RNA-seq
TODO Summary
How to analyze RNA-seq data
Understand what the data looks like
1. Quality control
Larger error means the data quality is poor
Identify failed sequencing experiments
Filter out those low quality reads
Trim off those low quality fragments
Reduce sequencing error caused noise as much as possible for downstream analysis
2. Mapping to reference database
3. Quantify gene expression
4. Identify differentially expressed genes
Backlinks
- Notes on Yao, Liang, Ozer, Leung, Lis, Yu, A comparison of experimental assays and analytical methods for genome-wide identification of active enhancers
- StatQuest: DESeq2, part 1, Library Normalization - YouTube
- DESeq2 experimental design and interpretation
- RNA-Seq Analysis with R and Bioconductor | Manual
- Session 5: Advanced analysis and downstream analysis in R | crukci-cluster-transition
- Sartorelli_2020: Enhancer RNAs are an important regulatory layer of the epigenome
- BIOL5460 - Quantitative Biology
- transcriptomics