Bring three major areas of expression analysis together in one learning pathway: bulk RNA-seq, single-cell RNA-seq, and circular RNA. The course moves from gene- and transcript-level analysis to cellular resolution and specialized downstream topics.
Beyond core processing, you will explore batch-effect correction, visualization, enrichment analysis, and co-expression networks. The bulk and single-cell sections are also available as standalone courses.
Part 1: Bulk RNA-seq
- Gene and transcript expressionExplore experimental design and the HISAT2–FeatureCounts–DESeq2/edgeR/limma, HISAT2–StringTie–Ballgown, and Kallisto–Sleuth workflows.
- Analysis and visualizationCorrect batch effects, create plots, run multi-condition comparisons, and perform Gene Ontology enrichment analysis.
- Networks and advanced topicsBuild WGCNA co-expression networks, examine module membership and gene significance, visualize networks in Cytoscape, and review variant calling from RNA-seq.
Part 2: Single-cell RNA-seq
- From reads to cellsUnderstand protocols and move from FASTQ files to a cellular count matrix.
- Clustering and extractionWork with Seurat and extract count matrices for selected cell clusters.
Part 3: Circular RNA
- circRNA analysisLearn the concepts, identify and quantify circRNAs through two workflows, and examine differential expression.
Who is this course for?
- Researchers and students who want several expression-analysis disciplines in one program.
- Analysts interested in statistics, networks, and effective presentation as well as data processing.
