SAM timecourse or what else ?
1
0
Entering edit mode
@davide-valentini-2218
Last seen 10.3 years ago
Hi to all, I have a dataset of 5 patients each one taken in 4 different times gene P1-T1 P1-T2 P1-T3 P1-T4 P2-T1 P2-T2 ... AAA 42 22 232 ... ... ... ... BBB 33 76 200 ... ... ... ... CCC 123 22 11 ... ... ... ... ... ... I'm mostly interested to the evaluate the change in gene expression over time, for this I was thinking to use the "quantitative" option in samr package, but I'm also curious about "One class timecourse" (I know that is not in BioC but maybe someone already used it). I don't find any examples in the documentation, and I don't know IF and how to proceed. Any help ? :) Secondly I'm also interested to group the patients with the same trends. So my question also is: Do you have some suggestions about what technique (or packages) to use for BOTH this tasks ? Thanks in advance to all, and sorry if part of the question is not strictly regarding BioConductor. Regards Davide -- Davide Valentini Postdoc - Biostatistician Department of Medical Epidemiology and Biostatistic Karolinska Institute Box 281 SE-171 77 Stockholm SWEDEN Tel: +46-8-524 82294 Fax: +46-8-31 4975
• 951 views
ADD COMMENT
0
Entering edit mode
Ana Conesa ▴ 130
@ana-conesa-2246
Last seen 10.3 years ago
Hi Davide You could use the maSigPro package for this. Time is treated quantitatively and with a little modification in the default created design, you can find those genes whith an homogeneous pattern across patients considering some intra-patient dependency. I am enclosing you a little script on how to proceed in this case, taken either a quadratic and cubic regression model. Hope this helps Ana ------------------------------------------- Ana Conesa, PhD Bioinformatics Department Centro de Investigaci?n Pr?ncipe Felipe Avda. Autopista Saler 16 46013 Valencia Spain http://bioinfo.cipf.es =========================================== CAMDA2007 Conference @ CIPF http://camda.bioinfo.cipf.es =========================================== > > >---- Mensaje Original ---- >De: Davide.Valentini at ki.se >Para: bioconductor at stat.math.ethz.ch >Asunto: RE: [BioC] SAM timecourse or what else ? >Fecha: Thu, 09 Aug 2007 10:44:33 +0200 > >> >> >>Hi to all, >> >>I have a dataset of 5 patients each one taken in 4 different times >> >>gene P1-T1 P1-T2 P1-T3 P1-T4 P2-T1 P2-T2 ... >> >>AAA 42 22 232 ... ... ... ... >>BBB 33 76 200 ... ... ... ... >>CCC 123 22 11 ... ... ... ... >>... ... >> >>I'm mostly interested to the evaluate the change in gene expression >over >>time, for this I was thinking to use the "quantitative" option in >samr >>package, but I'm also curious about "One class timecourse" (I know >that >>is not in BioC but maybe someone already used it). I don't find any >>examples in the documentation, and I don't know IF and how to >proceed. >>Any help ? :) >>Secondly I'm also interested to group the patients with the same >trends. >>So my question also is: Do you have some suggestions about what >>technique (or packages) to use for BOTH this tasks ? >> >>Thanks in advance to all, and sorry if part of the question is not >>strictly regarding BioConductor. >>Regards >> >>Davide >> >> >>-- >>Davide Valentini >>Postdoc - Biostatistician >>Department of Medical Epidemiology and Biostatistic >>Karolinska Institute >>Box 281 >>SE-171 77 Stockholm >>SWEDEN >>Tel: +46-8-524 82294 >>Fax: +46-8-31 4975 >> >>_______________________________________________ >>Bioconductor mailing list >>Bioconductor at stat.math.ethz.ch >>https://stat.ethz.ch/mailman/listinfo/bioconductor >>Search the archives: http://news.gmane.org/gmane.science.biology.inf >ormatics.conductor >> -------------- next part -------------- An embedded and charset-unspecified text was scrubbed... Name: patients.txt Url: https://stat.ethz.ch/pipermail/bioconductor/attachments/20070809/ 1586d5f0/attachment.txt
ADD COMMENT

Login before adding your answer.

Traffic: 494 users visited in the last hour
Help About
FAQ
Access RSS
API
Stats

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.

Powered by the version 2.3.6