Biointelligence

November 10, 2009

BASE – A software for Microarray Data Management and Analysis

Filed under: Bioinformatics,Microarray — Biointelligence: Education,Training & Consultancy Services @ 4:27 am
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Microarray techniques produce large amounts of data in many different formats and experiment sizes are growing with more samples analysed in each experiment. Samples are collected over long time and microarray analysis is performed asynchronously and re-analysed as more samples are hybridised. Systematic use of collected data requires tracking of biomaterials, array information, raw data, and assembly of annotations. Particularly for microarray service facilities, where researchers deposit samples for experimentation, information tracking becomes vital for a subsequent data delivery back to the researchers. To meet the information tracking and data analysis challenges involved in microarray experiments BASE has been implemented.

BASE (Bioarray Software Environment) is a comprehensive free web-based database solution for the massive amounts of data generated by microarray analysis. It is a MIAME (Minimum Information About a Microarray Experiment guidelines) compliant application designed for microarray laboratories looking for a single point of storage for all information related to their microarray experimentation. BASE is a multi-user local data repository that features a web browser user interface, laboratory information management system (LIMS) for biomaterials and array production, annotations, hierarchical overview of analysis, and integrates tools like MultiExperiment Viewer (MEV) and GenePattern.

BASE is an annotable microarray data repository and analysis application providing researchers with efficient information management and analysis. BASE stores all microarray experiment related data, biomaterial information, and annotations regardless if analysis tools for specific techniques or data formats are readily available. As new techniques becomes available software applications should be expendable and modifiable to support changed needs. Moreover, it is an open source software and is freely available.

BASE website: http://base.thep.lu.se

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September 22, 2009

Minimum Information about a Microarray Experiment

Filed under: Bioinformatics,Microarray — Biointelligence: Education,Training & Consultancy Services @ 11:20 am
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After genome sequencing, DNA microarray analysis has become the most widely used source of genome scale data in the life sciences. Microarray expression studies are producing massive qunatities of gene expression and other functional genomics data, which priomise to provide an insight into gene function and inetractions within and across metabolic pathways. Unlike genome sequence data, however, which have standard formats for presentation and widely used tools and databases, much of the microarray daa generated so far remain inaccessible.

To make this information accesible in a proper format MIAME (Minimum Information About a Microarray Experiment) was introduced. MIAME format was introduced to address the ned for comprehensive annotation necessary to interpret the results of microarray data. It is platform independent but includes essential evidence about how the gene expression level measurements have been obtained.

Although the goal of MIAME is to specify only the content of the information and not the technical format, MIAME includes recommendations for which parts of the information should be provided as controlled vocabularies. MIAME includes a description of the six sections which need to be included:

1. Experimental Design
2. Array Design
3. Samples
4. Hybridizations
5. Measurements
6. Normalization controls

This specific format would really make it easy to interpret microarray data obtained from various experiments.
To read more on MIAME click here-  http://www.mged.org/Workgroups/MIAME/miame.html

 

 
After genome sequencing, DNA microarray analysis has become the most widely used source of genome scale data in the life sciences. Microarray expression studies are producing massive qunatities of gene expression and other functional genomics data, which priomise to provide an insight into gene function and inetractions within and across metabolic pathways. Unlike genome sequence data, however, which have standard formats for presentation and widely used tools and databases, much of the microarray daa generated so far remain inaccessible.

To make this information accesible in a proper format MIAME (Minimum Information About a Microarray Experiment) was introduced. MIAME format was introduced to address the ned for comprehensive annotation necessary to interpret the results of microarray data. It is platform independent but includes essential evidence about how the gene expression level measurements have been obtained.

Although the goal of MIAME is to specify only the content of the information and not the technical format, MIAME includes recommendations for which parts of the information should be provided as controlled vocabularies. MIAME includes a description of the six sections which need to be included:

1. Experimental Design
2. Array Design
3. Samples
4. Hybridizations
5. Measurements
6. Normalization controls

This specific format would really make it easy to interpret microarray data obtained from various experiments.
To read more on MIAME click here-  http://www.mged.org/Workgroups/MIAME/miame.html

 

 
After genome sequencing, DNA microarray analysis has become the most widely used source of genome scale data in the life sciences. Microarray expression studies are producing massive qunatities of gene expression and other functional genomics data, which priomise to provide an insight into gene function and inetractions within and across metabolic pathways. Unlike genome sequence data, however, which have standard formats for presentation and widely used tools and databases, much of the microarray daa generated so far remain inaccessible.

To make this information accesible in a proper format MIAME (Minimum Information About a Microarray Experiment) was introduced. MIAME format was introduced to address the ned for comprehensive annotation necessary to interpret the results of microarray data. It is platform independent but includes essential evidence about how the gene expression level measurements have been obtained.

Although the goal of MIAME is to specify only the content of the information and not the technical format, MIAME includes recommendations for which parts of the information should be provided as controlled vocabularies. MIAME includes a description of the six sections which need to be included:

1. Experimental Design
2. Array Design
3. Samples
4. Hybridizations
5. Measurements
6. Normalization controls

This specific format would really make it easy to interpret microarray data obtained from various experiments.
To read more on MIAME click here-  http://www.mged.org/Workgroups/MIAME/miame.html