BOL: Related items

IPython: Interactive notebooks

Rahul Nayak — Fri, 07 Nov 2014 12:07:02 -0600

The IPython Notebook is a web-based interactive computational environment where you can combine code execution, text, mathematics, plots and rich media into a single document.

These notebooks are normal files that can be shared with colleagues, converted to other formats such as HTML or PDF, etc. You can share any publicly available notebook by using the IPython Notebook Viewer service which will render it as a static web page. This makes it easy to give your colleagues a document they can read immediately without having to install anything.

To learn more about using the IPython Notebook, you can visit our example collection, and you can read the documentation for all the details on how to use and configure the system. The Notebook Gallery showcases many interesting notebooks covering a variety of topics, from basic programming to advanced scientific computing.

More http://www.nature.com/news/interactive-notebooks-sharing-the-code-1.16261

http://ipython.org/ipython-doc/1/interactive/notebook.html

Reference http://ipython.org/notebook.html

iTOL: Interactive Tree Of Life

Rahul Nayak — Tue, 18 Jul 2017 05:36:51 -0500

Interactive Tree Of Life is an online tool for the display, annotation and management of phylogenetic trees.

Explore your trees directly in the browser, and annotate them with various types of data.

iTOL can easily visualize trees with 50'000 or more leaves. With advanced search capabilities and display of unrooted, circular and regular cladograms or phylograms, exploring and navigating trees of any size is simple.

https://itol.embl.de/

Address of the bookmark: https://itol.embl.de/

Interactive Bioinformatics Resources !

Jit — Thu, 12 Aug 2021 00:09:00 -0500

Learn how to use bioinformatics tools right from your browser.
Everything runs in a sandbox, so you can experiment all you want.

More at sandbox.bio

Address of the bookmark: http://sandbox.bio

S-plot2: creates an interactive, two-dimensional heatmap of sequences

Jit — Fri, 28 Sep 2018 05:36:19 -0500

S-plot2 creates an interactive, two-dimensional heatmap capturing the similarities and dissimilarities in nucleotide usage between genomic sequences (partial or complete). In S-plot2, whole eukaryotic chromosomes and smaller prokaryotic genomes can be efficiently compared. The tool includes functionality to extract, analyze, and automate BLAST queries of regions of interest within the heatmap. This facilitates the investigation of quickly evolving coding regions, novel coding regions, and laterally transferred elements.

http://www.putonti-lab.com/uploads/4/5/3/0/45307835/s-plot2_tutorial.pdf

http://journals.sagepub.com/doi/pdf/10.1177/1176934318797354

Address of the bookmark: https://bitbucket.org/lkalesinskas/splot

dotPlotly: Generate an interactive dot plot from mummer or minimap alignments

Rahul Nayak — Thu, 21 Feb 2019 10:22:17 -0600

Create an interactive dot plot from mummer output OR PAF format

R script that makes a plotly interactive and/or static (png/pdf) dot plot.

Shiny app available for testing

Address of the bookmark: https://github.com/tpoorten/dotPlotly

shinyChromosome:a GUI for the interactive creation of non-circular whole genome diagrams

Jit — Sat, 29 Feb 2020 00:39:50 -0600

shinyChromosome is a graphical user interface for interactive creation of non-circular whole genome diagrams developed using the R Shiny package.

To create single-genome plot by aligning genome data along all chromosomes of a single genome, go to the Single-genome plot menu.

To cretae two-genome plot for comparison of data across two genomes, go to the Two-genome plot menu.

For the detail format of input data, check the Input data format submenu of the Help menu.

shinyChromosome is deployed at http://150.109.59.144:3838/shinyChromosome/, http://shinyChromosome.ncpgr.cn, and https://yimingyu.shinyapps.io/shinyChromosome for online use. The source code and manual of shinyChromosome are freely available at https://github.com/venyao/shinyChromosome.

https://yimingyu.shinyapps.io/shinychromosome/

https://www.sciencedirect.com/science/article/pii/S1672022919301883

Address of the bookmark: https://yimingyu.shinyapps.io/shinychromosome/

scikit-bio™ is an open-source, BSD-licensed, python package providing data structures, algorithms, and educational resources for bioinformatics.

Jit — Fri, 02 Mar 2018 04:29:47 -0600

scikit-bio is currently in beta. We are very actively developing it, and backward-incompatible interface changes can and will arise. To avoid these types of changes being a surprise to our users, our public APIs are decorated to make it clear to users when an API can be relied upon (stable) and when it may be subject to change (experimental). See the API stability docs for more details, including what we mean by stable and experimental in this context.

Address of the bookmark: http://scikit-bio.org/

IgBLAST: a popular NCBI package for classifying and analyzing immunoglobulin (IG) and T cell receptor (TCR) variable domain sequences

BioJoker — Thu, 23 Jan 2020 11:34:37 -0600

NCBI team released a new version of IgBLAST with four new improvements. IgBLAST is a popular NCBI package for classifying and analyzing immunoglobulin (IG) and T cell receptor (TCR) variable domain sequences. Improvements are:

1. Support for the new FWR4 annotation feature in the AIRR format, both in standard format and in the AIRR alignment format.

2. The previous “-penalty” parameter was renamed as -V_penalty to be consistent with other IgBLAST penalty options.

3. Restored constant internal BLAST search parameters for domain annotation (i.e., FWR/CDR) such that this process is not influenced by user parameters.

4. Corrected FWR/CDR annotations for certain mouse VK and rat VH germline genes.

IgBLAST 1.15.0 is available for download from the BLAST FTP area. See the the new manual on GitHub for information about setting up and running IgBLAST.

If you have any questions or concerns, please contact blast-help@ncbi.nlm.nih.gov

Luigi: a Python package that helps you build complex pipelines of batch jobs.

Neel — Thu, 24 Jun 2021 05:43:31 -0500

Luigi is a Python (3.6, 3.7, 3.8, 3.9 tested) package that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization, handling failures, command line integration, and much more.

Run pip install luigi to install the latest stable version from PyPI. Documentation for the latest release is hosted on readthedocs.

Run pip install luigi[toml] to install Luigi with TOML-based configs support.

Address of the bookmark: https://github.com/spotify/luigi

Which are the best statistical programming languages to study for a bioinformatician?

Jitendra Narayan — Wed, 10 Jul 2013 14:35:34 -0500

In Bio-informatics based genome sequencing and predicting metabolic pathways research jobs I used Matlab, SAS, SPSS, R and several Bioconductor packages. Matlab had a lot of powerful tools and was easy to use, whereas SPSS is for non-programmers and R need programming skills. I am wondering what other people think is best? or there might not be one specific language but a few that lend themselves best to Bio-informatics work that is math heavy and deals with a large amount of data.