<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/28200?offset=60 https://bioinformaticsonline.com/bookmarks/view/44279/bioinformatics-training-material Sat, 18 Mar 2023 11:26:18 -0500 https://bioinformaticsonline.com/bookmarks/view/44279/bioinformatics-training-material <![CDATA[Bioinformatics Training Material !]]> Glittr is a curated list of bioinformatics training material.
All material is:

  • In a GitHub or GitLab repository
  • Free to use
  • Written in markdown or similar

NOTE: This list of courses is selected only based on the above criteria.
There are no checks on quality.

https://glittr.org/?per_page=25&sort_by=stargazers&sort_direction=desc

Address of the bookmark: https://glittr.org/?per_page=25&sort_by=stargazers&sort_direction=desc

]]> BioStar https://bioinformaticsonline.com/blog/view/37049/chromomap-an-r-package-for-interactive-visualization-and-mapping-of-human-chromosomes Mon, 25 Jun 2018 17:22:24 -0500 https://bioinformaticsonline.com/blog/view/37049/chromomap-an-r-package-for-interactive-visualization-and-mapping-of-human-chromosomes <![CDATA[chromoMap-An R package for Interactive visualization and mapping of human chromosomes]]> chromoMap is an R package that provides interactive, configurable and elegant graphics visualization of the human chromosomes allowing users to map chromosome elements (like genes, SNPs etc.) on the chromosome plot. It introduces a special plot viz. the "chromosome heatmap" that, in addition to mapping elements, can visualize the data associated with chromosome elements (like gene expression) in the form of heat colors which can be highly advantageous in the scientific interpretations and research work. Because of the enormous size of the chromosomes, it is impractical to visualize each element on the same plot. But chromoMap plots provide a magnified view for each of chromosome location to render additional information and visualization specific for that location. You can map thousands of genes and can view all mappings easily. Users can investigate the detailed information about the mappings (like gene names or total genes mapped on a location) or can view the magnified single or double stranded view of the chromosome at a location showing each mapped element in sequential order (You will see in the demos below). Not ony that, the plots can be saved as HTML documents that can be customized and shared easily. In addition, you can include them in R Markdown or in R Shiny applications.

https://cran.r-project.org/web/packages/chromoMap/index.html

]]> Rahul Nayak https://bioinformaticsonline.com/bookmarks/view/38646/visnetwork-an-r-package-for-network-visualization-using-visjs-javascript-library Wed, 09 Jan 2019 11:00:32 -0600 https://bioinformaticsonline.com/bookmarks/view/38646/visnetwork-an-r-package-for-network-visualization-using-visjs-javascript-library <![CDATA[visNetwork: an R package for network visualization, using vis.js javascript library]]>

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 on htmlwidgets, so :

  • compatible with shiny, R Markdown documents, and RStudio viewer

The package proposes all the features available in vis.js API, and even more with special features for R :

  • easy to use
  • custom shapes, styles, colors, sizes, …
  • works smooth on any modern browser for up to a few thousand nodes and edges
  • interactivity controls (highlight, collapsed nodes, selection, zoom, physics, movement of nodes, tooltip, events, …)
  • visualize rpart tree

Address of the bookmark: https://datastorm-open.github.io/visNetwork/

]]> Jit https://bioinformaticsonline.com/bookmarks/view/39917/chromomap-an-r-package-for-interactive-visualization-and-annotation-of-chromosomes Sat, 07 Sep 2019 10:45:31 -0500 https://bioinformaticsonline.com/bookmarks/view/39917/chromomap-an-r-package-for-interactive-visualization-and-annotation-of-chromosomes <![CDATA[chromoMap-An R package for Interactive Visualization and Annotation of Chromosomes]]> chromoMap provides interactive, configurable and elegant graphics visualization of chromosomes or chromosomal regions allowing users to map chromosome elements (like genes,SNPs etc.) on the chromosome plot.Each chromosome is composed of loci(representing a specific range determined based on chromosome length) that, on hover, shows details about the annotations in that locus range. The plots can be saved as HTML documents that can be shared easily. In addition, you can include them in R Markdown or in R Shiny applications.

