do i have to batch correction when deal with RNA-seq data that combined with fresh tissue & FFPE tissue

Question

[hs960201]

i have some normal & tumor RNA seq data of multiple regions(but same organ) of three patients but those of 10 were from fresh tissue and the others from FFPE block then, do i have to batch correction after RSEM calculated? i already know about importance of batch correction among the data that originated different studies like, TCGA, GTEx... something like that. but i think this case is pretty different. because they(data) originated different source(fresh tissue and FFPE block) but sequencing process with illumina machine done simultaneously in same condition. in this case what should i do?

[ATpoint]

Almost certainly yes. The FFPE samples most likely are more degenerate than the fresh, would surprise me if this does not create unwanted variation. Can you post a table that shows for every sample which experimental group (organ) it belongs to and whether it is fresh or FFPE? What do you want to do with the data in terms of analysis goal?

[hs960201]

sampleID       organ               type                                  sampleID        organ           type  
a_1 (DNA)   Lung cancer gDNA (fresh tissue)                a_1 (RNA)       Lung cancer  Total RNA (fresh tissue)
a_2 (DNA)   Lung cancer gDNA (fresh tissue)      a_2 (RNA)       Lung cancer    Total RNA (fresh tissue)
a_3 (DNA)   Lung cancer gDNA (fresh tissue)     a_3 (RNA)       Lung cancer Total RNA (fresh tissue)
a_4 (DNA)   Lung cancer gDNA (fresh tissue)     a_4 (RNA)       Lung cancer Total RNA (fresh tissue)
a_5 (DNA)   Blood           gDNA (blood)                 a_5 (RNA)       Normal lung    Total RNA (fresh tissue)
b_1 (DNA)   Lung cancer gDNA (fresh tissue)     b_1 (RNA)       Lung cancer Total RNA (fresh tissue)
b_2 (DNA)   Lung cancer gDNA (fresh tissue)     b_2 (RNA)       Lung cancer Total RNA (fresh tissue)
b_3 (DNA)   Lung cancer gDNA (fresh tissue)     b_3 (RNA)       Lung cancer Total RNA (fresh tissue)
b_4 (DNA)   Lung cancer gDNA (fresh tissue)     b_4 (RNA)        Lung cancer    Total RNA (fresh tissue)
b_5 (DNA)   Blood           gDNA (blood)                  b_5 (RNA)    Normal lung  Total RNA (fresh tissue)
c_1 (DNA)   Lung cancer gDNA (fresh tissue)     c_1 (RNA)   Lung cancer FFPE RNA
c_2 (DNA)   Blood                   gDNA (blood)                c_2 (RNA)   Lung cancer FFPE RNA
c_3 (DNA)   Lung cancer FFPE DNA                         c_3 (RNA)  Lung cancer FFPE RNA
c_4 (DNA)   Lung cancer FFPE DNA                        c_4 (RNA)   Lung cancer FFPE RNA
c_5 (DNA)   Lung cancer FFPE DNA                         c_5 (RNA)  Normal lung FFPE RNA

like this, a_1, a_2 <- same person but different tissue region of lung cancer

i have WGS, RNAseq data and... goal of analysis is find gene or genomic region that affect metastasis or tumor evolution. do i have to batch effect normalization? about WGS data, it seems no need to batch correction because it's not about expression but mutation on the site But I'm confused about RNA data

[ATpoint]

You have at least one sample per group and batch so it should be possible to correct for that batch. Be sure to use PCA to see whether this factor is driving relevant separation. Batch effects can also happen in WGS, but I am not sure whether (and how) one would correct for this.

[hs960201]

Thanks ATpoint But i'confused how batch effects happen in WGS You mean is it possible to be false positive at CNV analysis? Due to falsely occured depth difference across the samples??

[hs960201]

Thanks ATpoint But i'confused how batch effects happen in WGS You mean is it possible to be false positive at CNV analysis? Due to falsely occured depth difference across the samples??