Note: Cover -- Half Title -- Title Page -- Copyright Page -- Dedication -- Table of Contents -- Acknowledgements -- Author -- Introduction -- How Do Pills Know Where to Go?: The Shape and Nature of Drug Molecules Dictate Where They Act One -- Singing and Navigating - The Extraordinary Feats of Ordinary Birds: What Science Tells Us about Bird Song and Migration Two -- The Colour of Light: The Nature of Light and Colours of the Spectrum Three -- Why We Look Like Our Parents - A Bit: The Story of Genes, Chromosomes and DNA Four -- Atmospheric Rivers: Rain, Humidity and the Water Cycle Five -- The Perennial Question of Sex: How Plants Reproduce Six -- The Geometry of Ice: What Lines on an Icy Pond Reveal about the Underlying Structure of Matter Seven -- Very Small and Very Busy: Life Inside the Cell What Goes on Inside Our Human Cells Eight -- Enzymes: Familiar to Brewers and Cheesemakers, but What Are They? Nine -- Sugar, Carbs and Type 2 Diabetes: The Substances behind the Surge in Diabetes 2 Ten -- Sticking Together: The Science of Adhesion Eleven -- A Nice Warm Shower: What's the Difference between Heat and Temperature? Twelve -- Why Your Ears 'Pop': What Popping Tells Us about Pressure, the Middle Ear and the Atmosphere Thirteen -- Making Decisions: Evidence from Experimental Psychology about How We Make Choices Fourteen -- COVID-19: Viruses, Lungs and Epidemics: The Basic Science of the Pandemic Fifteen -- COVID 19: Immunity, Vaccines and Variants: The Immune System and How Vaccines Stimulate It Sixteen -- Energy and the Climate Emergency: Greenhouse Gases, Energy and Heat Pumps Seventeen -- Electricity: What It Is and Where It Comes From Eighteen -- Reflections Nineteen.

Note: Intro -- Preface -- Contributors -- Contents -- Calling Rare Variants from Genotype Data -- Introduction -- Microarray Technology -- Historical Background -- Affymetrix -- Illumina -- Technical Confounders -- Genotype Calling Algorithms -- Application to Rare Variants -- GenCall -- Birdseed -- GenoSNP -- ALCHEMY -- M3 -- optiCall -- Chiamante -- zCall -- iCall -- Conclusion -- References -- Calling Variants from Sequence Data -- Introduction -- Next-Generation Sequencing Data -- DNA Sequence Reads -- Single and Paired Reads -- The FASTQ File Format -- The BAM File Format -- Header and Alignment Sections -- Other Sequencing Technologies -- Experimental Design -- Processing Sequence Data -- Removing Adapter Sequences -- Mapping and Aligning Sequence Data to a Reference Sequence -- The FASTA Format -- Mapping Software -- Sorting and Filtering Data and Quality Checks -- Checking BAM Data for Quality -- Variant Calling -- Variant Types -- The Variant Call Format (VCF) -- Reporting Indel Alleles in VCF -- Complex Variants -- Genome VCF -- SNP Calling -- Software for SNP Calling -- How to Check SNP Calls for Quality -- Indel Calling -- Software for Indel Calling -- How to Check Indels for Quality -- Calling Other Small Variants -- Calling Large Variants -- Different Approaches to Variant Calling -- Mapping Based -- Naive Allele Counting -- Realignment Based -- Assembly Based -- Local Assembly Based -- Split Read Based -- Insert Size and Coverage -- Things to Look Out For -- Repeats in Reference -- Centromere -- HLA and MHC -- Sex Chromosomes and Autosomes -- Large-Scale Abnormalities -- Calling Variants on Different (Non-European) Populations -- Allele-Biased Variants -- Strand Bias -- Somatic Variants -- Summary -- Rare Variant Quality Control -- Introduction -- Sample Quality Control -- Ambiguous or Discordant Gender Information. , Sample Genotyping Failure Rate and Heterozygosity -- Sample Relatedness -- Population Stratification -- Genotype Error