Some of the prominent features of the package are:

  • visualizing polyploidy simultaneously on the same plot.
  • annotating groups of elements as distinct colors.
  • creating chromosome heatmaps.
  • adjusting chromosome range or visualizing chromosome regions such as genes
  • adding labels to the plot
  • adding hyperlinks to each element

Address of the bookmark: https://cran.r-project.org/web/packages/chromoMap/vignettes/chromoMap.html

]]> Jit https://bioinformaticsonline.com/bookmarks/view/40964/panev-an-r-package-for-a-pathway-based-network-visualization Sun, 09 Feb 2020 12:41:52 -0600 https://bioinformaticsonline.com/bookmarks/view/40964/panev-an-r-package-for-a-pathway-based-network-visualization <![CDATA[PANEV: an R package for a pathway-based network visualization]]> 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 downstream pathways. The network graph visualization helps to interpret functional profiles of a cluster of genes.

https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-020-3371-7

Address of the bookmark: https://github.com/vpalombo/PANEV

]]> Jit https://bioinformaticsonline.com/news/view/8504/update-genome-workbench-2715-released Wed, 26 Feb 2014 16:12:17 -0600 https://bioinformaticsonline.com/news/view/8504/update-genome-workbench-2715-released <![CDATA[Update Genome Workbench 2.7.15 released]]> NCBI Genome Workbench is an integrated application for viewing and analyzing sequence data. With Genome Workbench, you can view data in publically available sequence databases at NCBI, and mix this data with your own private data.

Introductory screen shot

Genome Workbench can display sequence data in many ways, including graphical sequence views, various alignment views, phylogenetic tree views, and tabular views of data. It can also align your private data to data in public databases, display your data in the context of public data, and retrieve BLAST results.

Genome Workbench is built on the NCBI C++ ToolKit and uses cross-platform APIs for graphics. It runs on your local machine, and is available for Windows 2000/XP, Linux, MacOS X, and various flavors of Unix.

NCBI Genome Workbench is an integrated application for viewing and analyzing sequence data. Genome Workbench was developed entirely in-house at NCBI and makes use of the NCBI C++ ToolKit. The C++ ToolKit provides a convenient and flexible cross-platform API for managing system internals, database connections, network sockets, and the NCBI data model. In addition, the C++ ToolKit provides the Object Manager, which abstracts handling of sequences and sequence-related objects.

 New Features in Genome Workbench 2.7.15

  • Multiple Alignment View: implemented adaptive feature display when zooming in
  • Active Objects Inspector replaces Selection Inspector. New View should offer an improved selection context examination. See Using Active Objects Inspector tutorial for more details.
  • Binary packages for Linux OpenSUSE 13.1 are now available


Bug Fixes and Improvements in Genome Workbench 2.7.15

  • Fixed major issue with OpenGL overlay/scrolling. Could cause crashes or view scrolling irregularities
  • Multiple Pane View: fixed crash on loading BLAST results
  • Graphical Sequence View: fixed crash on zooming in and out, related to SNP track
  • Graphical Sequence View: fixed Go To Position dialog to give better diagnostics in case of a user error
  • Graphical Sequence View: PDF export fixed rendering of Markers with commas in the name
  • Text View / Flat File: fixed Mac OS rendering issues
  • Text View / Flat File: performance optimization, extended capabilities of real-time rendering of molecules to tens of thousands
  • File Import: optimization improvement to speed up load of files containing multiple project items
  • File Import: remapping stage now shows accession.version and description of molecules, instead of plain GI numbers
  • Mac OS: improved tooltips for toolbar buttons
  • Phylogenetic Tree Builder Tool: improved diagnostics of errors
  • Multiple Alignment View: optimizations to avoid main GUI freezes
  • Open Dialog: removed duplicate elements in table of genomes (load Genome)
  • PDF export: fixed issue with XREF table errors
  • Tree View: fixed issues with showing Force Layout progress on Mac OS
  • Tree View: PDF export fixed issues for showing labels of collapsed nodes
  • Tree View: added an option to stop layout
  • Tree View: broadcasting mechanism fixed not to accumulate selected nodes

Reference:

