Hello everyone.
I'm rigjht now working on data of Brassica napus getting from the company. Here is my confusion, when I come to analyze the DEG(differentially expressed genes) datasets, due to limitation of Bn database, I first correspond Bn genes to At genes where I got the putative function. However, I found one At gene, may match up to several genes in Bn, which cause big trouble as I'm looking at concrete regulation in pathways of my interest, since those gene may not have the same expression pattern (some may down-regulated, others are subject to up-regulation).
In order to better explain my question, coming up with an example here. For AtNRT1.1, there may Bn1, Bn2, Bn3 and Bn4 which are its homologs in Bn, the fact is Bn1 and 3 may got up-regulated whereas the rest two were downregulated. So, out of those 4 genes, which one or ones I should choose as I'm gonna analyze the BnNRT1.1 regulation?
Basically the company data isn't helping you answer your question. Well all I know about Rapeseed genetics is what I learned from your question and a quick look at Google. However I did find a link that may help you get started:
https://www.bing.com/search?q=brassica+napus+differentially+expressed+genes+analysis&FORM=AWRE
and
https://www.bing.com/search?q=brassica+napus+genome+database&FORM=R5FD1
hope this helps a little. Best wishes, David Booth
Hi!
I suggest you, after preprocessing your data, evaluate the dispersion of every gene. Doing so, you can select high variable genes that are really changing across sample. After, you can filter the genes by functions using the GEO database for example.
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