I am trying to filter out counts of 0.000 from my normalised counts data frame so that I can run a power calculation from it using the RnaSeqSampleSize library.
I have tried to filter using dplyr (the library is active) but this doesnt seem to work.
I ideally would like 'normalized_counts' (the final data frame) to have the samples with normalised counts that are above 0.0. so not values of 0.0
Thanks for anyone's help. I've gone through a few tutorials to work this out to no avail. If I glimpse 'normalized_counts', the values in the columns are dbl
normalised_counts <- counts(dds, normalized = TRUE) normalized_counts <- counts(dds, normalized = TRUE) %>% data.frame(check.names = FALSE) %>% rownames_to_column(var="ensembl") normalized_counts$symbol <- mapIds(org.Mm.eg.db, keys = rownames(res), column="SYMBOL", keytype="ENSEMBL", multiVals="first") normalized_counts %>% filter(if_any(starts_with("ZER", "TWO", "THI", "SEV"), ~ . > 0.0))