I have scale and normalized data in excel. A column = genes, B - S columns = Tissue types.
- How can I perform PCA for my data; >To cluster similar Tissue types, >To cluster similar Gene groups
- -How can I generate heat map for this data; I used d3heatmap R package, but I do not know how to explain this statistically this because not sure what method is using this package i.e. Clustering method, scaling, etc.
The way my data looks like in Excel,
AGI Tissue Type 1 Tissue Type 2 Tissue Type 3 Tissue Type 4 Tissue Type 5 Tissue Type 6 Tissue Type 7 Tissue Type 8
A 1.457958966 1.082728155 1.421862008 1.282919309 1.365338194 1.825823721 1.442458653 1.301820193
B 0.215245986 0.232381653 0.206548478 0.203164578 0.476502255 0.178929005 0.2419442 0.381018497
C 0.297877541 0.313489112 0.251719576 0.272301642 0.354067746 0.326371147 0.268637474 0.344993509
E 1 D 1.113670056 0.878336899 1.467816289 1.099945097 0.841847105 1.296911268 1.04983679 1.20244969
F 1.236532232 1.297729828 1.225486185 1.308011803 1.148918493 1.229466152 1.232070028 1.286624981
I have genes A to BC (55 genes), 18 different Tissue types,
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WUSCHEL
1 answer
First get your data out of Excel by saving it as a TSV or CSV file, then read this into R with read.table() or read.csv(). Then:
- For PCA: A: PCA plot from read count matrix from RNA-Seq
- For heatmap with dendrogram: How to generate PCA plot and heatmaps in R
- For a complexheatmap with dendrogram: How to plot a heatmap with two different distance matrices for X and Y
Each of these functions will scale your data for you. In order to understand which distance (e.g. Euclidean, correlation, Canberra, etc.) and linkage (e.g. single, average, complete, Ward's, etc.) methods are being use, research the default values for each function. In R, if you want to see what the defaults are, then type the function name with a question mark pre-pended, e.g. ?heatmap.2 brings up the help pages ont the heatmap.2 function
Best of luck with it!
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