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DNA Microarrays

DNA 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...

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DNA-affinity-purified Chip DAP-chip Method to Determine Gene Targets for Bacterial Two component Regulatory Systems

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ChIP-on-chip analysis methods for Affymetrix tiling arrays.

¹Molecular Genomics Core Facility, H. Lee Moffitt Cancer Center and Research Institute, 12902 Magnolia Drive, Tampa, FL, 33612, USA, Sean.yoder@moffitt.org.

Methods in Molecular Biology (Clifton, N.J.)

|April 2, 2015

Summary

This summary is machine-generated.

ChIP-Chip microarray analysis offers a cost-effective method for identifying protein-DNA interactions. This review guides researchers in selecting appropriate tools for Affymetrix ChIP-Chip data analysis.

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Area of Science:

Genomics
Molecular Biology
Bioinformatics

Background:

ChIP-sequencing is popular, but ChIP-Chip microarrays remain valuable for cost-effectiveness and data accessibility.
ChIP-Chip data analysis is complex, requiring multiple computational tools for raw data processing to binding site identification.
Numerous analysis approaches and applications exist, necessitating careful selection based on experimental needs and user expertise.

Purpose of the Study:

To review commonly available applications for Affymetrix ChIP-Chip data analysis.
To provide a general workflow for ChIP-Chip analysis.
To guide researchers in selecting appropriate tools for their specific experiments.

Main Methods:

Review of existing bioinformatics applications for ChIP-Chip data.
Description of a general ChIP-Chip data analysis workflow.
Evaluation criteria for selecting analysis tools.

Main Results:

Identification of various applications suitable for different stages of ChIP-Chip analysis.
Outline of a structured approach to ChIP-Chip data processing.
Considerations for matching tools to experimental design and researcher computational proficiency.

Conclusions:

Selecting the right tools is crucial for successful ChIP-Chip data analysis.
Researchers can navigate the complexities of ChIP-Chip analysis with informed application choices.
This review empowers researchers to effectively utilize Affymetrix ChIP-Chip data.