Chapter 1
Platforms & Chemistries
1: Sequencing Technologies & NGS Chemistries
- • Illumina cyclic reversible terminator chemistry and pattern flow cells
- • Pacific Biosciences Single-Molecule Real-Time (SMRT) circular consensus reads (HiFi)
- • Oxford Nanopore electrolytic nanopores, squiggles, and Dorado basecalling
- • Phred quality scores ($Q = -10 \log_{10} P$) and sequencing error profiles
- • Comparison of throughput, read lengths, cost per gigabase, and runtime
Chapter 2
Experimental Design
2: Experimental Design, Library Prep & Coverage Estimation
- • Mathematical modeling of sequencing depth: Lander-Waterman equation
- • Poisson statistics: Probability of zero-coverage regions ($P(0) = e^{-C}$)
- • Library preparation strategies: Mechanical acoustic shearing vs enzymatic tagmentation
- • PCR-free vs amplified libraries: Mitigating GC dropout and duplicate rates
- • Designing cohort experiments: Balancing multiplexing, flow cell lanes, and batch effects
Chapter 3
Quality Control
3: Raw Read Quality Control & Adapter Trimming
- • Deconstructing FastQC reports: Per-base sequence quality and GC content distributions
- • Diagnosing sequencer anomalies: Phasing, pre-phasing, tile quality degradation, and optical bubbles
- • Adapter read-through in short insert libraries and dimer contamination
- • Automated dual-adapter detection, poly-G tail clipping, and quality filtering with fastp
- • Aggregating cohort-scale quality metrics across hundreds of runs using MultiQC
Chapter 4
Alignment
4: Reference Genome Architecture, Indexing & Read Alignment
- • Evolution of human reference builds: GRCh37 (hg19), GRCh38 (hg38), and T2T-CHM13
- • Reference genome fasta hygiene: Primary assembly vs alt-contigs and decoy sequences
- • The Burrows-Wheeler Transform (BWT) and FM-Index for $O(m)$ exact substring searches
- • High-throughput read alignment using BWA-MEM2 and Bowtie2
- • Long-read alignment using minimap2 with splice and structural variant presets
Chapter 5
Data Processing
5: SAM/BAM/CRAM Processing & Duplication Metrics
- • Deconstructing the SAM 11 mandatory fields and CIGAR string semantics (M, I, D, S, H)
- • Bitwise FLAG arithmetic: Reading paired-end alignment states (0x1, 0x2, 0x4, 0x10, 0x400)
- • Mapping Quality (MAPQ) scoring and alignment uniqueness
- • PCR vs optical duplicates: Duplicate identification mechanics with Picard and Sambamba
- • Reference-based CRAM compression for 60% storage cost reduction in clinical biobanks
Chapter 6
Variant Discovery
6: Germline Short Variant Calling with GATK4 & DeepVariant
- • Base Quality Score Recalibration (BQSR): Correcting sequencer optical and flow cell systematic error
- • GATK4 HaplotypeCaller: Local de novo re-assembly of active regions via de Bruijn graphs
- • Joint genotyping cohort architecture: GenomicsDBImport and GenotypeGVCFs
- • Variant Quality Score Recalibration (VQSR) vs Hard Filtering guidelines
- • DeepVariant: Transforming read alignments into multi-channel tensor images for CNN classification
Chapter 7
Clinical Genomics
7: Somatic Oncology & Cancer Genomics
- • Biological distinction: Germline variation vs somatic clonal/subclonal mutations
- • Matched tumor-normal experimental design and blood-derived normal controls
- • Constructing a Panel of Normals (PoN) to filter recurring sequencing and mapping artifacts
- • Somatic variant discovery with GATK4 Mutect2 and FilterMutectCalls
- • FFPE sample damage modeling: Read orientation bias (8-oxoguanine and deamination artifacts)
Chapter 8
Annotation & Clinical
8: Variant Annotation, Effect Prediction & ClinVar Integration
- • Deconstructing functional consequences: Missense, nonsense, frameshift, and canonical splice site
- • High-throughput annotation with Ensembl VEP (Variant Effect Predictor) and plugins
- • Population allele frequency filtering with gnomAD (Genome Aggregation Database)
- • ClinVar database querying and ACMG/AMP pathogenicity classification standards
- • In silico damage prediction scores: CADD, REVEL, SpliceAI, and AlphaMissense
Chapter 9
Structural Genomics
9: Structural Variant Discovery & Copy Number Alterations
