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Genome Annotation and Assembly

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.

Evolutionary Relationships through Genome Comparisons

Evolutionary 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...

Genome-wide Association Studies-GWAS

Genome-wide Association Studies-GWAS

Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...

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GATB: Genome Assembly & Analysis Tool Box.

Erwan Drezen¹, Guillaume Rizk¹, Rayan Chikhi¹

¹INRIA/IRISA/GenScale, Campus de Beaulieu, 35042 Rennes Cedex, France and Department of Computer Science and Engineering, Pennsylvania State University, PA 16802, USA.

Bioinformatics (Oxford, England)

|July 4, 2014

Summary

This summary is machine-generated.

We developed an open-source library for faster genome assembly and analysis. This tool uses optimized de-Bruijn graphs to process complex genomes efficiently on standard computers with low memory usage.

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Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

Next-generation sequencing (NGS) generates massive datasets requiring efficient analysis algorithms.
Algorithm design for NGS is a bottleneck due to complex data structures and hardware demands.

Purpose of the Study:

To accelerate the development of efficient software for genome assembly and analysis.
To provide an open-source library for handling large-scale genomic data.

Main Methods:

Development of an open-source C++ library named GATB.
Implementation of an optimized de-Bruijn graph algorithm.
Focus on low memory footprints and high-speed processing.

Main Results:

The GATB library enables processing of complex genomes on desktop computers.
Achieved fast algorithms with low memory requirements.
Facilitates efficient genome assembly and analysis.

Conclusions:

The GATB library offers a solution to the computational challenges in NGS data analysis.
Promotes faster development of efficient bioinformatics software.
Supports complex genome processing with readily available hardware.