The output dimension is different from the input.

[inoue0426]

I tried to use this library for the public dataset, but it returned a different dimension.
Do you know why this occurs?

Dataset

https://www-ncbi-nlm-nih-gov.ezp3.lib.umn.edu/geo/query/acc.cgi?acc=GSE87544
GSE87544_Merged_17samples_14437cells_count.txt.gz

Environment

R.version

             _                           
platform       x86_64-pc-linux-gnu         
arch           x86_64                      
os             linux-gnu                   
system         x86_64, linux-gnu           
status                                     
major          4                           
minor          2.0                         
year           2022                        
month          04                          
day            22                          
svn rev        82229                       
language       R                           
version.string R version 4.2.0 (2022-04-22)
nickname       Vigorous Calisthenics       

packageVersion("scISR")

[1] ‘0.1.1’

Code and output

library(scISR)

data.path <- "../../data/chen/chen_data.csv"

A <- read.csv(
    data.path,
    header = FALSE
)

raw = as.matrix(A)

dim(raw)

14437 ・ 23284

imputed <- scISR(data = raw)

dim(imputed)

14419 ・ 23284

[duct317]

Hi,

Thank you very much for your interest in our package.

It seems like your input matrix is in form samples * genes. The required input for scISR is matrix of genes * samples. scISR has preprocessing step, so the number of rows/genes would be less in the output (in this case, samples). If you don't want scISR to filter anything, you can set preprocessing=F to turn the preprocessing step off.

Let's me know if you have any other problem.

[inoue0426]

Hi @duct317
Thank you for your advice!
I completely misunderstood it. I'll try, thanks!