From RNA-seq raw counts to normalized data

[Conerx]

I have several RNA-seq datasets. Some of them provide RNA-seq raw counts, some provide FPKM, RPKM and some have transcripts per million (TPM) data. Non of them provide fastq files, all data is processed already. At the end I want all datasets to be normalized to TPM.

I'm using this code in order to normalize raw counts to TPM: (using R)

rpkm <- apply(X = subset(dataset), MARGIN = 2, FUN = function(x) { 10^9 * x / genelength / sum(as.numeric(x)) })
TPM <- apply(rpkm, 2, function(x) x / sum(as.numeric(x)) * 10^6) %>% as.data.frame()

When RPKM is provided, and no raw counts is available, I use the second line in the same code:

TPM <- apply(rpkm, 2, function(x) x / sum(as.numeric(x)) * 10^6) %>% as.data.frame()

And when FPKM is provided, I use this formula to transform the data to TPM:

TPM = FPKM*X

where

X = 1e6/[sum of all FPKM of a sample]

NOTE: genelength is obtained using the biomart package in R, to get the transcript length directly out of ensemble.

However, because I know the steps of TPM normalization in theory, one should firstly normalize to gene length, and then to gene depth. I'm not sure this is what the code does, feeling very skiptical about it even thought this code was given to me by a Phd student.

Can you guys please help me with this question? is my code right or should I alter something?

Thank you!

[Ben3]

Hello Conerx,

I'm unfortunately not well-versed in R, however, at first glance it appears like the code is not correct. The order of operations for TPM and FPKM are different, so you shouldn't use one to calculate the other. It's possible I'm wrong but my recommendation is to rewrite the code yourself. I think it teaches you more to write your own code and it allows you to fully understand what is happening.

Here are two older blog posts about TPM, RPKM, and FPKM that talk about their differences and some code to run them. Hopefully, it helps, if not let me know and I can send some additional information.

https://haroldpimentel.wordpress.com/2014/05/08/what-the-fpkm-a-review-rna-seq-expression-units/

https://www.programmersought.com/article/6418591870/

https://www.programmersought.com/article/8730973445/

[Conerx]

Hello Conerx,

I'm unfortunately not well-versed in R, however, at first glance it appears like the code is not correct. The order of operations for TPM and FPKM are different, so you shouldn't use one to calculate the other. It's possible I'm wrong but my recommendation is to rewrite the code yourself. I think it teaches you more to write your own code and it allows you to fully understand what is happening.

Here are two older blog posts about TPM, RPKM, and FPKM that talk about their differences and some code to run them. Hopefully, it helps, if not let me know and I can send some additional information.

https://haroldpimentel.wordpress.com/2014/05/08/what-the-fpkm-a-review-rna-seq-expression-units/

https://www.programmersought.com/article/6418591870/

https://www.programmersought.com/article/8730973445/

Hey Ben, thank you for your answer.

The blog posts you proposed deal with normalizing data with the fastq files at hand (raw data). However, I have only the processed data (raw counts matrix), I don't possess fasta or fastq files, therefore those blogs do not answer my question above unfortunately.