Rates -- Singleton Content -- Batch Effects -- Variant Quality Control -- Genotyping Rate -- Deviation from HWE -- Differential Missing Genotype Rates -- Allele Frequency Distribution -- Cluster Plots -- Concordance with 1000 Genomes Project Data -- X-Chromosome Quality Control -- Post Hoc Confirmation of Quality Control -- References -- Rare Structural Variants -- Structural Variation -- Arrays -- Next-Generation Sequencing -- Whole-Exome Sequencing in Disease Studies -- Conclusions and Future Directions -- References -- Functional Annotation of Rare Genetic Variants -- Overview -- Mapping Variants to Annotated Features -- Variants Falling in Protein-Coding Genes -- Variants in Non-coding Genes -- Intergenic and Regulatory Variants -- Conservation and Constraint -- Integrative Approaches -- Overlap with Known Variants and Associated Loci -- Summary -- Appendix -- References -- The 1000 Genomes Project -- Introduction -- Project Aims -- Project Implementation -- Results -- Major Biological Findings -- Genetic Variation and Its Functional Consequences in Humans -- Distribution of Variants Across Populations -- Identifying Insertion and Deletion Variants -- Looking Forward: Implications for Other Projects -- References -- The UK10K Project: 10,000 UK Genome Sequences-Accessing the Role of Rare Genetic Variants in Health and Disease -- What Is UK10K? -- Motivation Behind the Project -- UK10K Project Design -- Genome-Wide Sequencing of 4,000 Cohort Samples -- The Cohorts -- Whole Genome Sequencing -- Direct Association of Traits in the Sequenced Individuals to the Variants Found in Section 'Genome-Wide Sequencing of 4,000 Cohort Samples' -- Sequencing and Association Analysis of 6,000 Exomes from Samples with Extreme Phenotypes. , Whole Exome Sequencing -- Statistical Methods -- The Exome Collections -- Neurodevelopmental Disorders Group -- Rare Diseases Group -- Obesity Group -- Imputation into Additional GWAS Samples -- Providing a Sequence Variation Resource for Use in Further Studies -- Managed Data Access -- Publications -- UK10K Sample Sets -- The Cohorts Group -- UK10K_COHORT_ALSPAC -- UK10K_COHORT_TWINSUK -- The Neurodevelopmental Disorders Group -- UK10K_NEURO_MUIR -- UK10K_NEURO_EDINBURGH -- UK10K_NEURO_ASD_SKUSE -- UK10K_NEURO_ASD_TAMPERE -- UK10K_NEURO_ASD_BIONED -- UK10K_NEURO_ASD_MGAS -- UK10K_NEURO_FSZ and A.2.8 UK10K_NEURO_FSZNK -- UK10K_NEURO_ASD_FI -- UK10K_NEURO_IOP_COLLIER -- UK10K_NEURO_UKSCZ -- UK10K_NEURO_IMGSAC -- UK10K_NEURO_ASD_GALLAGHER -- UK10K_NEURO_GURLING -- UK10K_NEURO_ABERDEEN -- The Rare Diseases Group -- UK10K_RARE_SIR -- UK10K_RARE_NEUROMUSCULAR -- UK10K_RARE_COLOBOMA -- UK10K_RARE_CHD -- UK10K_RARE_CILIOPATHIES -- UK10K_RARE_FIND -- UK10K_RARE_THYROID -- UK10K_RARE_HYPERCHOL -- The Obesity Group -- UK10K_OBESITY_SCOOP -- UK10K_OBESITY_GS -- UK10K_OBESITY_TWINSUK -- References -- Population Isolates -- Introduction -- Use of Population Isolates in Genetic Studies -- Successful and Ongoing Studies on Population Isolates -- The First Next-Generation GWAS: deCODE and Collaborators -- HEllenic Isolate Cohorts -- The Orkney Complex Disease Study -- The SardiNIA Project and the Case-Control Study of Type 1 Diabetes and Multiple Sclerosis in Sardinia -- Conclusions -- References -- Natural Selection at Rare Variants -- Introduction -- The Characteristics and Fate of New Mutations in a Population -- Types of Selection -- Detecting Purifying Selection at Rare Variants -- Detection by Variant Deficit -- Detection by Functional Annotation -- Detection from Haplotype Structure -- Consequences of Purifying Selection at Rare Variants. , Consequences for the Age of Rare Variants -- Consequences for the