Module 5 — RNA-seq Primer (Watch/Skim)

Time: 30–45 min
Goal: Know the wet-lab → data flow so FASTQ lines make sense.

Pick any 2–3 videos (watch at 1.25× if you like)

• Gentle concept video: StatQuest: RNA-seq: Great intro to gene expression analysis by RNA sequencing
• Single Cell Sequencing - Eric Chow (UCSF): This one is mandatory!!
• Part I: What is next generation sequencing: This illumina page describes sequencing by synthesis, includes a video
• Part II: Intro to RNA-seq analysis: This is the first of several videos on RNA seq analysis (feel free to browse the others)
• EMBL-EBI "Introduction to RNA-seq & functional interpretation": Full course materials + recordings to get a minor in RNA seq

Core habit you'll use forever

Look before you loop. For any new dataset or tool, skim raw inputs and outputs with head, tail, less, or zless before writing a script that blasts through many files.

RNA-seq Workflow Overview

graph LR
    A[RNA Sample] --> B[Library Prep]
    B --> C[Sequencing]
    C --> D[FASTQ Files]
    D --> E[Quality Control]
    E --> F[Trimming/Filtering]
    F --> G[Alignment]
    G --> H[Quantification]
    H --> I[Differential Expression]

    B1[Poly-A Selection<br/>or rRNA Depletion] --> B
    B2[Fragmentation] --> B
    B3[Adapter Ligation] --> B

    C1[Sequencing by Synthesis] --> C
    C2[Base Calling] --> C
    C3[Quality Scoring] --> C

    style D fill:#e3f2fd
    style E fill:#fff3e0
    style A fill:#f3e5f5

What to notice while watching

• Where quality scores come from (fluorescence → base call → Phred).
• Why library prep choices (poly-A, rRNA depletion, UMIs) change what you see in FASTQ.
• Paired-end vs single-end expectations (R1/R2 roles).

Optional references for later: SRA home & Run Selector docs. NCBI, NCBI Insights

Exit Ticket (email)

Subject: DE M5 Exit Ticket –
Paste:

Three bullets: (1) what a read's quality string represents, (2) one library-prep choice and its consequence, (3) why we "look before we loop," in your own words.