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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Journal.pone.0147942.g002.PNG|240px]]</div>
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'''"[[Journal:Water, water, everywhere: Defining and assessing data sharing in academia|Water, water, everywhere: Defining and assessing data sharing in academia]]"'''
'''"[[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]]"'''


Sharing of research data has begun to gain traction in many areas of the sciences in the past few years because of changing expectations from the scientific community, funding agencies, and academic journals. National Science Foundation (NSF) requirements for a data management plan (DMP) went into effect in 2011, with the intent of facilitating the dissemination and sharing of research results. Many projects that were funded during 2011 and 2012 should now have implemented the elements of the data management plans required for their grant proposals. In this paper we define "data sharing" and present a protocol for assessing whether data have been shared and how effective the sharing was. We then evaluate the data sharing practices of researchers funded by the NSF at Oregon State University in two ways: by attempting to discover project-level research data using the associated DMP as a starting point, and by examining data sharing associated with journal articles that acknowledge NSF support. Sharing at both the project level and the journal article level was not carried out in the majority of cases, and when sharing was accomplished, the shared data were often of questionable usability due to access, documentation, and formatting issues. We close the article by offering recommendations for how data producers, journal publishers, data repositories, and funding agencies can facilitate the process of sharing data in a meaningful way. ('''[[Journal:Water, water, everywhere: Defining and assessing data sharing in academia|Full article...]]''')<br />
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 />
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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