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Lecture 3: Transcriptomics - Coggle Diagram
Lecture 3: Transcriptomics
RNA-Sequencing protocol and implications for alignment
Experiment design > RNA preparation > library preparation > sequence > analysis
Optional: cDNA conversion, fragmentation, amplification
biases due to cDNA library construction, sequencing, read alignment
direct and long read sequencing reduce biases
Gene expression quantification
Expression normalization
normalize by a) length of transcript and b) total number of reads
-> reads / fragments per kilobase per million mapped reads RPKM / FPKM
Common goals of RNA-Seq based transcriptomics
gene-level vs transcript-level expression counting
alignment- vs assembly-based transcript reconstruction
alignment vs pseudoalignment (of a read is simply a set of target sequences that the read is compatible with)
Transcript quantification and reconstruction
if transcript structure is known: (pseudo-)alignment-based
no known transcripts available: optimization of transcript weights
Differential analysis of gene expression
Linear models, p-value, confounding factors, multiple testing correction, QQ-plot
Transcriptome = complete RNA content of a cell at a given time (varies over time unlike genome)
https://www.youtube.com/watch?v=tlf6wYJrwKY
