Data normalization and new metrics

Normalize first!

wt_quant_log2cpm = my_norm(wt_merged, out_type="cpm", filter="log2", norm_type="quant")
## Pull out the counts for ease
wt_quant = wt_quant_log2cpm$counts
## Lets graph the raw data right quick
wt_quant_cor = my_corheat(wt_quant, wt_colors, design=wt_data_design)

wt_quant_cor = my_corheat(wt_quant, wt_colors, design=wt_data_design, method="spearman")

wt_quant_smc = my_smc(wt_quant, wt_colors)

wt_quant_dis = my_disheat(wt_quant, wt_colors, design=wt_data_design)

wt_quant_smd = my_smd(wt_quant, wt_colors)

wt_quant_pca = my_pca(wt_quant, wt_colors, wt_data_design)

## [1] 1 1 2 2 3 3

## Loading required package: proto

wt_quant_pca

Given those metrics, lets set up a quantile normalized data set for future analyses

## This is suitable for passing to voom
wt_quant_raw = my_norm(wt_merged, out_type="raw", filter="raw", norm_type="quant")
wt_quant_counts = wt_quant_raw$counts
## While this may be used with voomMod
wt_quant_log2cpm = my_norm(wt_merged, out_type="cpm", filter="log2", norm_type="quant")
wt_quant_log2cpm_counts = wt_quant_log2cpm$counts

Save data

yay!