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!