Quick pre-QC knee plots for barcode-based scRNAseq data
Dowload main.cpp and compile qnee using e.g.
g++ -std=c++11 main.cpp -o qnee -DNDEBUG
Run qnee with the length of cellbarcodes as only parameter supplying a fastq file for read 1 (cell barcode + UMI) on std_in and receiving the number of reads for each cell barcode as a text file on std_out:
zcat input_R1.fastq.gz | ./qnee 16 > output.csv
Finally load and plot the aggregated counts in you favourite analysis tool. E.g., in R you can do:
library(ggplot2)
read_numbers <- sort(read.csv("output.csv", header = F)$V1, decreasing=TRUE)
indices <- unique(round(exp(seq(log(10),log(1E5),length.out=101)))) # to limit the number of plotted lines
df <- data.frame(index=indices,
number_of_reads=read_numbers[indices])
ggplot(df, aes(x=index,y=number_of_reads))+
geom_line() +
scale_x_log10() +
scale_y_log10() +
xlab("index of cell barcode sorted by total #reads") +
ylab("#reads of cell barcode") +
NULL
To get a results like this:
