<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/43319?offset=20 https://bioinformaticsonline.com/bookmarks/view/43321/applying-minhash-to-cluster-rnaseq-samples Thu, 26 Aug 2021 10:37:19 -0500 https://bioinformaticsonline.com/bookmarks/view/43321/applying-minhash-to-cluster-rnaseq-samples <![CDATA[Applying MinHash to cluster RNAseq samples]]> A kmer blog worth spending time on

Address of the bookmark: http://ivory.idyll.org/blog/2016-sourmash.html

]]> Neel https://bioinformaticsonline.com/bookmarks/view/27070/venn-diagrams-on-r-studio Mon, 25 Apr 2016 16:22:28 -0500 https://bioinformaticsonline.com/bookmarks/view/27070/venn-diagrams-on-r-studio <![CDATA[Venn Diagrams on R Studio]]> 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 <- read.csv("catdoge.csv")

Address of the bookmark: http://rstudio-pubs-static.s3.amazonaws.com/13301_6641d73cfac741a59c0a851feb99e98b.html

]]> Jitendra Prajapati https://bioinformaticsonline.com/bookmarks/view/28937/sushi-an-rbioconductor-package-for-visualizing-genomic-data Wed, 31 Aug 2016 08:29:12 -0500 https://bioinformaticsonline.com/bookmarks/view/28937/sushi-an-rbioconductor-package-for-visualizing-genomic-data <![CDATA[Sushi: An R/Bioconductor package for visualizing genomic data]]> Sushi: An R/Bioconductor package for visualizing genomic data

Address of the bookmark: https://www.bioconductor.org/packages/devel/bioc/vignettes/Sushi/inst/doc/Sushi.pdf

]]> Jit https://bioinformaticsonline.com/bookmarks/view/29917/gojs Tue, 22 Nov 2016 08:25:37 -0600 https://bioinformaticsonline.com/bookmarks/view/29917/gojs <![CDATA[GoJS]]> GoJS is a feature-rich JavaScript library for implementing custom interactive diagrams and complex visualizations across modern web browsers and platforms. GoJS makes constructing JavaScript diagrams of complex nodes, links, and groups easy with customizable templates and layouts.

GoJS offers many advanced features for user interactivity such as drag-and-drop, copy-and-paste, in-place text editing, tooltips, context menus, automatic layouts, templates, data binding and models, transactional state and undo management, palettes, overviews, event handlers, commands, and an extensible tool system for custom operations.

GoJS is pure JavaScript, so users get interactivity without requiring round-trips to servers and without plugins. GoJS normally runs completely in the browser, rendering to an HTML5 Canvas element or SVG without any server-side requirements. GoJS does not depend on any JavaScript libraries or frameworks, so it should work with any HTML or JavaScript framework or with no framework at all.          

More at http://gojs.net/latest/index.html

Address of the bookmark: http://gojs.net/latest/index.html

]]> Jit https://bioinformaticsonline.com/bookmarks/view/30973/abacas Thu, 16 Feb 2017 12:15:55 -0600 https://bioinformaticsonline.com/bookmarks/view/30973/abacas <![CDATA[ABACAS]]> ABACAS is intended to rapidly contiguate (align, order, orientate) , visualize and design primers to close gaps on shotgun assembled contigs based on a reference sequence. It uses MUMmer to find alignment positions and identify syntenies of assembly contigs against the reference. The output is then processed to generate a pseudomolecule taking overlaping contigs and gaps in to account. MUMmer's alignment generating programs, Nucmer and Promer are used followed by the 'delta-filter' utility function. Users could also run tblastx on contigs that are not used to generate the pseudomolecule. 

Address of the bookmark: http://abacas.sourceforge.net/Manual.html#9._Colour_code

]]> Surabhi Chaudhary https://bioinformaticsonline.com/bookmarks/view/31881/gbtools-interactive-visualization-of-metagenome-bins-in-r Sun, 26 Mar 2017 15:41:31 -0500 https://bioinformaticsonline.com/bookmarks/view/31881/gbtools-interactive-visualization-of-metagenome-bins-in-r <![CDATA[gbtools: Interactive Visualization of Metagenome Bins in R]]> We have developed gbtools, a software package that allows users to visualize metagenomic assemblies by plotting coverage (sequencing depth) and GC values of contigs, and also to annotate the plots with taxonomic information. Different sets of annotations, including taxonomic assignments from conserved marker genes or SSU rRNA genes, can be imported simultaneously; users can choose which annotations to plot. Bins can be manually defined from plots, or be imported from third-party binning tools and overlaid onto plots, such that results from different methods can be compared side-by-side. gbtools reports summary statistics of bins including marker gene completeness, and allows the user to add or subtract bins with each other. 

