Carmen-Proteomics: Difference between revisions

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Preliminary results of GSEA runs by Amanda Larracuente (Qiu Lab)
Preliminary results of GSEA runs by Amanda Larracuente (Qiu Lab)
* Methods
* Methods
# Rank identified proteins by t-statistics, which is a measure of difference between WT and KO mice (3 individuals each). Most genes don't change, with t close to zero. t << 0 suggests down-regulation in KO mice relative to WT mice, and t >> 0 suggests up-regulation. (Need to make sure of the sign)
# Rank identified proteins by t-statistics, which is a measure of difference between WT and KO mice (3 individuals each). Most genes don't change, with t close to zero. t << 0 suggests down-regulation in KO mice relative to WT mice, and t >> 0 suggests up-regulation. (Could be the other way around. Need to confirm)
# Download mice gene sets from a web resource
# Download mice gene sets from a web resource
# Run GSEA by Broad Institute
# Run GSEA by Broad Institute
* [http://diverge.hunter.cuny.edu/~weigang/carmen-proteomics/mice.GseaPreranked.1490136739893 | Results using mice gene set with GO annotations]
* [http://diverge.hunter.cuny.edu/~weigang/carmen-proteomics/mice.GseaPreranked.1490136739893 Results using mice gene set with GO annotations]
* [http://diverge.hunter.cuny.edu/~weigang/carmen-proteomics/mice.GseaPreranked.1490138021974 Results using mice gene set w/o GO annotations]
* [http://diverge.hunter.cuny.edu/~weigang/carmen-proteomics/mice.GseaPreranked.1490138021974 Results using mice gene set w/o GO annotations]

Latest revision as of 14:06, 22 March 2017

Tuesday, March 21, 2017

Preliminary results of GSEA runs by Amanda Larracuente (Qiu Lab)

  • Methods
  1. Rank identified proteins by t-statistics, which is a measure of difference between WT and KO mice (3 individuals each). Most genes don't change, with t close to zero. t << 0 suggests down-regulation in KO mice relative to WT mice, and t >> 0 suggests up-regulation. (Could be the other way around. Need to confirm)
  2. Download mice gene sets from a web resource
  3. Run GSEA by Broad Institute