How to evaluate the similarity between two different samples by using RNA-Seq?
1
0
Entering edit mode
2.2 years ago
dz2353 ▴ 110

Hi, there!

I have two samples' RNA-Seq data, one is amniotic epithelial cells(AEC), and another is keratinocyte(KRT). I have done with the upstream analysis and get the original reads count matrix. After that, I did PCA analysis, differential gene expression analysis by using DESeq2. Actually, I want to find out the similarity between AEC and KRT at the gene level. But I do not know how to do that cause I do not think the un-differently expressed genes from the result of DESeq2 can represent the similarity. I only have two samples and each one has one replicate, so I can not do co-expression network analysis. Anyone can help me? Thanks in advance!

RNA-Seq rna-seq gene • 1.5k views
ADD COMMENT
0
Entering edit mode

I only have two samples and each one has one replicate...

Do you mean you have n=1 for each group? It is impossible to do proper statistics with such a 'poor' design (no offense), please consider adding more biological replicates.

Similarity between samples can be evaluated with clustering, such as hierarchical clustering. But also correlation can be used as a measure for similarity.

ADD REPLY
1
Entering edit mode

Sorry, I mean each group has two replicates. A_1 and A_2 in AEC group, K_1 and K_2 in KRT group.

ADD REPLY
1
Entering edit mode

Are these technical replicates? For sound statistics you need biological reps... try to calculate correlation between your samples, and make a heatmap such as here. Correlation of 1 means similar, correlation of 0 means not similar.

ADD REPLY
0
Entering edit mode

Yes, they are biological replicates and I've done with correlation analysis. But actually what I want to do is to find out a gene list that shows the same expression level between two groups. Do you think the complementary set of differently expressed gene list is my target´╝čThanks for your reply!

ADD REPLY
0
Entering edit mode

Sounds like you are looking for equivalence test, haven't seen that before with RNA-seq data but if that's what you need maybe worth a try.

ADD REPLY
2
Entering edit mode
2.2 years ago

PCA and a dendrogram with hierarchical clustering (with Pearson Dissimilarity and/or Euclidan Distance as the distance metric) are the main things I would use to assess replicates before differential expression.

Otherwise, I would create a heatmap of differential expressed genes. Even if gene list sizes are similar, you may visually see better consistency of replicates with one method versus another (and I would test DESeq2/edgeR/limma-voom for your n=4 comparison).

ADD COMMENT
1
Entering edit mode

Thanks a lot, Charles.

ADD REPLY
0
Entering edit mode

If an answer was helpful you should upvote it, if the answer resolved your question you should mark it as accepted.

Upvote|Bookmark|Accept

ADD REPLY

Login before adding your answer.

Traffic: 2576 users visited in the last hour
Help About
FAQ
Access RSS
API
Stats

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.

Powered by the version 2.3.6