academic.oup.com - Motivation: The Oxford Nanopore MinION device represents a unique sequencing technology. As a mobile sequencing device powered by the USB port of a laptop, the MinION has huge potential applications. To enable these applications, the...
datastorm-open.github.io - visNetwork is an R package for network visualization, using vis.js javascript library (http://visjs.org/). All remarks and bugs are welcome on github : https://github.com/datastorm-open/visNetwork.
Features
Based...
github.com - PANEV (PAthway NEtwork Visualizer) is an R package set for gene/pathway-based network visualization. Based on information available on KEGG, it visualizes genes within a network of multiple levels (from 1 to n) of interconnected upstream and...
github.com - AnchorWave (Anchored Wavefront Alignment) identifies collinear regions via conserved anchors (full-length CDS and full-length exon have been implemented currently) and breaks collinear regions into shorter fragments, i.e., anchor and inter-anchor...
www.rstudio.com - Devtools makes package development a breeze: it works with R’s existing conventions for code structure, adding efficient tools to support the cycle of package development. With devtools, developing a package becomes so easy that it will be...
bioconductor.org - The dupRadar package gives an insight into the duplication problem by graphically relating the gene expression level and the duplication rate present on it. Thus, failed experiments can be easily identified at a glance
cran.r-project.org - Provides interactive, configurable and elegant graphics visualization of the chromosomes or chromosome regions of any living organism allowing users to map chromosome elements (like genes, SNPs etc.) on the chromosome plot. It introduces a special...
github.com - platypus is an R package for object detection and semantic segmentation. Currently using
platypus you can perform:
multi-class semantic segmentation using U-Net architecture
multi-class object detection...
rstudio-pubs-static.s3.amazonaws.com - First step: Install & load “VennDiagram” package.
# install.packages('VennDiagram')
library(VennDiagram)
Second step: Load data
Add filepath if “catdoge.csv” is not in working-directory.
d <-...