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hi all i have a problem for meta analysis of RNA-Seq defferential expression data that generated by CLC Genomic Workbench . in the result of RNA-Seq data analysis i see a total gene read column and tree p-value column that is the result of baggerly , edge and t-test . now , my question is that Which of them (3 type of p-value ) should be used for meta-analysis ??? is it impossible that i used the total gene read for meta analysis??

thanks giahi

Could you explain more about your experimental setup? Essentially, of what are you doing a meta-analysis?

thank you for your answer my porpose in meta analysis is that : the application of one treatment material on breast cacer cell line is effective or not ??? and for this reason i want to do a meta analysis ...but i do not know that witch column of rna seq result data ( that analysed by CLC ) should be used for meta analysis ??? my rna seq output have this column : gene id , expression value .... , total gene read , p-value , .... i think that 3 method for calculate the p-value is : 1- baggerly 2- edge 3 t-test ??? now , for meta analysis , whitch of this column /method can i used ؟؟؟ thank you so much giahi

Meta-analysis can mean everything. Do you want just to see

how manydifferentially expressed genes are there, do you want to see if there isanysignificant difference between the samples in general, or do you want to see if the differential expression you see isreliable?