Jenna Reed
2/13/18
mut/WT log2 500/1000 = 0.5 Anything less than 1 is negative
DESeq2 >>> run htseq-count data with features After doing a DESeq2 run, two files will appear in the history First one is tabular. Download that, open in Text Wrangler, then copy and paste that in excel Second one is a pdf. Download and open that to see data visualizations
54 & 55 >>> DESeq2 for "Female_MUTvWT" 56 & 57 >>> DESeq2 for "Male_MUTvWT" 58 & 59 >>> DESeq2 for "MUT_MALEvFEMALE" 60 & 61 >>> DESeq2 for "WT_MALEvFEMALE" 62 & 63 >>> DESeq2 for "MUT_v_WT"
Research method for today: look at what genes are significant in each dataset and see where there is overlap between datasets
In excel sheet: DESeq2 data for all 5 comparisons P-value < 0.05 highlighted in yellow P-adjusted <0.05 highlighted in green List of just the p-adjusted <0.05 genes for all 5 comparisons together
General observations:
- of genes with p-adj < 0.05
Female_MUTvWT: 72
Sphk2 >>> p-adj is less than 0.05 for both MUT_MALEvFEMALE and WT_MALEvFEMALE Sphingosine Kinase 2 Paralog with Sphk1, which codes for the other enzyme that has the same function Encodes for an enzyme that catalyzes the phosphorylation of sphingosine into sphingosine 1-phosphate sphingosine 1-phosphate = important in cell migration, proliferation, apoptosis Implicated in some cancers (breast cancer proliferation, chemoresistance) Related pathways: Calcium signaling pathway (could be connection to CMT2D), Metabolism
Tsix >>> p-adj is less than 0.05 for both MUT_MALEvFEMALE and WT_MALEvFEMALE
