Sheridan Data Widgets 3.11 22l
a new python widget library is out. this one is a series of widgets for making data visualizations. all of these widgets are built with toolkits like wxpython, gtk, or qt, so there should be nothing stopping you from creating a python widget using any of these toolkits.
this is a preview release. 3.11 is not the final release of the widgets, it’s just an indication of where the widgets are going. this is a windows release of the widget, not a linux release. this release will be the first that you can get it to work for your linux distro. so, if you have a linux distro, please test out the linux release.
this is a preview release of the widget library, not a stable version of a library. this is not a release of the toolkit. this is a preview of the toolkit and the library. this is a preview of the linux version of the library, not the windows version of the library. this is a preview of the windows version of the library. this is a preview of the widgets for windows, not the widgets for linux.
the library provides an interface to tools like qgis or osm, so it can be used in conjunction with these tools. it provides a python-to-raster conversion tool, so you can convert your data/raster to qgis or osm format. it provides an osm api, so you can use your python code to get the locations of the features and other information for these features. it provides a wms api, so you can get this information without converting it to a raster format.
a large number of new widgets have been added to the sheridan data project. this release covers primarily the data widgets widget library. this release also includes a simple trellis widget, a gantt widget, and a charts widget.
GeneTonic provides an enriched workflow to navigate the transcriptome to identify differentially expressed genes (left top panel), genesets significantly related to a given phenotype (right top panel) or directly link them to a set of relevant pathways (bottom panel, middle panel). GeneTonic reduces the complexity of the RNA-seq data analysis by automatizing tasks otherwise performed by the user, enabling straightforward exploration of all results, highlighting only the relevant entities in a presentation that makes the most of the information available. We also provide a number of custom-made tools to facilitate gene set and pathway analysis, allowing complex queries over specific gene-gene set relations and gene set or pathway enrichment. The results are automatically contextualized with a user-friendly gene set browser, enabling further exploration of the findings in an interactive manner.
The analysis of gene sets and gene-gene relationships may be easily integrated with the project-specific data, using all the tools provided by the shiny application to link several intermediate results back to the data and/or to perform predefined actions. Instead of having to go through each step to load and integrate the results in the project database, we propose the use of dynamic lists and data frames to store and share relevant information. The top section of GeneTonic ( Figure 2 ) provides the core functionality for data exploration and interpretation, and all the different steps of the analysis are automatically saved as a GeneTonicList object. All the functions described below are generic by nature and could be applied to any transcriptomic analysis, requiring the provision of lists/data frames/data frames instead of the original results of the DE analysis.