Code used to carry out parameter estimation, correlation estimation, type 1 error analysis, and power analysis for our "Pseudoreplication in Single-Cell" study
MIT License
18
stars
5
forks
source link
Intra- and inter-individual correlation: input specification missing #4
Thanks for sharing the code to study intra- and inter-individual correlation in scRNA-seq data. We are interested in performing this analysis, specifically the intra-correlation one, in our dataset as a proxy of cell-to-cell variability within an individual.
Would you mind specifying what is really the initial input in the Correlation Comparison.Rmd? I assume it's the cells <- allgenes[-3] object in line 65 of this script. Maybe you could share a toy example?
Also, in the methods, you say you filtered out the lowly expressed and correlated genes. I do see the section where you filter out the correlated genes (lines 67-86 in this script), but I do not find the filter of lowly expressed genes ("Genes were removed if the average transcript-per-million (TPM) value was equal to zero.", from your methods section).
Hi!
Thanks for sharing the code to study intra- and inter-individual correlation in scRNA-seq data. We are interested in performing this analysis, specifically the intra-correlation one, in our dataset as a proxy of cell-to-cell variability within an individual.
Would you mind specifying what is really the initial input in the Correlation Comparison.Rmd? I assume it's the
cells <- allgenes[-3]
object in line 65 of this script. Maybe you could share a toy example?Also, in the methods, you say you filtered out the lowly expressed and correlated genes. I do see the section where you filter out the correlated genes (lines 67-86 in this script), but I do not find the filter of lowly expressed genes ("Genes were removed if the average transcript-per-million (TPM) value was equal to zero.", from your methods section).
Thanks a lot! Aida