- Compare ASCA proteins (high loadings) with hierarchical cluster (differentially clustered) proteins
- make raw abundance line plots facetted by protein
- examine if GO enrichment changes when ASCA and cluster proteins are combined
- Determine how time is factored into the cluster
- preform a time dependent cluster: TSclust: An R Package for Time Series Clustering?
- Determine if the permutation test with ASCA tests needs to be improved for the high loadings proteins to be considered highly influential
- Redo BLAST of CHOYP proteins to 2018 Uniprot database
- Begin identifying and locating data files that we need to deposit in public protein repository (i.e. ProteomeXchange and PeptideAtlas)
- need to regenerate ‘table_blastout_gigatonpep-uniprot’
- need fasta file of the peptides ID’d by mass spec
- make a simplified supplementary table containing CHOYP IDs, UniProt Accessions, e.val, Protein names, Gene names
- Can modify current datasheet to get this info as well
- Redo NMDS with two temps
- Remove day 0 and redo clustering
- Protein quantification comparisons between silos
- Protein abundance heatmaps with enrichment tags
- )I could also make these heatmaps with the protein names.)
- Revigo enrichment visuals (all proteins)
- DAVID gene enrichment (all proteins)
- Played around with Metboanalyst a lot, but haven’t been able to get any meaningful information from it
- Added basic statistical calculations to the original ABACUS data sheet although it wasn’t/hasn’t been informative because of the large number of proteins.
- (This is why clustering was pursued- to parse out unique proteins.)
Question: Does temperature influence the proteome of larval C. gigas, and if so, how?
- Do we need to explain we did 2 x 4 treatments, or just say we did 1 x 2 treatments?
- Do we have survival data for other silos to compare to silo 2, 3, and 9?
- Can we rule out silo 2 as an anomaly or should we include it?