noush-joglekar
commented
5 months ago Hi Wei, the code you mention above performs exon counting based on read coverage, splice site usage, etc. Since you have already used IsoQuant to get the exon counts then the way to perform differential analysis would be to use the scisorseqr package, particularly the DiffSplicingAnalysis() function with test type set to exon. Because we described it in the methods, the actual quantification code has not been shared primarily because it is kind of slow and has not been optimized for performance. Hopefully we can include it in the next iteration of scisorseqr
Do let me know if you have issues running the differential analysis
weib3
Hello,
I'm analysing single-cell full-length RNA sequencing data. I would like to perform an analysis on alternative splicing exons, which has been mentioned multiple times in your research group's series of articles and in the methodology sections. However, I have not been able to find the related code in the repositories of your team(scisorseqr, biccn_tilgner_scisorseq, sn-code). Could you please share related code? Or perhaps I misunderstood, and the code does exist. Thanks！
A screenshot of the methods description from the article is as follows:
Hardwick S A, Hu W, Joglekar A, et al. Single-nuclei isoform RNA sequencing unlocks barcoded exon connectivity in frozen brain tissue[J]. Nature biotechnology, 2022, 40(7): 1082-1092.
Additionally, my data comes from ScNaUmi-seq, which is also 2+3 sequencing data. I analysis my data with SiCeLoRe to get consensus reads and IsoQuant to get exon count.
Wei