3.2 From text-table file

This is definitely the most compatible text format for scRNA-seq data. which can be used by all single-cell RNA-seq technologies, like 10x Genomics, Smart-Seq, Drop-Seq and more. The commonly used text table file formats include txt (text file format), csv (comma-separated values) and tsv (tab-separated values).

table_file <- system.file("extdata/demo_inputs/table_file/demoData3.txt.gz", package = "scMINER")
demo3_mtx <- readInput_table(table_file = table_file, sep = "\t", is.geneBYcell = TRUE, removeSuffix = TRUE, addPrefix = "demo3") # set is.geneBYcell = FALSE to read features in columns and cell in in rows

## Reading table file: /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/scMINER/extdata/demo_inputs/table_file/demoData3.txt.gz ...
##  Suffix removal was specified but skipped, since some barcodes do not carry "-1" suffix.
## Done! The sparse gene expression matrix has been generated: 1000 genes, 100 cells.

NOTE: A major concern to read the gene expression matrix from text-table files is that the special characters in column names might change to dots (“.”), especially when the matrix is organized in cells by genes. This may cause failures in the identification of mitochondrial genes (usually defined by “MT-|mt-”) or spike-in RNAs (usually defined by “ERCC-|Ercc-”). The readInput_table() function has set check.names = FALSE to avoid this issue. However, if this issue already exists in the source data, you will have to fix it manually.