search

IMB-Computational-Genomics-Lab / ascend

R package - Analysis of Single Cell Expression, Normalisation and Differential expression (ascend)
21 stars 7 forks source link

which data type input to runCORE #21

Closed mkrzak closed 5 years ago

mkrzak commented 5 years ago

Hello,

It is a question rather than issue. In README it is written that we can use ascend with read counts or UMI counts. I tried to perform clustering on Raw data , it gives me error to runPCA first, however once I run the PCA it tells me to normalise dataset before using this function. If I normalize dataset everything works fine. But my question is what to do if we want to avoid normalization and directly input counts into runCORE function. Is it possible ?

Best, Monika

asenabouth commented 5 years ago

Hi @mkrzak ,

You can just load your count data into the normcounts slot as follows:

normcounts(em_set) <- counts

You can then use runPCA to reduce the dataset. However, the CORE algorithm will remove any cells that are identified as outliers.

I don't recommend using whole count data in lieu of PCA-reduced values.

mkrzak commented 5 years ago

Hi @asenabouth , thank you for your quick response ! Monika