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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-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...

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.

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Eukaryotes have large genomes compared to prokaryotes. To fit their genomes into a cell, eukaryotic DNA is packaged extraordinarily tightly inside the nucleus. To achieve this, DNA is tightly wound around proteins called histones, which are packaged into nucleosomes that are joined by linker DNA and coil into chromatin fibers. Additional fibrous proteins further compact the chromatin, which is recognizable as chromosomes during certain phases of cell division.

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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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Related Experiment Video

Updated: Jul 18, 2025

A Fast and Quantitative Method for Post-translational Modification and Variant Enabled Mapping of Peptides to Genomes

A Fast and Quantitative Method for Post-translational Modification and Variant Enabled Mapping of Peptides to Genomes

Published on: May 22, 2018

Gonomics: uniting high performance and readability for genomics with Go.

Eric H Au¹, Christiana Fauci^1,2, Yanting Luo^1,2

¹Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, NC 27710, United States.

Bioinformatics (Oxford, England)

|August 25, 2023

Summary

This summary is machine-generated.

Gonomics is a new open-source software collection in Go, offering high performance and readability for genomic analyses. It supports various file formats and enables flexible pipeline development for bioinformatics.

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Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

Genomic software often forces a choice between compiled language performance and interpreted language accessibility.
Existing tools may not meet the growing demand for high-performance bioinformatics resources.

Purpose of the Study:

Introduce Gonomics, an open-source collection of bioinformatic libraries and command-line programs.
Unite performance and readability in genomic data analysis using the Go programming language.

Main Methods:

Implemented Gonomics using the Go programming language.
Developed modular libraries for reading, writing, and manipulating genomic file formats (FASTA, FASTQ, BED, BEDPE, SAM, BAM, VCF).
Enabled format conversion and interoperability.

Main Results:

Gonomics provides a unified solution for genomic analyses, balancing performance and ease of use.
Offers a flexible platform for developing custom bioinformatics tools.
Facilitates the creation of complex, high-performance analysis pipelines.

Conclusions:

Gonomics addresses the performance-accessibility conflict in genomic software.
It serves as a valuable, open-source resource for researchers in genomics and bioinformatics.
The Go implementation ensures efficient and readable genomic data processing.