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Related Concept Videos

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.
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...
Organization of Genes02:07

Organization of Genes

Overview
Organization of Genes02:07

Organization of Genes

Overview
Gene Families01:57

Gene Families

Gene families consist of groups of genes proposed to have originated from a common ancestor. Typically these arise through events in which a gene or genes are mistakenly duplicated during cell division. Unlike their parent genes (which are subject to selection pressure to maintain function), these gene copies do not need to preserve their sequences and may evolve at a relatively faster rate.
Occasionally these regions can be adapted to take on new roles within the organism, becoming novel genes...
Gene Families01:57

Gene Families

Gene families consist of groups of genes proposed to have originated from a common ancestor. Typically these arise through events in which a gene or genes are mistakenly duplicated during cell division. Unlike their parent genes (which are subject to selection pressure to maintain function), these gene copies do not need to preserve their sequences and may evolve at a relatively faster rate.
Occasionally these regions can be adapted to take on new roles within the organism, becoming novel genes...

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Related Experiment Videos

FUNC: a package for detecting significant associations between gene sets and ontological annotations.

Kay Prüfer1, Bjoern Muetzel, Hong-Hai Do

  • 1Max-Planck-Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany. pruefer@eva.mpg.de

BMC Bioinformatics
|February 8, 2007
PubMed
Summary

The FUNC program package aids in analyzing large gene sets from genome-wide studies by identifying significant associations with ontological annotations. It provides statistical methods for robust interpretation of biological data.

Related Experiment Videos

Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Genome-wide studies generate extensive gene candidate lists requiring interpretation.
  • Gene Ontology (GO) and other ontologies organize biological knowledge.
  • Linking experimental gene sets with ontological data aids interpretation but faces statistical challenges due to simultaneous testing of interdependent categories.

Purpose of the Study:

  • To develop a computational tool for statistically assessing the significance of associations between gene sets and ontological annotations.
  • To expand upon existing methods for analyzing genome-wide data and interpreting biological results.

Main Methods:

  • Development of the FUNC (Functional Annotation) program package.
  • Implementation of statistical tests suitable for genome-wide sequence comparisons.
  • Inclusion of methods for estimating family-wise error rate (FWER) and false discovery rate (FDR).
  • Incorporation of a sensitive global significance estimator and a complexity-reducing algorithm.

Main Results:

  • FUNC identifies significant associations between gene sets and ontological annotations.
  • The package provides robust statistical measures, including FWER and FDR estimations.
  • FUNC offers a sensitive global significance estimator and an algorithm to simplify complex results.

Conclusions:

  • FUNC is a versatile and valuable tool for analyzing and interpreting genome-wide data.
  • The software is freely available under the GPL license.
  • FUNC is accessible as a downloadable package and via a web service.