Hello everybody,
I have two RNASeq experiments that I would like to combine for clustering purpose. Unfortunately, my 2 experiments are rather different!
Experiment 1:
19 primary tumors, 2 conditions: 13 and 6 tumors per condition
Paired-ends, 75bp, Next Seq 500
TruSeq Stranded mRNA
Experiment 2:
12 tumor cell lines, the two same conditions: 6 and 6 cell lines per condition
Paired-ends, 100bp, Illumina HiSeq4000
TruSeq total RNA Stranded
I need to merge these two experiments since 4 of the cell lines derived from 4 primary tumors. The question is: Will a tumor and its cell line cluster together?
When I perform an ascending hierarchical clustering on the sample-to-sample distances with DESeq2 after merging the samples of the two experiments into one study, my samples cluster by library type.
It is not surprising since a lot of genes will have an expression value when using ribodepletion whereas they won't be captured by polyA selection.
I was thinking about simply eliminating genes that have 0 counts in polyA experiment and counts beyond a certain threshold for at least one sample of the ribodepletion experiment.
Do some of you had such problem and eventually a nice solution for exploiting such data?
Thank you in advance,
Jane
I have two RNASeq experiments that I would like to combine for clustering purpose. Unfortunately, my 2 experiments are rather different!
Experiment 1:
19 primary tumors, 2 conditions: 13 and 6 tumors per condition
Paired-ends, 75bp, Next Seq 500
TruSeq Stranded mRNA
Experiment 2:
12 tumor cell lines, the two same conditions: 6 and 6 cell lines per condition
Paired-ends, 100bp, Illumina HiSeq4000
TruSeq total RNA Stranded
I need to merge these two experiments since 4 of the cell lines derived from 4 primary tumors. The question is: Will a tumor and its cell line cluster together?
When I perform an ascending hierarchical clustering on the sample-to-sample distances with DESeq2 after merging the samples of the two experiments into one study, my samples cluster by library type.
It is not surprising since a lot of genes will have an expression value when using ribodepletion whereas they won't be captured by polyA selection.
I was thinking about simply eliminating genes that have 0 counts in polyA experiment and counts beyond a certain threshold for at least one sample of the ribodepletion experiment.
Do some of you had such problem and eventually a nice solution for exploiting such data?
Thank you in advance,
Jane
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