scRNASeq expression matrix with decimal values

Question

I am trying to replicate some results of a scRNASeq experiment and, when I looked at the data provided by the author, I noticed that some of the counts in the expression matrix are represented as decimals.

Would this be because the authors uploaded a normalised count matrix or for other reasons? Also, please note that the authors used the 10X genomics cellranger pipeline for the processing of raw data.

I have provided a brief snippet of the data frame here:

structure(list(P1TLH_AAACCTGAGCAGCCTC_1 = c(0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), P1TLH_AAACCTGTCCTCATTA_1 = c(0, 
0, 0.314759545319035, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0.314759545319035, 0, 0), P1TLH_AAACCTGTCTAAGCCA_1 = c(0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 1.18024827050334, 0, 0, 0, 0, 0, 1.18024827050334, 
0, 0, 0), P1TLH_AAACGGGAGTAGGCCA_1 = c(0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0.644905372424165, 0, 0, 0), P1TLH_AAACGGGGTTCGGGCT_1 = c(0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.780522072779651, 
0, 0, 0), P1TLH_AAAGCAACAGTAAGAT_1 = c(0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0)), row.names = c("RP11-34P13.7", 
"FO538757.2", "AP006222.2", "RP4-669L17.10", "RP5-857K21.4", 
"RP11-206L10.9", "LINC00115", "FAM41C", "RP11-54O7.1", "RP11-54O7.3", 
"SAMD11", "NOC2L", "KLHL17", "PLEKHN1", "RP11-54O7.17", "HES4", 
"ISG15", "AGRN", "C1orf159", "RP11-465B22.8"), class = "data.frame")

Also, I am quite confused of the structure they used - as I don't have much experience with single cell datasets. Just to give some further context:

The colnames of the "full" dataframe are coded from P1TLH_sequence_1 to P5TLH_sequence_1. There are 5 patients in the study.

I'm assuming that each of the colnames represents a cell for a particular patient while the rows are the genes.

If this assumption is correct, how would I do the conversion from colnames in the dataframe to the "cell names"? And lastly, why are there decimals in this expression matrix?

Thank you all for your time,

Answer 1

It looks like you have normalized counts. My guess is that they are log-normalized with some scale factor, probably 10000.

With the whole matrix you should be able to work out the scale factor for each cell. See https://www.nxn.se/valent/2018/10/25/unscaling-scaled-counts-in-scrna-seq-data

They typical format for scRNA-seq data is to have cells in the columns and genes in the rows. So here your rownames are the gene names and colnames are the cell names.