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1answer
35 views

RNA-seq: How to get new expression count after normalization

I've RNA seq, Human, Paired-end data, Sample size is <40. These are aligned using STAR, RSEM processed. With RSEM I've TPM and expected counts, that is two files columns as individual IDs and row ...
0
votes
1answer
93 views

Correlate DEGs from DESeq2, EdgeR and Limma results

I have a lists of DEGs identified by DESeq2, EdgeR and Limma. I would like to correlate the the gene rankings in the lists to decide on a package to use in downstream analysis. I am havig a few ...
1
vote
0answers
179 views

What is the formula for Mg values in TMM normalization for RNA Seq data?

I am reading through the paper "A scaling normalization method for differential expression analysis of RNA-seq data" by Mark D Robinson, Alicia Oshlack, available here. In this paper they introduce a ...
0
votes
0answers
38 views

Normalization for microbiome 16s sequence analysis

The way I understand things, normalization (such as in DeSeq2, EdgeR, etc.) serves two purposes: 1) Model the "real" abundance in the original samples from the read counts, 2) Make the abundance ...
1
vote
1answer
301 views

Calculating Z-score from logCPM values using edgeR

I have the raw counts for RNA-Seq data. I converted counts data to logCPM using edgeR package. Lets say I have a dataframe A with 15000 genes as rows and 100 ...
0
votes
1answer
65 views

Experimental Design for Differential expreression analysis

I have a Normal esophageal Fibroblasts (NOFs) cultured in DMEM media; The same NOF also have been cultured with a tumor sample from a patient named 005 on DMEM media; I have also Cancer Associated ...
0
votes
1answer
541 views

Batch Effects in RNA Seq Sample

I am using the R (using EdgeR) for the RNA Seq analysis, I had few batch effect samples like Control vs treatment. Could anyone tell me the best way to remove the batch effects. I have looked into ...
1
vote
1answer
614 views

How to calculate logCPM across all samples?

Using edgeR for differential analysis between Tumor and Normal gave me differential expressed genes with logFC, logCPM, PValue and FDR. From the details of glmTreat function I see that logCPM is ...
1
vote
2answers
178 views

What could be the reason for the samples not clustering?

I'm performing RNA-seq analysis. I have used Hisat2 for aligning reads to the genome and stringtie for quantification and extracted read count information directly from the files generated by ...
2
votes
0answers
573 views

Which R package to use for differential analysis with TPM values?

I'm using hisat2, stringtie tools for the RNA-Seq analysis. After stringtie using ballgown I get FPKM and TPM values for every gene. I have seen that edgeR, Deseq2 can be used for Counts data. I ...
10
votes
2answers
444 views

*very* unbalanced group sizes for DE

I downloaded some publicly available RNA-seq data and want to compare those samples carrying a mutation (~4) against the rest (~800!). I ran both EdgeR and DESeq2, and the first results in an ...
8
votes
1answer
334 views

When performing differential expression analysis, should genes with low read counts be removed before or after normalization?

I have RNA seq data which I've quantified using Kallisto. I'd like to use tximport to transform the read count data into input for EdgeR, following the R code supplied in the tximport documentation: ...