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Related Concept Videos

Next-generation Sequencing03:00

Next-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.
Maxam-Gilbert Sequencing01:05

Maxam-Gilbert Sequencing

In the same year as the discovery of the Sanger sequencing method, another group of scientists, Allan Maxam and Walter Gilbert, demonstrated their chemical-cleavage method for DNA sequencing. The Maxam-Gilbert method relies on using different chemicals that can cleave the DNA sequence at specific sites, the separation of resulting DNA fragments of variable size using electrophoresis, and deciphering the DNA sequence from the resulting gel bands.
Challenges of the Maxam-Gilbert Method
The...
Sanger Sequencing01:57

Sanger Sequencing

DNA sequencing is a fundamental technique that is routinely used in the biological sciences. This method can be applied to a range of questions at different scales - from the sequencing of a cloned DNA fragment or the study of a mutation in a gene up to whole-genome sequencing. However, despite the widespread use of sequencing today, it was not until 1977 that Fredrick Sanger and his collaborators developed the chain-termination method to decode DNA sequences. It relies on the separation of a...
Genomics02:02

Genomics

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...
Genome Annotation and Assembly03:36

Genome 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.
RNA-seq03:21

RNA-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. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while microarray-based...

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Related Experiment Video

Updated: May 25, 2026

Collection and Extraction of Saliva DNA for Next Generation Sequencing
06:58

Collection and Extraction of Saliva DNA for Next Generation Sequencing

Published on: August 27, 2014

Hadoop-BAM: directly manipulating next generation sequencing data in the cloud.

Matti Niemenmaa1, Aleksi Kallio, André Schumacher

  • 1Aalto University, Department of Information and Computer Science, Aalto, Finland. matti.niemenmaa@aalto.fi

Bioinformatics (Oxford, England)
|February 4, 2012
PubMed
Summary

Hadoop-BAM enables scalable manipulation of next-generation sequencing data using the Hadoop framework. This library simplifies BAM data access and processing for large-scale genomics analysis.

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Last Updated: May 25, 2026

Collection and Extraction of Saliva DNA for Next Generation Sequencing
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Published on: August 27, 2014

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Next-generation sequencing (NGS) generates large datasets.
  • Manipulating aligned sequencing data (BAM files) in distributed frameworks presents challenges.
  • Existing tools may not efficiently handle large-scale BAM data processing.

Purpose of the Study:

  • Introduce Hadoop-BAM, a library for scalable manipulation of aligned NGS data.
  • Provide a convenient API for processing BAM records within the Hadoop framework.
  • Demonstrate the utility of Hadoop-BAM for large-scale genomics analysis.

Main Methods:

  • Developed Hadoop-BAM as an integration layer between analysis applications and Hadoop.
  • Leveraged the Picard Sequence Alignment/Map (SAM) Java Development Kit (JDK).
  • Implemented a coverage summarizing tool for the Chipster genome browser using Hadoop-BAM.

Main Results:

  • Hadoop-BAM facilitates scalable manipulation of BAM files on the Hadoop distributed computing framework.
  • The library offers a convenient API for map and reduce functions operating directly on BAM records.
  • Demonstrated good scalability of Hadoop for genomics data processing, emphasizing in-framework data handling.

Conclusions:

  • Hadoop-BAM effectively addresses challenges in accessing and processing large-scale BAM data.
  • The library supports seamless integration with existing Picard-based tools for distributed processing.
  • Optimizing data flow within Hadoop is crucial for efficient large-scale genomics analysis.