Hi All,
I have around say 150 differentially expressed (DE) genes between 2 groups (control and treatment of a disease) by RNA-seq. My goal is to really shorten this list and find that few number of genes, which are of utmost significance which acts as a marker for this disease.
Now my problem is that there are so many ways out there to achieve this (read quite a lot of papers) and no one states it clearly. Can anyone suggest the best way to shortlist really significant (biologically and statistically) gene/genes between these groups?
Thank you, Rituriya.
•
written
by
Rituriya •
1 answer
There are many ways to determine if a set of genes are functionally related, and/or altered as group in response to a "disease", you can start with webgestalt or string. These tools may help you to understand/stablish networks between DE genes.
Log in to answer this question.
-
Differential Expression Contrast Interpretation
written by fnepo •
-
Proteomics differential expression in longitudinal data
written by fnepo •
-
Heatmap for visualizing the differentially expressed genes in RNA-seq data
written by KABILAN •
-
Statistically Comparing Two DiffEx Gene Sets To Discern Treatment Effect
written by James •
-
DESeq2 model design for 1 condition versus two grouped conditions
written by gatollefson •
-
Differentially expressed genes between Seurat objects
written by lic4010 •
-
Use DESeqDataSetFromMatrix from a matrix of normalized read counts
written by celia.escher •
-
How to create design matrix in edgeR
written by Björn •
-
Significance of overlap between multiple lists
written by gsmur •
-
Is There Any Paper That Compares/Combines Differentially Expressed Genes With Co-Expressed Genes?
written by Diwan
