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Related Concept Videos

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...
Evolutionary Relationships through Genome Comparisons02:54

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...
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.
Genome-wide Association Studies-GWAS01:11

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...
Genetic Screens02:46

Genetic Screens

Genetic screens are tools used to identify genes and mutations responsible for phenotypes of interest. Genetic screens help identify individuals or a group of people at risk of developing  genetic diseases and help them with early intervention, targeted therapy, and reproductive options.
Forward genetic screens
Forward or “classical” genetic screens involve creating random mutations in an organism’s DNA using radiation, mutagens, or insertion of additional bases, which result in visible changes...
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.

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Introductory Analysis and Validation of CUT&RUN Sequencing Data
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The Genomic HyperBrowser: inferential genomics at the sequence level.

Geir K Sandve1, Sveinung Gundersen, Halfdan Rydbeck

  • 1Department of Informatics, University of Oslo, Blindern, 0316 Oslo, Norway. geirksa@ifi.uio.no

Genome Biology
|December 25, 2010
PubMed
Summary
This summary is machine-generated.

Analyzing large genomic datasets is challenging. We introduce a novel statistical method and the Genomic HyperBrowser tool for flexible, powerful analysis of sequence-level genomic information and pairwise track relations.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Statistical Analysis

Background:

  • Genomic data generation is rapidly increasing.
  • Existing analytical methods lack the required flexibility and power for large-scale genomic data.

Purpose of the Study:

  • To propose a principled statistical approach for analyzing sequence-level genomic information.
  • To develop a flexible and powerful analytical framework for genomic data.

Main Methods:

  • Developed a novel statistical approach for analyzing genomic data.
  • Represented genomic tracks as mathematical objects.
  • Created a collection of generic biological investigations querying pairwise relations between tracks.

Main Results:

  • The Genomic HyperBrowser tool implements the proposed statistical approach.
  • The approach allows for flexible and powerful analysis of genomic data.
  • The tool facilitates the investigation of pairwise relations between genomic tracks.

Conclusions:

  • The proposed statistical approach addresses the analytical challenges posed by large-scale genomic data.
  • The Genomic HyperBrowser provides a powerful platform for genomic data analysis.
  • This methodology enables new biological insights through the analysis of sequence-level genomic information.