Friday. Mar. 1, 2019 oyster proteomics network analysis
Expanding protein list to bring into network analysis
Instead of using ASCA selected proteins, which tend to not show much change due to temperature, I’m going to try selected proteins based on their log foldchange or ChiSq. pvalues from the same-day foldchange analysis
Determining a log foldchange or pvalue cutoff for selecting proteins
Numbers below came from code: ASCA_proteinNetworkAnalysis_withGO.R lines 260-308
- Using same-day folchange and pvalues between temperatures, I found - 2224 proteins have a magnitude log2foldchange >=1 (which is 2x or greater foldchange) - 165 proteins have magnitude logfoldchange >=2 (4x) - 128 proteins have an adj.pvalue <= 0.05 - 153 proteins have an adj.pvalue <= 0.1
conclusions: I think it makes the most sense to use the adj.pvalue cutoff instead of log2foldchange, so I’m going to go with and adj.pvalue cutoff of 0.1.
Comparing ChiSq. pvalue cutoff protein selection with ASCA protein selection
Numbers below came from code: ASCA_proteinNetworkAnalysis_withGO.R lines 310-316
- 330 ASCA selected proteins map to uniprot
- 153 ChiSq. pvalue selected proteins map to uniprot
- 50 proteins overlap between the two methods with 230 unique to ASCA and 103 unique to ChiSq. pvalue cutoff.
- Using ASCA to select proteins provides a larger list of proteins, but the majority aren’t affected by temperature.
- So when we are looking for temperature effects on protein abundance in the networks, it’s not apparent in most of these proteins.
- I think it’s most relevant to use the same-day comparison adj.Chisq pvalue <= 0.1 threshold for selecting proteins and use their log foldchange to color the nodes in the network.
- Need to:
- make a cleaner version of the R script to make new node and edge attribute files
- make a new cytoscape network