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Raw reads or raw counts for meta-analysis

Dear all,

I have one question regarding meta analysis. I have multiple datasets where preprocessing were done using Trimmomatic Software, Cutadapt STAR, kallisto aligned against hg19 or grch38. Can I use raw counts of them for meta-analysis or I need to preprocess all of them again using the same protocol. Problem is that I don't have access to raw reads from all of them, is there any way to overcome differences caused by differences in protocol.

Thank you in advance!

meta-analysis rna-seq htseq star

Ideally, to exclude technical variation based on preprocessing you would do an identical upstream processing. But since this is no option as you say, I don't see any choice other than using existing data for your meta analysis. After all, meta-analysis asks whether your significant calls are consistent across datasets, so I tend to say that upstream processing does not matter too much. Of cource, for genes that are difficult to map you might get insignificant results simply because aligners ahndle them differently. That's a limitation.

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