Meta analysis of RNA-seq data

Question

[bharata1803]

Hello,

So, currently, I want to do an analysis which include 2 separate experiments from NCBI datasets. The data is generated by Illumina HiSeq 2500 but with a bit different sequencing method. The first is paired end stranded with 48 bp. The second is single end (unknown stranded/unstranded, but I assume stranded because it has the same TruSeq preparation protocol) with 100 bp.

I generated the read count using Salmon. First, I generated human cDNA index from Ensembl GrCH38-80 and do the read counting. I set the parameter of libtype according to the experiment, whether it is single or paired end in Salmon.

Usually, this read count result will only need to be merged and become input for analysis using DESeq2 (if it is rounded to integer) or Limma/voom (as it is).

My question now is, do I need to do some special meta-analysis technique, like published in this paper

or

because the different in single/paired end is already handled during the read count I can just compare it directly?

Thank you for your answers and suggestions.

[Martombo]

there are some packages in bioconductor to perform meta-analysis of RNA-seq data. metaSeq is one of these: https://www.bioconductor.org/packages/release/bioc/html/metaSeq.html how does the PCA plot look like? if the study effect is not too big, you can account for it in the linear model.

[bharata1803]

Thank you for the suggestion. I will check for the PCA first.