Tool at https://github.com/kbseah/genome-bin-tools

Address of the bookmark: http://journal.frontiersin.org/article/10.3389/fmicb.2015.01451/full

]]> Jit https://bioinformaticsonline.com/bookmarks/view/35418/karyoploter-plot-whole-genomes-with-arbitrary-data Fri, 02 Feb 2018 03:24:28 -0600 https://bioinformaticsonline.com/bookmarks/view/35418/karyoploter-plot-whole-genomes-with-arbitrary-data <![CDATA[karyoploteR: plot whole genomes with arbitrary data]]> karyoploteR is an R package to create karyoplots, that is, representations of whole genomes with arbitrary data plotted on them. It is inspired by the R base graphics system and does not depend on other graphics packages. The aim of karyoploteR is to offer the user an easy way to plot data along the genome to get broad genome-wide view to facilitate the identification of genome wide relations and distributions.

Address of the bookmark: https://bernatgel.github.io/karyoploter_tutorial/

]]> Abhimanyu Singh https://bioinformaticsonline.com/bookmarks/view/38443/genoplotr-plot-gene-and-genome-maps-project Wed, 12 Dec 2018 08:33:41 -0600 https://bioinformaticsonline.com/bookmarks/view/38443/genoplotr-plot-gene-and-genome-maps-project <![CDATA[genoPlotR - plot gene and genome maps project!]]> genoPlotR is a R package to produce reproducible, publication-grade graphics of gene and genome maps. It allows the user to read from usual format such as protein table files and blast results, as well as home-made tabular files.

Features

  • Linear representation of several segments of DNA
  • Comparisons represented by areas between the segments (like Artemis, for example)
  • Reads from common formats: Genbank, EMBL, blast, Mauve, and from user-generated tab files
  • Plot several subsegments of the same segment on the same line, separated by a //
  • Automatic or manual placement of the segments on the plot
  • Add annotations to all the lines
  • Create smart, automatic annotations for genomes, based on gene names
  • Add a user-generated tree
  • Add a global scale or a scale to each line
  • Use user-defined graphical functions to represent genes

Address of the bookmark: http://genoplotr.r-forge.r-project.org/

]]> Abhimanyu Singh https://bioinformaticsonline.com/bookmarks/view/41487/tinycov-standalone-command-line-utility-written-in-python-to-plot-coverage-from-a-bam-file Mon, 23 Mar 2020 06:22:08 -0500 https://bioinformaticsonline.com/bookmarks/view/41487/tinycov-standalone-command-line-utility-written-in-python-to-plot-coverage-from-a-bam-file <![CDATA[tinycov: standalone command line utility written in python to plot coverage from a BAM file]]> Tinycov is a small standalone command line utility written in python to plot the coverage of a BAM file quickly. This software was inspired by Matt Edwards' genome coverage plotter.

To install the stable version: pip3 install --user tinycov

To install the development version:

git clone https://github.com/cmdoret/tinycov.git
cd tinycov
pip install .

Address of the bookmark: https://github.com/cmdoret/tinycov

]]> Jit https://bioinformaticsonline.com/pages/view/44284/tools-for-geospatial-data-analysis Wed, 22 Mar 2023 02:10:28 -0500 https://bioinformaticsonline.com/pages/view/44284/tools-for-geospatial-data-analysis <![CDATA[Tools for Geospatial data analysis !]]>

Geospatial data is becoming increasingly important in many fields, including urban planning, environmental science, public health, and more. These tools can help you work with data from a variety of sources, including satellite imagery, GPS data, and other forms of spatial data. They can help you visualize data, perform complex analysis, and even create maps and other visualizations.

The list includes some of the most popular and widely used geospatial tools available in Python. These tools can help you work with data from a variety of sources and in a variety of formats. Some of the tools are focused on visualization, such as Cartopy, Folium, and Contextily, which allow you to create interactive maps and other visualizations. Other tools are more focused on data manipulation and analysis, such as Fiona, GeoPandas, and Rasterio, which allow you to manipulate and analyze spatial data in a variety of ways.

The list also includes some tools for working with specific types of geospatial data. For example, the H3 library is designed specifically for working with hexagonal grids, while PySAL is focused on spatial econometrics and spatial analysis. Whether you are a data scientist, GIS specialist, or geospatial enthusiast, these tools are sure to enhance your work and help you achieve your goals.

In summary, this list is an excellent resource for anyone working with geospatial data in Python. It contains a wide range of tools for working with different types of data, and can help you visualize data, perform complex analysis, and create maps and other visualizations. If you're looking to enhance your skills in geospatial analysis, this list is definitely worth checking out.

These tools are:

These tools offer a wide range of capabilities for working with geospatial data, from visualizing and manipulating data to performing complex analysis and modeling. Whether you are a data scientist, GIS specialist, or geospatial enthusiast, these tools are sure to enhance your work and help you achieve your goals.

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