Provide easy means to export normalized Counts

[apeltzer]

Thanks for creating this tool / method! The Shiny App / general functionality is really an improvement and works pretty good. However, I'd like to export the data (e.g. normalized counts) to a separate TSV/CSV file to do downstream analyses with it, which is currently not very straightforward.

It would be very nice to see an export functionality - either in the Shiny App or (also good) in the R package in general. Couldn't find anything unfortunately...

[mcanouil]

Hi,

I described how to export the counts matrix within the vignette focusing on analysis.
https://mcanouil.github.io/NACHO/articles/NACHO-analysis.html

expr_counts <- GSE70970[["nacho"]] %>% 
  filter(grepl("Endogenous", CodeClass)) %>% 
  select(IDFILE, Name, Count_Norm) %>% 
  pivot_wider(names_from = "Name", values_from = "Count_Norm") %>% # "Name" can be replaced with "Accession"
  column_to_rownames("IDFILE") %>% 
  t()

The code above could end up in a function like the following one (quick draft).

library(NACHO)
get_counts <- function(
  nacho, 
  codeclass = "Endogenous", 
  rownames = "IDFILE", 
  colnames = c("Name", "Accession")
) {
  nacho[["nacho"]] %>% 
    dplyr::filter(grepl(codeclass, .data[["CodeClass"]])) %>% 
    dplyr::select(c("IDFILE", "Name", "Count_Norm")) %>% 
    tidyr::pivot_wider(names_from = colnames[1], values_from = "Count_Norm") %>%
    tibble::column_to_rownames(rownames) %>% 
    t()
}
get_counts(GSE74821)

[apeltzer]

Ok, didn't see / find this intuitively - this looks great, thank you!

[apeltzer]

Could be potentially cool to have some exporting functionality in the Shiny Applicaiton but from the commandline this is more than I expected and I'm absolutely happy with this 👍

[mcanouil]

I'll think more about adding a function to ease the exportation and in that case, I'll probably add some download button using that function.

The function defined above, does not exclude bad samples nor bad "genes".
Extra filters should be applied based on quality columns (or just is_outlier column), this is why I did not implement such function, because it will have a lot of parameters for QC depending on dataset.

[apeltzer]

Thats a valid and good concern. Thank you for the insights / comments. I do think there would be a benefit to allow this export, but also see the concerns here!