How to compute global chromosome expression from RNA-Seq

Question

[Nicolas Rosewick]

Hi,

I want to assess the global expression of the different chromosomes (human) using RNA-Seq and compare it across mutliple samples. My first idea was to use compute a TPM for each chromosome by taking all genes from the same chromosome as a meta-gene (so count all reads aligning on all the genes of one chromosome and then compute the associated TPM).

Any other idea/suggestions ?

Thanks

[Buffo]

Aligning with bowtie at >97% identity and then count; samtools view -S.

[Nicolas Rosewick]

it's RNA-Seq so bowtie is not the best aligner to do that. I personaly use STAR to align RNA-Seq

[Buffo]

? star also creates a .sam file index doesn´t it?

[andrew.j.skelton73]

bowtie2 is not splice aware.

Answer 1

[WouterDeCoster]

That's a quite atypical analysis. Would you normalise to the length of the chromosome or to the number of genes per chromosome? Or to the total length of genes on the chromosome?

You can get the number of aligned reads per chromosome using samtools idxstats (requires bam index) after alignment. STAR is a great choice.

[Carlo Yague]

Would you normalise to the length of the chromosome or to the number of genes per chromosome? Or to the total length of genes on the chromosome?

If the OP compare multiple sample, there is no need to normalize for chromosome length or number of genes. But you need some kind of between sample normalization. The easiest (and probably not the best) way is to normalize to the total number of reads mapped.

PS : samtools idxstats is very efficient indeed, much faster than a samtools view command as Buffo proposed in its comment.

[Buffo]

For index of about 16 gb samtools view takes about 5 seconds to read it. But, idxstats works very fast too.