Hi there,
I have looking for answers to best perform this analysis.
Its my second time in my facility preparing/running and analyzing riboseq. I think this time went way better comparing from the first experiment. :) However, there are some issues that happen...
For this experiment we made two batches of samples to try to maximize the quality and the coverage. Anyway, the first batch my colleague (wet lab technician) and i realized alot of "noise" after the 76bp (is recommended to perform 150 cycles in riboseq). The reads after the 76bp decreased the quality but passed the Q20 (was not so bad) also the number of reads was quite low. We expected between 30-50 million and we have got around 16-27 million.
After talking with our boss my colleague rerun the same batch of samples but using a kit for 76bp. Instantly, we have got a way better quality, coverage, ... The 2nd batch was ran with 75bp and was a perfect run in terms of quality!
My idea was using only the batch 1 from second run and the batch 2.
However, my boss suggested to merge the two runs from the batch 1 and the batch 2.
Now, i wonder if it is correct merge different runs with different read lengths (ok, we have here now some technical bias for the posterior analysis). I read this post (Best way to merge RNA-seq data from two sequencing runs of the same samples) "Technical replication of sequencing is excellent. As long as you stick to the same platform/read lengths..." i don't know what to do to be honest or ignore the the first run from the first batch or merge them during the stringtie (assembly step) and use the collapseReplicates() from DESeq2 for the two runs.
What do you think guys? :)
I really appreciate any feedback.
All the best,
Andreia
I would run a PCA first to see if the same samples from different batches cluster together or not.