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Genomics

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...

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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.

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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...

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Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
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Next-generation Sequencing

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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.
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Genomation: a toolkit to summarize, annotate and visualize genomic intervals.

Altuna Akalin¹, Vedran Franke¹, Kristian Vlahoviček²

¹Friedrich Miescher Institute for Biomedical Research, 4058 Basel, Switzerland, Bioinformatics Group, Department of Molecular Biology, Faculty of Science, University of Zagreb, 10000 Zagreb, Croatia, Department of Physiology and Biophysics and the Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10021, USA, Faculty of Science, University of Basel, 4051 Basel, Switzerland and Department of Informatics, University of Oslo, NO-0316 Oslo, Norway.

Bioinformatics (Oxford, England)

|November 24, 2014

Summary

This study introduces genomation, an R package simplifying the analysis of diverse genomics data. It streamlines extracting biological insights from high-throughput data, overcoming common file format and tool challenges.

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Area of Science:

Genomics
Bioinformatics
Computational Biology

Background:

Genomics data integration is crucial for biological insights but faces challenges with diverse file formats and complex tools.
Existing methods for analyzing high-throughput genomics data can be cumbersome and require specialized expertise.

Purpose of the Study:

To develop an R package, "genomation", to simplify and expedite the extraction of biological information from high-throughput genomics data.
To provide a user-friendly tool for summarizing and annotating various genomic interval file types.

Main Methods:

Developed an R package named "genomation".
The package supports multiple genomic interval file formats.
Enables summarization and annotation of high-throughput data using genomic annotations.

Main Results:

The "genomation" package facilitates efficient processing of diverse genomics datasets.
It simplifies the integration and analysis of high-throughput data.
The package allows for easy summarization and annotation of genomic information.

Conclusions:

"genomation" enhances the accessibility of biological insights from genomics data.
The R package addresses limitations in current genomics data analysis tools.
It offers a valuable resource for researchers working with high-throughput genomics datasets.