Athurva Gore/LabNotes/ExomeReseq/2009-5-13: Difference between revisions

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>Ajgore
(New page: =iPS Cancer?= * Obtained Illumina Array data from Dr. Zhang * Used SAM and DAVID to try and identify GO Terms in differentially expressed genes. * Say we want a desired FDR of 15% or lower...)
 
>Ajgore
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* Should help find any genes that do not match normal Fibroblasts or hESC in iPS cells.
* Should help find any genes that do not match normal Fibroblasts or hESC in iPS cells.
* Should help find some new behavior.
* Should help find some new behavior.
==Procedure==
* First, run SAM on Illumina sequencing data for just iPS and hESC.
* Extract differentially expressed genes such that the FDR is 0.05
** Turned out to be a delta of 1.7 with 4365 differentially expressed genes.
* Extracted data for just this gene subset from Illumina data, and only for FIBROBLASTS and IPS.
** Saved file in NewMethod folder as csv
* Imported into R, ran SAM again.

Revision as of 22:41, 13 May 2009

iPS Cancer?

  • Obtained Illumina Array data from Dr. Zhang
  • Used SAM and DAVID to try and identify GO Terms in differentially expressed genes.
  • Say we want a desired FDR of 15% or lower; since we are just doing preliminary.
  • SAM's multiclass feature is not useful here; it will call everything that is fibroblast-only "significant," leading to numbers that are far too large.

Very Lenient

  • Very lenient analysis results in a large amount of GO Terms and GO Clusters.
  • Delta of 2.3 was used for IPS_HESC
  • Delta of 0.1 (very low, since figured a lot of genes would need to be called as "not similar")
  • Will upload DAVID results to Wiki.
  • Lots of very interesting GO terms and GO clusters
  • However, inspection of several reveals that these values may be too lenient. Lots of things are called as significant that are not very.

Very Stringent

  • Limited ESC_IPS differences to 475, limited GO differences to 250.
  • In this case, only 3 or 4 clusters were obtained at all (only 23 diff. expressed genes)
  • Most of them have very low scores...probably too stringent here

New Method

  • It seems SAM has issues finding differences between fibroblasts and IPS that are meaningful
  • Because so many genes are differentially expressed already, very hard to choose a proper delta value.
    • FDR is predicted to be very high.
  • Instead, will find differentially expressed genes between IPS and HESC first.
    • Only look at these in Fibroblasts, then run SAM!
  • Should help find any genes that do not match normal Fibroblasts or hESC in iPS cells.
  • Should help find some new behavior.

Procedure

  • First, run SAM on Illumina sequencing data for just iPS and hESC.
  • Extract differentially expressed genes such that the FDR is 0.05
    • Turned out to be a delta of 1.7 with 4365 differentially expressed genes.
  • Extracted data for just this gene subset from Illumina data, and only for FIBROBLASTS and IPS.
    • Saved file in NewMethod folder as csv
  • Imported into R, ran SAM again.