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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig3 Panahiazar JofBiomedInformatics2017 72-8.jpg|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig4 Auer CytometryPartA2018 93-7.jpg|240px]]</div>
'''"[[Journal:Predicting biomedical metadata in CEDAR: A study of Gene Expression Omnibus (GEO)|Predicting biomedical metadata in CEDAR: A study of Gene Expression Omnibus (GEO)]]"'''
'''"[[Journal:ChromaWizard: An open-source image analysis software for multicolor fluorescence in situ hybridization analysis|ChromaWizard: An open-source image analysis software for multicolor fluorescence in situ hybridization analysis]]"'''


A crucial and limiting factor in data reuse is the lack of accurate, structured, and complete descriptions of data, known as metadata. Towards improving the quantity and quality of metadata, we propose a novel metadata prediction framework to learn associations from existing metadata that can be used to predict metadata values. We evaluate our framework in the context of experimental metadata from the Gene Expression Omnibus (GEO). We applied four rule mining algorithms to the most common structured metadata elements (sample type, molecular type, platform, label type and organism) from over 1.3 million GEO records. We examined the quality of well supported rules from each algorithm and visualized the dependencies among metadata elements. Finally, we evaluated the performance of the algorithms in terms of accuracy, precision, recall, and F-measure. We found that PART is the best algorithm outperforming Apriori, Predictive Apriori, and Decision Table.
Multicolor image analysis finds its applications in a broad range of biological studies. Specifically, multiplex [[wikipedia:Fluorescence in situ hybridization|fluorescence ''in situ'' hybridization]] (M‐FISH) for chromosome painting facilitates the analysis of individual chromosomes in complex metaphase spreads and is widely used to detect both numerical and structural aberrations. While this is well established for human and mouse [[wikipedia:Karyotype|karyotypes]], for which species sophisticated software and analysis tools are available, other organisms and species are less well served. Commercially available software is proprietary and not easily adaptable to other karyotypes. Therefore, a publicly available open-source software that combines flexibility and customizable functionalities is needed. Here we present such a tool, called “ChromaWizard,” which is based on popular scientific image analysis libraries (OpenCV, scikit‐image, and NumPy). We demonstrate its functionality on the example of primary Chinese hamster (''Cricetulus griseus'') fibroblasts metaphase spreads and on Chinese hamster ovary cell lines, known for their large number of chromosomal rearrangements. ('''[[Journal:ChromaWizard: An open-source image analysis software for multicolor fluorescence in situ hybridization analysis|Full article...]]''')<br />
 
All algorithms perform significantly better in predicting class values than the majority vote classifier. We found that the performance of the algorithms is related to the dimensionality of the GEO elements. ('''[[Journal:Predicting biomedical metadata in CEDAR: A study of Gene Expression Omnibus (GEO)|Full article...]]''')<br />
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Revision as of 22:58, 24 February 2020

Fig4 Auer CytometryPartA2018 93-7.jpg

"ChromaWizard: An open-source image analysis software for multicolor fluorescence in situ hybridization analysis"

Multicolor image analysis finds its applications in a broad range of biological studies. Specifically, multiplex fluorescence in situ hybridization (M‐FISH) for chromosome painting facilitates the analysis of individual chromosomes in complex metaphase spreads and is widely used to detect both numerical and structural aberrations. While this is well established for human and mouse karyotypes, for which species sophisticated software and analysis tools are available, other organisms and species are less well served. Commercially available software is proprietary and not easily adaptable to other karyotypes. Therefore, a publicly available open-source software that combines flexibility and customizable functionalities is needed. Here we present such a tool, called “ChromaWizard,” which is based on popular scientific image analysis libraries (OpenCV, scikit‐image, and NumPy). We demonstrate its functionality on the example of primary Chinese hamster (Cricetulus griseus) fibroblasts metaphase spreads and on Chinese hamster ovary cell lines, known for their large number of chromosomal rearrangements. (Full article...)

Recently featured:

▪ Haves and have nots must find a better way: The case for open scientific hardware
▪ CytoConverter: A web-based tool to convert karyotypes to genomic coordinates
▪ Implementing a novel quality improvement-based approach to data quality monitoring and enhancement in a multipurpose clinical registry
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