@brent_p @mikelove @LuciaBarMar The paper is now >10y old, but @LaurenMMcIntyr1 and colleagues looked into this https://t.co/Y7U6O0KFVY
@PeroMHC @illumina RNA-seq: technical variability & sampling McIntyre et al http://t.co/EXyh0ml7Wn read it a while ago. hope it is relevant
RNAseq data analysis for class, papers on experimental replicates I'll have the students read http://t.co/znXzv9r0hY http://t.co/HTunqe3yj2
#bmcgenomics RNA-seq : technical variability and sampling http://t.co/VGaG2sqt
@notSoJunkDNA but, as always, recommendations depend on individual experiment (see http://t.co/38I9UzNe)
#RNA-seq: technical variability and sampling http://bit.ly/pM6omw #WWS @MyEN
Even w/ hi coverage, RNA-seq expts on same platform/protocol can give very different estimates of transcript abundance http://bit.ly/lzcUs6
Paywalled @GenomeWeb article refers to this openaccess paper on RNA-seq technical variability http://bit.ly/lzcUs6 (thanks @OpenHelix)
RNA-Seq - what can it actually do measured empirically. Awesome work, and a great reference for collaborators! http://bit.ly/jiPjqf
RNA-seq : technical variability and sampling http://ow.ly/5ef7I Concl: technical variability too high to ignore.