Hello :D
I'm trying to individuate significant expression correlations (in a co-expression network) between a limited number of genes (9) and a larger dataset (to which the genes belong) (2300).
More specifically, the logic behind this is to correlate 9 promising candidates (individuated through other approaches, literature, BSA-Seq analysis etc) for disease resistance in plants to other genes (potentially co-regulated and involved in the same network), according to their expression levels. Particularly, the 2300 genes I'd like to investigate are differentially expressed (as a result of a DEG analysis with DESeq2) in a line characterized by a partial resistance to the pathogen, compared to a sensitive one.
I've already tried WGCNA (with R and then, Cytoscape) but I'm not really interested in co-expressionmodules. Instead,I'd need and approach allowing me to start from a very limited number of candidate genes and individuate further, related, genes, from them.
As I wrote in this topic, for this aim, I tried the CoExpNetViz Cytoscape plugin, which unfortunately doesn't seem to work in a reliable way for larger datasets. Moreover, the statistical approach, only relying on Pearson coefficients and not discriminating among sample conditions, doesn't fully convince me.
Can anyone suggest me some bioinformatics tool (on R, or stand-alone online tools) which could be useful?
Thanks in advance, have a nice day and a happy new year!
you got many previous questions that didn't got any validation or feedback: Trinity RSEM Bowtie2 align_and_estimate_abundance script error ; Trinity RSEM Bowtie2 align_and_estimate_abundance script error ; How to perform KEGG enrichment analysis for DE genes from a de-novo transcriptome? ; How to merge two gff3 files? ; etc... etc...
Yes, I used this website quite frequently since I started working with bioinformatic tools... especially at the beginning. Some of my previous questions are still unanswered or didn't really solve my problems but in some other cases they did.
Should I close my old topics or anything like that?
For example, in this post, the answer is correct. However, you did not accept the answer.
How to perform KEGG enrichment analysis for DE genes from a de-novo transcriptome?
And for the rest of posts give feedback.