A beginner's bioinformatics guide for single-cell RNAseq data analysis

slides: docs.google.com/presentation/...
In this guide, we'll be discussing Bioinformatics methods for single-cell RNA sequencing data analysis. We'll be covering topics like RNA sequencing data QC, and normaliztion, dimension reduction, clustering and differential gene expression analysis.
If you're new to the world of bioinformatics and want to start analyzing your single-cell RNA sequencing data, then this guide is for you! By the end of this guide, you'll get a high-level understanding of analyzing the data. #bioinformatics #computationalbiology #bioinformaticstutorial #singlecell #rstats

[@kmrsongh]

I really like your videos and updates on OMICS data analysis.

[@sben5548]

Thank you so much for this video! do you have any recommendations for working with TCR repertoire data analysis?

[@mdnaveedkn]

❤

[@tobiaminu8565]

Hi Tommy, The slide you uploaded are for RNA seq and not scRNA. Thanks

[@samaafaiz6523]

Regarding the bioinformatics we can design gene accurately by sending sequence to the right company?