Clustering without having any replication
1
0
Entering edit mode
7 weeks ago
A ★ 4.0k

I have raw read counts of three different samples (sub-types) with no replications

like this

> head(oc)
          sample1 sample2 sample3
WASH7P          3      29      48
MIR6859-1       0       6       4
DDX11L17        0       2       2
WASH9P          3      92     101
MTND1P23        8     154     139
MTND2P28     3104    3491    3814
> 

How I can normalise this data frame because both of edger and deseq2 software needs a design of conditions

My ultimate goal is having clustering of genes in these samples but for that I would need normalised counts

Thanks for any help

edger deseq2 • 210 views
ADD COMMENT
2
Entering edit mode
7 weeks ago

Hi there!

You can achieve your goal using edgeR. Here is a brief example of what you need to do:

Convert your raw count expression matrix into a DGEList object

DGEoc <- DGSEList(counts = oc, genes = rownames(oc), group = as.factor(colnames(oc)))

Calculate normalization factors:

DGEoc <- calcNormFactors(DGEoc, method = "TMM")

Retrieve cpm (TMM) normalized counts:

norm_counts <- cpm(DGEoc, log = T)

Then, you will be able to cluster the genes.

Best regards

ADD COMMENT

Login before adding your answer.

Traffic: 2256 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