ReadNewTotal {grandR} | R Documentation |
Read sparse new/total matrices
Description
This function can be used to load matrix market data in case genes were quantified by (i) counting all reads (for total RNA) and (ii) counting T-to-C mismatch reads (for new RNA)
Usage
ReadNewTotal(
genes,
cells,
new.matrix,
total.matrix,
detection.rate = 1,
verbose = FALSE
)
Arguments
genes |
csv file (or URL) containing gene information |
cells |
csv file (or URL) containing cell information |
new.matrix |
Matrix market file of new counts |
total.matrix |
Matrix market file of total counts |
detection.rate |
the detection rate of T-to-C mismatch reads (see details) |
verbose |
verbose output |
Details
Metabolic labeling - nucleotide conversion RNA-seq data (such as generated by SLAM-seq,TimeLapse-seq or TUC-seq) must be carefully analyzed to remove bias due to incomplete labeling. We advice against counting read with and without T-to-C mismatches for quantification, and encourage using a statistical method such as GRAND-SLAM that properly deals with incomplete labeling.
To correct for some bias, a detection rate (as suggested by Cao et al., Nature Biotech 2020) should be provided. This detection rate defines, how much new RNA is detected on average using the T-to-C mismatch reads.
Value
a grandR object