NCBI news

http://www.ncbi.nlm.nih.gov/tools/gbench/

]]> Surabhi Chaudhary https://bioinformaticsonline.com/videolist/watch/14218/pimp-your-brain-bioinformatics Wed, 20 Aug 2014 22:09:21 -0500 https://bioinformaticsonline.com/videolist/watch/14218/pimp-your-brain-bioinformatics <![CDATA[Pimp your brain: Bioinformatics]]> Jan Lisec from the Max Planck Institute of Molecular Plant Physiology explains, in this "pimp your brain" episode, what bioinformatics is and why bioinformatics is so important and indispensable for biological research. In the video serial "Pimp your brain" scientists from the Max Planck Institute of Molecular Plant Physiology describe their research. More videos from the 'Pimp your brain' serial are available on www.youtube.com/playlist?list=PL-l9VItC9Gn2Ur2Xj6PTOAkjLUlVPbIOO More videos are available on www.mpimp-golm.mpg.de]]> https://bioinformaticsonline.com/videolist/watch/19555/a-3d-map-of-the-human-genome Fri, 12 Dec 2014 22:27:55 -0600 https://bioinformaticsonline.com/videolist/watch/19555/a-3d-map-of-the-human-genome <![CDATA[A 3D Map of the Human Genome]]> Suhas Rao and Miriam Huntley (of the Aiden Lab) describe a 3D map of the human genome at kilobase resolution, revealing the principles of chromatin looping. Guest Origami Folding: Sarah Nyquist. Suhas S.P. Rao*, Miriam H. Huntley*, Neva C. Durand, Elena K. Stamenova, Ivan D. Bochkov, James T. Robinson, Adrian L. Sanborn, Ido Machol, Arina D. Omer, Eric S. Lander, Erez Lieberman Aiden. (2014). A 3D Map of the Human Genome at Kilobase Resolution Reveals Principles of Chromatin Looping. Cell.]]> https://bioinformaticsonline.com/pages/view/21365/a-guide-for-complete-r-beginners Fri, 20 Feb 2015 23:36:46 -0600 https://bioinformaticsonline.com/pages/view/21365/a-guide-for-complete-r-beginners <![CDATA[A guide for complete R beginners !]]> This tutorial is intended to introduce users quickly to the basics of R, focusing on a few common tasks that  biologists need to perform  some basic analysis:  load a table, plot some graphs, and perform some basic statistics. More extensive tutorials can be found on the project website and via bioconductor (not covered here).

R-language: http://www.r-project.org

BioConductor: http://www.bioconductor.org

Advantages of R

  • Free!
  • Powerful, many libraries have been created to perform application specific tasks. e.g. analysis of microarray experiments and Next-Gen sequencing (bioconductor: including Bioseq group).
  • Presentation quality graphics
    • Save as a png, pdf or svg
  • History
    • What you do can be saved for the next time you use R.
    • Ability to turn it into an automated script to perform again and again on different data

Disadvantages

Preparation

  • (Optional) Download and save the tutorial data set from
    • http://bioinformatics.knowledgeblog.org/wp-content/uploads/bioinf/kerr/data.tsv
    • Start R (type R on a Linux or Mac terminal, or find the starting link from PC)

Getting More Help

  • Project Home page
    • http://www.r-project.org/
    • Check out the ‘introduction to R’, which is a much more in depth guide .
    • Also R has a built-in help system (see later)

Working directory

This is the directory used to store your data and results. It is useful if it is also the directory where your input data is stored.

  • Mac/Linux: this is the directory where you typed in R
  • PC: Change using the change working directory option
]]> Archana Malhotra https://bioinformaticsonline.com/bookmarks/view/22961/bioscripts Sun, 28 Jun 2015 07:46:14 -0500 https://bioinformaticsonline.com/bookmarks/view/22961/bioscripts <![CDATA[BioScripts]]> You are requested to please bookmark collection of bioinformatics tools, scripts, codes that can be pieced together in a very easy and flexible manner to perform both simple and complex bioinformatics tasks.

The next-generation sequencing included whole genome sequencing(WGS), transcriptome sequencing (whole cDNA sequencing, RNA-seq), digital gene expression sequencing (Tag-Seq), ChIP-Seq, and so on. And there are many sequencing platform to generate sequece, as well know Sanger/ABi(the frist generation), Solexa/illumina, SOLiD/ABi, 454/Roche. But thier sequence format is different, also they have different error type. High quality data is very important for further analysis or data mining. There are many pipeline for raw sequence quality analysis and control with few of process for reporting reads quality statistical details, trimming, filtering, and error correction. Please bookmarks them for the benefits of bioinformatics community.

https://code.google.com/p/biowiki/

https://code.google.com/p/ngs-pipeline/source/browse/#svn%2Ftrunk

NGSand Perl scripts https://code.google.com/hosting/search?q=NGS+perl&projectsearch=Search+projects

NGS and Python scripts https://code.google.com/hosting/search?q=NGS+Python&projectsearch=Search+projects

Address of the bookmark: https://code.google.com/hosting/search?q=bioinformatics&sa=Search

]]> Rahul Nayak