DNA microarray
From Biohack
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Minimum Information About a Microarray Experiment checklist
MIAME website. Go get the MGED ontology. The importance of ontologies is that they can help standardize massively parallel microarray experiments and lab on a chip (LOAC) technology. Such designs allow for the highly parallel testing of organisms or separated DNA strands for various properties.
The raw data for each hybridisation (e.g., CEL or GPR files)[edit]Minimum Information About a Microarray Experiment - MIAME 2.0 (a proposal for discussion, May 21, 2007)
The six following elements must be provided to support microarray based publications.
- The raw data for each hybridisation.
The raw data are defined as data files produced by the microarray image analysis software, such as CEL files for Affymetrix or GPR files for GenePix. These files should be provided in the native formats and should match their respective array designs.
- The final processed data for the set of hybridisations in the experiment (study)
The processed data is defined as the normalised and/or summarized data on which the conclusions in the related publication are based. For instance, these can be <acronym title="Affymetrix Microarray Suite ">MAS5</acronym> or <acronym title="Robust Multichip Average">RMA</acronym> normalised data matrices for Affymetrix data. In gene expression experiments the final processed data is typically a matrix of genes and experimental conditions characterizing the expression of each gene under each condition. The identifiers used in these processed data files should match the array annotation or locations on the arrays.
- The essential sample annotation, including experimental factors and their values
Experimental factors (conditions) and their values are the most essential information about the samples used in the experiment. The experimental factors are the key experimental variables in the experiment, for instance "time" in time series experiments, "dose" in dose response experiments, "compound" in compound treatment experiments, or "disease state" (normal or otherwise) in disease studies. The same experiment may have several experimental factors, for example, compound, dose and time may all be experimental factors in a dose response experiment in which several compounds are used to treat samples over a time course. In addition to experimental factor values, additional sample information that is required to interpret the experiment must be given, for instance, the organism and organism part from which the sample has been taken.
- The experiment design including sample data relationships
The purpose of the experimental design description is simply to specify the essential relationships between different biomaterials, such as samples and arrays, and the data files which are produced in each hybridisation. In a simple one channel one sample - one array experiment, this may be a table listing all samples and the respective raw data files. If relevant, it is important to show which hybridisations in the experiment are replicates, and which are technical and which are biological replicates. More generally, the experimental design can be described as a graph where nodes represent biomaterials (e.g., samples or their sources) and data objects (e.g., files), and edges or arrows show their relationships. <a href="/mage-tab/"><acronym title="MicroArray and Gene Expression">MAGE</acronym>-TAB</a> provides a simple format to encode such graphs.
- Sufficient annotation of the array design
Essential array design information is the reporter (probe) sequence information and/or the database accession numbers that characterise a sequence. For synthetic oligonucleotides the precise DNA sequence must be given. For commercial or other standard array platforms this information is typically provided by the array vendors or manufacturers.
- Essential experimental and data processing protocols
The essential laboratory and data processing protocols are usually described in the journal methods section. It is sufficient to simply reference the standard experimental or data processing protocols, such as <acronym title="Affymetrix Microarray Suite">MAS5</acronym> or <acronym title="Robust Multichip Average">RMA</acronym>. However, if a protocol depends on parameters that can be varied, their values should be provided. If novel or non-standard data processing protocols are used, these should be described in sufficient detail to allow the user to understand what exactly has been done in the experiment and how the data have been analysed to reach the conclusions of the study.
DNA melting
DNA melting is the process of increasing the temperature of a container of DNA, supposedly separating the DNA into fragmented segments. These segments can then be mixed with other random segments. Then, chromatographic or fluoroscopic or perhaps even visual methods can be used to assess to what degree the DNA is similiar to the other strands inserted with the labelled DNA sample. DNA that is highly similiar will connect with the other similiar strands and require greater temperature (energy) to separate them. So, when you have a giant microarray experiment, those samples of mixed DNA (known & unknown fragments) that separate easily are those that are dissimiliar. Evidently the DNA microarrays are used to run incredibly massive experiments such that information on what is similiar to what can be discovered (statistical reasoning). However, microarrays have other uses. See also DNA-DNA hybridization.
Other uses of the DNA microarray
Other possible uses include more generalized uses ... basically the design seems to be the same as an oligonucleotide inkjet printer setup, except that there are many more place-values to hold the RNA fragments, and there is some sort of probe that is able to scan each 'well' for relevant variables -- the probe is made of the mRNA complement and thus why RNA microarrays are useful for analyzing gene expression.
Videos
How DNA microarrays are used to show dynamic gene expression
How they are made
Re: lasers, go see Sam for DIY lasers.
