You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Hi and thank you for producing this package and the associated paper. I am interested in your idea of using the Beta-Binominal distribution for modelling CRISPR-screen count data and your comparisons with the MAGeCK package. I was wondering why the choice was made in CB2 to only normalise by total library size rather than by a normalisation method that attempts to handle the imbalance caused by highly abundant sequences.
As I understand it, MAGeCK uses a median ratio normalisation (function is very similar to that carried out by DESeq2) for counts before evaluating fold changes, does it make sense to also use a median ratio normalisation before running the measure_sgrna_stats function from CB2 or shoud we stick to using only the total library size normalisation (implented as get_CPM in CB2)?
The text was updated successfully, but these errors were encountered:
Hi and thank you for producing this package and the associated paper. I am interested in your idea of using the Beta-Binominal distribution for modelling CRISPR-screen count data and your comparisons with the MAGeCK package. I was wondering why the choice was made in CB2 to only normalise by total library size rather than by a normalisation method that attempts to handle the imbalance caused by highly abundant sequences.
As I understand it, MAGeCK uses a median ratio normalisation (function is very similar to that carried out by DESeq2) for counts before evaluating fold changes, does it make sense to also use a median ratio normalisation before running the
measure_sgrna_stats
function from CB2 or shoud we stick to using only the total library size normalisation (implented asget_CPM
in CB2)?The text was updated successfully, but these errors were encountered: