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4 votes

Doubt about using TPM for statistics

This is a common question, and the answer is while you can calculate this, it's not statistically robust. You're likely to arrive at false conclusions. Why is this? Because while TPM is something you ...
James Hawley's user avatar
  • 1,394
4 votes

The confusion of using TPM (transcripts per million)

Use raw counts as much as you can. Add in various relevant factors as covariates in DESeq2. RNAseq metrics have come a long way but are still misused by people because it's more convenient to compare ...
Ram RS's user avatar
  • 2,454
3 votes

TPM or rlog(CPM) for comparing expression?

For comparing the counts of different samples from DESeq2, Michael Love recommends using the variance-stabilized transform. It'd be great if you could provide some specific code examples in your ...
gringer's user avatar
  • 14.7k
3 votes

Discordance in gene signature behavior between bulk and single-cell RNASeq

One explanation could be that your mapping of clusters to timepoints is not accurate. There are other methods you could look at for doing this, for example scMap, scPred, or Seurat v3 (disclosure: I ...
TimStuart's user avatar
  • 684
2 votes

TPM or rlog(CPM) for comparing expression?

To add to what @gringer, when you do use TPM, the normalization done is for both library size and gene length. When you use rlog, the normalization is done via median normalization (https://www.ncbi....
StupidWolf's user avatar
  • 1,698
2 votes
Accepted

Different results of spearman correlation between TPM and FPKM

This shouldn't be surprising that you see different correlations between gene expression data when expressed in different units. To see why, let's look at how these units are defined. Let's denote the ...
James Hawley's user avatar
  • 1,394
1 vote

Mitochondrial genes - TPM calculation bulk RNA-Seq

Yes, this is a common situation. Not just for mitochondrial genes, but for any gene that may be an outlier (e.g. the B-cell receptor gene in a contaminant/unexpected B-cell population). The way to get ...
gringer's user avatar
  • 14.7k
1 vote

What do the numbers mean in these RNA-Seq gene/transcript TPM files?

The files have pretty self-explanatory headers. The first file has EnsEMBL gene ID, HGNC symbol and then TPM for each sample. The second file has EnsEMBL gene ID, EnsEMBL transcript ID and TPM for ...
Ram RS's user avatar
  • 2,454
1 vote

The confusion of using TPM (transcripts per million)

For scRNA-seq, you don't want to normalize for gene length because the most popular 10X technology only sequences a the 3' or 5' end of the transcript. Hence CPM, which normalizes for sequencing depth ...
Chris_Rands's user avatar
  • 3,958
1 vote

What are common ways to calculate gene length for TPM calculations?

I think the most common way is to use something like Kallisto which figures out what proportion of reads are likely assigned to each transcript variant, and calculated TPM based on that.
swbarnes2's user avatar
  • 1,971
1 vote

Convert TPM-normalized matrices back to UMI in python

It depends what your downstream requirement is. If you want to do count based statisitcs, then you definately shouldn't just do TMM normalisation on the TPM data as count statistics only work on real ...
Ian Sudbery's user avatar
  • 3,331

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