Keywords: Gene expression, RNA, RNAseq, Single cell, Transcriptomics

Prerequisites:

• A general understanding of molecular biology and genomics
• A working knowledge of Linux at the level of the Edinburgh Genomics Linux for Genomics workshop
• A working knowledge of R at the level of Edinburgh Genomics R for Biologists workshop.

Learning objectives:

• Clustering and visualisation
• Functional analysis of differentially expressed genes
• Identification of cell types in our data
• Identification of genes differentially expressed between samples
• Identification of marker genes and visualisation of marker genes
• Integration of multiple samples
• Interactive data analysis with Trailmaker
• Normalisation and dimension reduction of data
• Processing of fastq files, quality control and data filtering
• Understanding the advantages and disadvantages of single cell RNA-seq

Organizer: Edinburgh Genomics

Target audience: Graduates, postgraduates, and PIs, who are using, or planning to use, single cell RNA-seq technology in their research and want to learn how to process and analyse single cell RNA-seq data.

Event types:

• Workshops and courses