Design and analysis of microarray experiments

  • How do you analyze a microarray?

    There are three main elements to consider when designing a microarray experiment.
    First, replication of the biological samples is essential for drawing conclusions from the experiment.
    Second, technical replicates (e.g. two RNA samples obtained from each experimental unit) may help to quantitate precision..

  • How do you perform a microarray analysis?

    To perform a microarray analysis, mRNA molecules are typically collected from both an experimental sample and a reference sample.
    For example, the reference sample could be collected from a healthy individual, and the experimental sample could be collected from an individual with a disease like cancer..

  • What are the major steps in preparing a microarray experiment?

    There are four main steps to a DNA microarray analysis: Sample isolation/preparation, hybridization, washing, and image analysis.
    Hybridization occurs when the samples (target and control) bond to probes with a complementary sequence..

  • What are the steps of preparing microarray experiment?

    The microarray experiment is a multi-stage process in which the accuracy of each individual step may influence the gene expression estimates.
    Precise understanding of each step is very important not only for the experimenter but also for the person performing data pre-processing..

  • What is analysis in a microarray analysis?

    Microarray analysis techniques are used in interpreting the data generated from experiments on DNA (Gene chip analysis), RNA, and protein microarrays, which allow researchers to investigate the expression state of a large number of genes - in many cases, an organism's entire genome - in a single experiment..

  • What is the basic of designing a microarray?

    There are four main steps to a DNA microarray analysis: Sample isolation/preparation, hybridization, washing, and image analysis..

  • What is the basic of designing a microarray?

    There are three main elements to consider when designing a microarray experiment.
    First, replication of the biological samples is essential for drawing conclusions from the experiment.
    Second, technical replicates (e.g. two RNA samples obtained from each experimental unit) may help to quantitate precision..

  • What is the principle of microarray analysis?

    The principle behind microarrays is that complementary sequences will bind to each other.
    The unknown DNA molecules are cut into fragments by restriction endonucleases; fluorescent markers are attached to these DNA fragments.
    These are then allowed to react with probes of the DNA chip..

  • The DNA microarray is based on using an image analysis to detect hybridization of a target molecule to a specific probe immobilized on a solid base (March-Rossell\xf3, 2017).
    Initially, specific probes of each gene are deposited onto a solid substrate (generally glass) in a lattice pattern.
  • There are four main steps to a DNA microarray analysis: Sample isolation/preparation, hybridization, washing, and image analysis.
    Hybridization occurs when the samples (target and control) bond to probes with a complementary sequence.
    The target sample refers to the treatment.
Microarray experiments generate vast quantities of raw gene expression data, therefore good experimental design and statistical analysis is required for theĀ  Microarray PlatformsExperimental Design of Analysis of Microarray Data

Do microarray experiments require statistical analysis?

Consequently, there is a greater demand for statistical assessment of the conclusions drawn from microarray experiments

This review discusses fundamental issues of how to design an experiment to ensure that the resulting data are amenable to statistical analysis

How can microarray experiments improve obstetrics and gynecology?

Microarray experiments allow description of genome-wide expression changes in health and disease

The results of such experiments are expected to change the methods employed in the diagnosis and prognosis of disease in obstetrics and gynecology

What is a problem in microarray analysis?

A major problem in the analysis of microarray data is that many hypotheses are tested simultaneously

More precisely, testing the differential expression of each gene in the array involves one hypothesis

The number of genes represented in a commercially available array is on the order of tens of thousands

Minimum information about a microarray experiment (MIAME) is a standard created by the FGED Society for reporting microarray experiments.
A reverse phase protein lysate microarray (RPMA) is a protein microarray designed as a dot-blot platform that allows measurement of protein expression levels in a large number of biological samples simultaneously in a quantitative manner when high-quality antibodies are available.

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