Related Concept Videos
03:36Genome Annotation and Assembly
The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.
03:00Next-generation Sequencing
The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features.
02:02Genomics
Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
02:54Evolutionary Relationships through Genome Comparisons
Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
03:21RNA-seq
RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases.Â
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while microarray-based...
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while microarray-based...
02:34DNA Microarrays
Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...
You might also read
Related Articles
Articles linked to this work by shared authors, journal, and citation graph.
Sort by
Same author
Structural variant discovery and diagnostic impact in rare diseases from short-read and long-read sequencing.
medRxiv : the preprint server for health sciences·2026
Same author
Hierarchical lineage tracing reveals diverse pathways of cytarabine resistance.
Nature communications·2026
Same author
Protocol for generating iPSC-derived intestinal organoids through dissection to model cystic fibrosis therapies.
STAR protocols·2026
Same author
PALINCODE: Recording cell lineage with ternary palindromic CRISPR bits.
bioRxiv : the preprint server for biology·2026
Same author
Mapping breast cancer lineage in radiation and immunotherapy using the REMAP mouse.
bioRxiv : the preprint server for biology·2026
Same author
Experimental and computational methods for allelic imbalance analysis from single-nucleus RNA-seq data.
Genome biology·2026
Same journal
Complete sequencing of medaka genomes reveals the architecture of centromeric satellites, giant mobile elements, and sex chromosomes.
Genome research·2026
Same journal
Convergence and conflict among telomere specialized transposons across 60 million years of Drosophilid evolution.
Genome research·2026
Same journal
A unified analysis of cell type- and trajectory-associated pathways in single-cell data using Phoenix.
Genome research·2026
Same journal
Resf1 is required for proper placental development and configuration of trophoblast cell-specific heterochromatin.
Genome research·2026
Same journal
Telomere-driven replicative crisis is driven by large-scale changes in genomic architecture.
Genome research·2026
Same journal
Spatially informed reference-free cell-type deconvolution for spatial transcriptomics with SpatialCD.
Genome research·2026
Related Experiment Video
Updated: Jun 10, 2026
06:58
Collection and Extraction of Saliva DNA for Next Generation Sequencing
Published on: August 27, 2014
The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data.
Aaron McKenna1, Matthew Hanna, Eric Banks
1Program in Medical and Population Genetics, The Broad Institute of Harvard and MIT, Cambridge, Massachusetts 02142, USA.
Genome Research
|July 21, 2010
Summary
The Genome Analysis Toolkit (GATK) simplifies developing analysis tools for massive next-generation DNA sequencing data. This framework enhances efficiency and robustness for genetic variation studies.
Area of Science:
- Genomics
- Bioinformatics
- Computational Biology
Background:
- Next-generation sequencing (NGS) generates vast datasets, posing challenges for analysis tool development.
- Existing tools often lack the efficiency and robustness needed for large-scale genetic variation studies.
Purpose of the Study:
- To introduce the Genome Analysis Toolkit (GATK) as a structured programming framework.
- To facilitate the creation of efficient and robust analysis tools for NGS data.
Main Methods:
- Utilized the functional programming philosophy of MapReduce.
- Developed a framework separating analysis calculations from data management infrastructure.
- Implemented parallelization for distributed and shared memory systems.
Main Results:
- The GATK provides essential data access patterns for common analysis needs.
- Enabled optimization for correctness, stability, and computational efficiency.
- Successfully implemented tools for coverage calculation and single nucleotide polymorphism (SNP) calling.
Conclusions:
- The GATK programming framework empowers developers to rapidly create efficient and robust NGS tools.
- GATK has been integrated into major sequencing projects like the 1000 Genomes Project and The Cancer Genome Atlas.