I have gene expression data from different conditions from different studies. Instead of using the actual TPM values for Pearson Correlation coefficient (PCC) calculation, I have decided to use Fold change values from different studies to eliminate biases from different studies. My question is whether using these raw fold change values for identifying co-expressed genes is a correct way to do it or should perform quantile normalization on these fold change values before using them for PCC calculation? (Note: Distribution of fold change values in different studies is quite different)
Unconfigured Ad
Collapse
X
Latest Articles
Collapse
-
by SEQadmin2
Tumors contain complex mixtures of cell populations that evolve in response to treatment and host-specific factors. Tissue biopsies provide only static snapshots of a tumor’s state. But what if we could follow that evolution over time using a minimally invasive technique?
Liquid biopsies can detect tumor-derived material circulating in the bloodstream, providing a way to study treatment response, detect emerging resistance, and discover new biomarkers. Circulating...-
Channel: Articles
10-14-2026, 09:55 AM -
ad_right_rmr
Collapse
News
Collapse
| Topics | Statistics | Last Post | ||
|---|---|---|---|---|
|
Genome Sequencing Reveals Large, Repeat-Rich DNA in Trapdoor Spider Named for Stephen Colbert
by SEQadmin2
Started by SEQadmin2, 10-28-2026, 09:57 AM
|
0 responses
21 views
0 reactions
|
Last Post
by SEQadmin2
10-28-2026, 09:57 AM
|
||
|
Started by SEQadmin2, 10-28-2026, 09:51 AM
|
0 responses
14 views
0 reactions
|
Last Post
by SEQadmin2
10-28-2026, 09:51 AM
|
||
|
Started by SEQadmin2, 10-22-2026, 11:13 AM
|
0 responses
67 views
0 reactions
|
Last Post
by SEQadmin2
10-22-2026, 11:13 AM
|
||
|
Started by SEQadmin2, 10-22-2026, 10:48 AM
|
0 responses
47 views
0 reactions
|
Last Post
by SEQadmin2
10-22-2026, 10:48 AM
|