- • Classes of structural variation (SV > 50 bp): Deletions, duplications, inversions, and translocations
- • Signatures in short-read data: Discordant read pairs, split reads, and read-depth disparities
- • Calling germline and somatic SVs with Manta and Delly
- • Long-read SV breakthroughs: Span-based detection of complex nested rearrangements using Sniffles2
- • Copy Number Variation (CNV) profiling across whole-exome and targeted panels using CNVkit
Chapter 10
Transcriptomics
10: Bulk RNA-Seq Alignment & Quantification
- • Splice-aware vs unspliced alignment: The challenge of non-contiguous eukaryotic exons
- • STAR (Spliced Transcripts Alignment to a Reference): 2-pass indexing and junction discovery
- • Alignment-free pseudoalignment: Quasi-mapping mechanics of Salmon and kallisto
- • Normalized expression units: Dissecting CPM, RPKM, FPKM, and TPM (Transcripts Per Million)
- • Summarizing transcript-level abundances to gene-level count matrices using tximport
Chapter 11
Epigenomics & Regulation
11: Epigenomics & Peak Calling (ChIP-Seq & ATAC-Seq)
- • Principles of chromatin regulation: Open chromatin vs heterochromatin and histone marks
- • Assay for Transposase-Accessible Chromatin (ATAC-seq) biochemistry and Tn5 cutting dynamics
- • Chromatin Immunoprecipitation sequencing (ChIP-seq): Antibody specificity and Input controls
- • MACS3 model-based peak calling for narrow (TF) and broad (H3K27me3, H3K9me3) domains
- • Motif discovery and regulatory footprinting using HOMER and MEME-Suite
Chapter 12
Single-Cell Genomics
12: Single-Cell RNA Sequencing Foundations
- • Microfluidic droplet mechanics: Encapsulating single cells with barcoded gel beads (GEMs)
- • Cellular Barcodes vs Unique Molecular Identifiers (UMIs) to eliminate PCR amplification bias
- • The 10x Genomics Cell Ranger count pipeline: Demultiplexing, alignment, and filtering
- • Distinguishing real single cells from ambient RNA: The EmptyDrops algorithm
- • Quality metrics: Mitochondrial read percentage thresholds and doublet detection
Chapter 13
Genome Assembly
13: De Novo Genome Assembly, Scaffolding & Quality Assessment
- • Algorithmic paradigms: De Bruijn graphs ($k$-mers) for short reads vs Overlap-Layout-Consensus (OLC) for long reads
- • Resolving genomic repeats, segmental duplications, and heterozygosity bubbles
- • Long-read and telomere-to-telomere assembly with Hifiasm and Flye
- • Chromosome-level scaffolding using High-Throughput Chromosome Conformation Capture (Hi-C)
- • Assembly validation: Evaluating contiguity with N50/L50 (QUAST) and completeness with BUSCO
Peer-Reviewed Foundations
Seminal peer-reviewed benchmarks and methodology literature
📚 Foundational Literature & Methodology Benchmarks
Variant Calling & GATK4
- Van der Auwera GA, O'Connor BD. (2020). Genomics in the Cloud: Using Docker, GATK, and WDL in Terra. O'Reilly Media. doi:10.5555/3432049
- Poplin R, Chang PC, Alexander D, et al. (2018). A universal SNP and small-indel variant caller using deep neural networks (DeepVariant). Nat Biotechnol 36(10):983–989. doi:10.1038/nbt.4235
- DePristo MA, Banks E, Poplin R, et al. (2011). A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat Genet 43(5):491–498. doi:10.1038/ng.806
Alignment & File Standards
- Li H. (2013). Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. arXiv. doi:10.48550/arXiv.1303.3997
- Danecek P, Bonfield JK, Liddle J, et al. (2021). Twelve years of SAMtools and BCFtools. GigaScience 10(2):giab008. doi:10.1093/gigascience/giab008
- Li H, Handsaker B, Wysoker A, et al. (2009). The Sequence Alignment/Map format and SAMtools. Bioinformatics 25(16):2078–2079. doi:10.1093/bioinformatics/btp352
Annotation & Interpretation
- Cingolani P, Platts A, Wang LL, et al. (2012). A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff. Fly 6(2):80–92. doi:10.4161/fly.19695
- Thorvaldsdóttir H, Robinson JT, Mesirov JP. (2013). Integrative Genomics Viewer (IGV): high-performance genomics data visualization. Brief Bioinform 14(2):178–192. doi:10.1093/bib/bbs017
- Okonechnikov K, Conesa A, García-Alcalde F. (2016). Qualimap 2: advanced multi-sample quality control for high-throughput sequencing data. Bioinformatics 32(2):292–294. doi:10.1093/bioinformatics/btv566