As part of GrasPods Welcome Week 2021, we’re delighted to bring you Part 1 of a step-by-step RNA-seq data analysis workshop, in association with the BC Children’s Hospital Research Institute’s Trainee Omics Group (TOG).

TOG is the resident graduate trainee…

Overview
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Tutorial on Co-expression network analysis using RNA-Seq data presented at the ISCB DC Regional Student Group Workshop at the University of Maryland - College Park (June 15 2016).

Abstract
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In this presentation, I provide…

If you benefit from my tutorial and use the same strategy for data analysis, please CITE my RNA-Seq paper published in "Scientific Reports - Nature": https://www.nature.com/articles/s41598-017-16603-y
And "PLOS ONE": https://journals.plos.org/plosone/art…

In this course we will be surveying the existing problems as well as the available computational and statistical frameworks available for the analysis of scRNA-seq. The course is taught through the University of Cambridge Bioinformatics training unit, but…

RNA-seq I aims to provide an introduction and the basics tools to process raw RNA-seq data on a cluster machine (Hoffman2). The workshop can serve also as a starting point to develop a gene expression project. This workshop is divided in three days that will…

"Revolutionize your RNA-seq data analysis skills with this ultimate hands-on tutorial! Learn how to create stunning PCA plots, interpret heatmaps, and master the art of differential gene expression analysis using DESeq2—all in R-Studio. This video takes you…

Single-cell RNA sequencing (scRNA-seq) analysis in R using Seurat is a powerful method for studying gene expression at the individual cell level, enabling researchers to explore cellular heterogeneity and identify distinct cell populations.
In this bioinformatics…

Building on the foundation of identifying differentially expressed genes (DEGs) in the previous workshop, it's time to unlock the biological meaning behind those findings. In this session, we'll dive into powerful downstream analyses to uncover the rich insights…

1. Introduction
2. Using Clustering Algorithms in Bioinformatics
3. Cancer Gene Expression RNA-Seq Dataset
4. K-Means Clustering Evaluation…

🧬 RNAseq Batch 6: GO and KEGG Pathway Enrichment Analysis in R – Complete Tutorial
In this hands-on session, you'll learn how to perform Gene Ontology (GO) and KEGG Pathway Enrichment Analysis in R using popular packages like clusterProfiler, org.Hs.eg.db…