Watch it happen

Animations

Some things are far easier to watch than to read about. These explainers cover the concepts students get stuck on — how sequencing actually works, why we run FastQC, how a read finds its place in the genome, and how a neural network learns.

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Sequencing

How sequencing actually works

Watch a single DNA fragment get read base by base: fluorescent nucleotides bind, the camera fires, and the light pattern becomes letters.

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Quality control

Read quality, and why we run FastQC

Quality scores drop along a read. Drag the trimming threshold and watch reads get shorter, cleaner, and sometimes discarded entirely.

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Alignment

How a read finds its place in the genome

Step a short read along a reference and score each position — mismatches, insertions and deletions all cost something.

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Genome mapping

Why mapping uses an index

Compare brute-force scanning against index lookup on the same genome, and watch the operation counter climb.

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Machine learning

How a neural network learns

Train a tiny network to separate two classes of cells. Watch the decision boundary bend as the loss falls.

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Cloud computing

How cloud computing scales your analysis

Send 100 samples through one machine, then through an autoscaling pool, and compare wall-clock time and cost.

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Algorithms

Global alignment, cell by cell

Watch a dynamic-programming matrix fill one cell at a time, then trace back to read the alignment out. Change the gap penalty and see a different alignment win.

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Algorithms

k-mers, graphs, and how a genome gets assembled

Shred reads into k-mers, build the graph they imply, and walk it to rebuild the genome. Move the k slider and watch the graph tangle or fragment.

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Statistics

20,000 genes and 1,000 false positives

Test 20,000 genes where nothing is really changed, and watch 1,000 of them come out significant. Then compare Bonferroni and Benjamini–Hochberg on the same data.

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Molecular biology

One read's journey — FASTA to FASTQ to SAM to BAM to VCF

Follow a single read through every file format an NGS pipeline touches, watching exactly what each format adds. Click any field to find out what it means.

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Transcriptomics

The RNA-seq pipeline, end to end

Follow 180 million reads from the sequencer to a list of differentially expressed genes, watching the data change shape at every stage. Click through and see exactly what each step throws away.

How sequencing actually works

Read quality, and why we run FastQC

How a read finds its place in the genome

Why mapping uses an index

How a neural network learns

How cloud computing scales your analysis

Global alignment, cell by cell

k-mers, graphs, and how a genome gets assembled

20,000 genes and 1,000 false positives

One read's journey — FASTA to FASTQ to SAM to BAM to VCF

The RNA-seq pipeline, end to end

Why raw counts lie

Reading a pileup

What 30x actually buys you

How UMIs kill PCR duplicates

Single-cell, droplet to cluster

Structural variants from discordant pairs

Scoring a docked pose

Where the layers agree and disagree

A FASTQ through a pipe

Table scan vs B-tree index

How a workflow DAG executes

The SLURM queue and backfill

Branches, merges, and conflicts

Same script, three machines

Smith-Waterman vs Needleman-Wunsch

Why one long gap beats five short ones

The Burrows-Wheeler transform

Backward search on an FM-index

Suffix arrays and binary search

Minimizers, and why minimap2 is fast

How BLAST cheats, usefully

Short reads vs long reads

HMMs and the Viterbi path

Building a phylogeny, step by step

Big-O, at genome scale

What a p-value actually is

Build a volcano plot live

PCA, one rotation at a time

t-SNE and UMAP: what the distances mean

k-means and hierarchical: both always succeed

Watch a model overfit

Folds — and the leak that inflates them

ROC against precision-recall

Descending a loss surface

Six reading frames, one sequence

Click a base, break a protein

The central dogma, end to end

PCR, cycle by cycle

From binding sites to a sequence logo

Cut a plasmid, run a gel

Why a unique guide still has off-targets

Folding, counted exhaustively

Rewriting a gene without touching the protein