Related Experiment Video
Updated: May 27, 2026
07:35
Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
Published on: October 11, 2018
Functional comparison of microarray data across multiple platforms using the method of percentage of overlapping
Zhiguang Li1, Joshua C Kwekel, Tao Chen
1Division of Genetic and Molecular Toxicology, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, USA. zhiguang.li@fda.hhs.gov
Methods in Molecular Biology (Clifton, N.J.)
|December 2, 2011
Summary
Functional comparison of gene expression data ensures biological relevance across microarray platforms. The percentage of overlapping functions (POF) method assesses data comparability for experiments, projects, or labs.
Area of Science:
- Bioinformatics
- Genomics
- Computational Biology
Background:
- Microarray technology generates gene expression data crucial for biological insight.
- Assessing data comparability across different microarray platforms is essential for reliable biological interpretation.
- Focusing solely on gene lists overlooks the ultimate goal of understanding biological meaning.
Purpose of the Study:
- To introduce and demonstrate the percentage of overlapping functions (POF) method.
- To enable functional comparison of gene expression data from multiple microarray platforms.
- To determine functional similarities or differences in microarray data.
Main Methods:
- Development of the percentage of overlapping functions (POF) method.
- Application of POF for functional comparison of microarray data.
- Analysis of functional concordance across platforms, experiments, projects, and laboratories.
Main Results:
- The POF method provides a quantitative measure of functional similarity between microarray datasets.
- Functional comparison reveals the degree of biological relevance comparability across platforms.
- POF facilitates identification of platform-specific or experiment-specific functional biases.
Conclusions:
- The percentage of overlapping functions (POF) method is a valuable tool for assessing microarray data comparability.
- Functional comparison enhances the biological interpretation of gene expression data across diverse sources.
- POF supports robust multi-platform microarray data integration and analysis.
Related Concept Videos
02:34DNA Microarrays
Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...
02:26Comparing Copy Number Variations and SNPs
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.
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...
02:54Evolutionary 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...
01:13Multiple Comparison Tests
Multiple comparison test, abbreviated as MCT, is a post hoc analysis generally performed after comparing multiple samples with one or more tests. An MCT will help identify a significantly different sample among multiple samples or a factor among multiple factors.
It would be easy to compare two samples using a significance alpha level of 0.05. In other words, there is only one sample pair to be compared. However, it would be difficult to identify a significantly different sample if the number...
It would be easy to compare two samples using a significance alpha level of 0.05. In other words, there is only one sample pair to be compared. However, it would be difficult to identify a significantly different sample if the number...