Geographical Distribution of Rare Variants -- Using Selection at Rare Variants to Inform Functional Interpretation of Rare Variants -- References -- Collapsing Approaches for the Association Analysis of Rare Variants -- Introduction -- Methods -- Extended Methods -- Identified Associations -- Discussion -- References -- Rare Variant Association Analysis: Beyond Collapsing Approaches -- Introduction -- Methods -- The Data-Adaptive Sum (aSum) Test -- Step-Up Method -- Sequence Kernel Association Test -- SKAT-O -- Score-Seq -- Maximizing the Test Statistic Over Multiple Weight Vectors -- Estimated REgression Coefficients -- Kernel-Based Adaptive Cluster -- Discussion -- Test Statistic and Evaluation of Statistical Significance -- Missing Data and Imputing Rare SNVs -- Choice of Weights to Maximize Power -- Which SNVs to Include in Association Testing -- Meta-analysis -- Other Types of Traits -- References -- Significance Thresholds for Rare Variant Signals -- Introduction -- Effective Number of Independent Tests -- Estimation of the Effective Number of Independent Tests for Whole-Genome Sequencing Region-Based Tests -- Single-Variant Analyses Combined with Window-Based Analyses -- Exome Sequencing -- Family Studies or Cancer Genome Analyses -- Identity-by-Descent Considerations -- False Discovery Rates -- Generalizing the Definition of a Window -- Population Stratification and Admixture -- Conclusions -- References -- Power of Rare Variant Aggregate Tests -- Introduction -- Model Building and Test Selection -- Annotation -- Classes of Aggregate Tests -- Power of Rare Variant Aggregate Tests for Case-Control Association Studies -- A Simulation Study Based on 1000 Genomes Project -- Results -- A Simulation Study for Sample Size Calculations: Dichotomous Traits -- Dataset. , Power of Rare Variant Aggregate Tests for Continuous Traits -- A Simulation Study to Evaluate Power -- A Simulation Study for Sample Size Calculations -- Conclusion -- Links -- References -- Replicating Sequencing-Based Association Studies of Rare Variants -- Background -- Replication Strategies for Gene-Level Association Test -- Three Possible Replication Strategies -- Factors That Influence the Power for Replication -- Power for Replicating Sequence-Based Association Studies: A Mathematical Formulation -- Simulation Comparison for Three Replication Strategies -- Comparison of Replication Strategies Using Sequence Data from the Dallas Heart Study -- Resources for Designing Replication Studies -- Conclusions and Discussions -- References -- Meta-Analysis of Rare Variants -- Motivation for Meta-Analysis -- Key Principles of Meta-Analysis and Practical Considerations -- Meta-Analysis of Sequencing Studies -- Heterogeneity and the Effects on Power -- Concluding Remarks -- References -- Population Stratification of Rare Variants -- Introduction -- Some Basic Principles of Population Genetics -- Methods to Assess Population Differentiation -- Methods to Correct for Population Stratification in Genome-­Wide Association Studies -- Rare Variant Stratification on Real Data -- Impact of Rare Variant Stratification on Association Tests -- References -- Use of Appropriate Controls in Rare-Variant Studies -- Introduction -- Case-Control Studies -- Internal Versus External Controls -- General Quality Control -- Sample Quality Control -- Variant Quality Control -- Imputation -- Population Stratification -- Post-analysis Quality Control -- Preventing Bias When Using Internal Controls -- Controlling for Bias When Using External Controls -- Sequencing Studies -- Rare-Variant Genotyping Chip Studies -- Diseased Controls -- Multiple Control Sets. , Validation and Replication.