for such software if it truly does work easily and well.  If you have used it and have an opinion or evaluation, I'd love to hear from you via email or phone.

Harry

--
Harry Mangalam - Research Computing, NACS, E2148, Engineering Gateway, UC Irvine 92697  949 824-0084(o), 949 285-4487(c)
---
Good judgment comes from experience;
Experience comes from bad judgment. [F. Brooks.]

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