Question: If I have a ran-seq data of disease A and also rna-seq for disease B on the same platform and If i extracted DEGs from both diseases and find common DEGs; is this analysis ok?
0
gravatar for Md. Al - Mustanjid
5 weeks ago by
Dhaka, Bangladesh.
Md. Al - Mustanjid30 wrote:

If I have a ran-seq data of disease A and also rna-seq for disease B on the same platform and If i extracted DEGs from both diseases and find common DEGs; is this analysis ok?

rna-seq degs • 151 views
ADD COMMENTlink modified 4 weeks ago by Kevin Blighe63k • written 5 weeks ago by Md. Al - Mustanjid30
1
gravatar for Kevin Blighe
4 weeks ago by
Kevin Blighe63k
Kevin Blighe63k wrote:

Yes; however, the way that you report on the results (the overlapping / common genes) is important. You could 'formalise' the overlap by doing a meta analysis.

Also, if all samples were profiled together in the same experiment, it would be better to process and normalise these together, and also perform the differential expression comparisons.

Kevin

ADD COMMENTlink modified 4 weeks ago • written 4 weeks ago by Kevin Blighe63k

Thank you a lot Kevin. It was quite impossible to conduct my research work without your help. Your suggestions make my study path more clear. I am moving forward to ran-seq analysis, as I am a beginner I have a hard a lot about meta-analysis. But I don't have proper knowledge on this. could you please suggest me any source or something like that. It will be more helpful for my learning process. Thanks again.

ADD REPLYlink written 4 weeks ago by Md. Al - Mustanjid30
1

Sure, but, are these diseases completely different or are they sub-types of the same disease? It is not a problem to simply compare the 2 lists of the genes that are statistically significant. What do you ultimately hope to infer from this particular part of the analysis?

For a simple meta-analysis, I found this program easy to use: https://www.bioconductor.org/packages/release/bioc/html/GenRank.html

You could also compare the fold-changes of all genes in a scatter plot, i.e., log2FC Disease A (x-axis) versus log2FC Disease B (y-axis), and derive a Pearson correlation co-efficient and p-value for this.

ADD REPLYlink modified 4 weeks ago • written 4 weeks ago by Kevin Blighe63k

Thanks Kevin. Disease A is a subtype of disease B. I want to detect molecular insights and signatures between these diseases from DEGs shared in both diseases from Systems biology perspective. I will check out the package.

ADD REPLYlink written 4 weeks ago by Md. Al - Mustanjid30

Cool. You should be doing pathway analysis on these diseases too, in that case, and checking for overlapping pathways (and noting the pathways that differ).

ADD REPLYlink written 4 weeks ago by Kevin Blighe63k

Any source or something I could read and understand? Sorry to say as I am just a beginner.

ADD REPLYlink written 4 weeks ago by Md. Al - Mustanjid30

For this exact process that you are doing? - I am not aware of any. Which do you normally use for pathway analysis?

ADD REPLYlink written 4 weeks ago by Kevin Blighe63k
Please log in to add an answer.

Help
Access

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.
Powered by Biostar version 2.3.0
Traffic: 703 users visited in the last hour