<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/39441?offset=380 https://bioinformaticsonline.com/bookmarks/view/26539/scikit-learn Mon, 29 Feb 2016 17:39:24 -0600 https://bioinformaticsonline.com/bookmarks/view/26539/scikit-learn <![CDATA[scikit-learn]]> Machine Learning in Python

Simple and efficient tools for data mining and data analysis
Accessible to everybody, and reusable in various contexts
Built on NumPy, SciPy, and matplotlib
Open source, commercially usable - BSD license

More at http://scikit-learn.org/stable/index.html

 

Address of the bookmark: http://scikit-learn.org/stable/auto_examples/index.html

]]> Jitendra Prajapati https://bioinformaticsonline.com/pages/view/35805/python-learning-resources-for-bioinformatics-and-computational-biologist Fri, 02 Mar 2018 06:54:15 -0600 https://bioinformaticsonline.com/pages/view/35805/python-learning-resources-for-bioinformatics-and-computational-biologist <![CDATA[Python learning resources for bioinformatics and computational biologist !]]> Python is a general-purpose language, which means it can be used to build just about anything, which will be made easy with the right tools/libraries.

Professionally, Python is great for backend web development, data analysis, artificial intelligence, and scientific computing. Many developers have also used Python to build productivity tools, games, and desktop apps, so there are plenty of resources to help you learn how to do those as well.

For pros and cons visit http://www.bestprogramminglanguagefor.me/why-learn-python and http://bioinformaticsonline.com/discussion/view/459/python-vs-perl

More resources at https://github.com/CodementorIO/Python-Learning-Resources

Following are the list of useful python programming resources:

]]> Jit https://bioinformaticsonline.com/bookmarks/view/40221/dash-a-web-application-framework-that-provides-pure-python-abstraction-around-html-css-and-javascript Tue, 05 Nov 2019 06:39:48 -0600 https://bioinformaticsonline.com/bookmarks/view/40221/dash-a-web-application-framework-that-provides-pure-python-abstraction-around-html-css-and-javascript <![CDATA[Dash: a web application framework that provides pure Python abstraction around HTML, CSS, and JavaScript.]]> Dash is a web application framework that provides pure Python abstraction around HTML, CSS, and JavaScript.

Dash Bio is a suite of bioinformatics components that make it simpler to analyze and visualize bioinformatics data and interact with them in a Dash application.

The source can be found on GitHub at plotly/dash-bio.

These docs are using Dash Bio version 0.1.4.

Address of the bookmark: https://dash.plot.ly/dash-bio

]]> Jit https://bioinformaticsonline.com/bookmarks/view/43101/luigi-a-python-package-that-helps-you-build-complex-pipelines-of-batch-jobs Thu, 24 Jun 2021 05:43:31 -0500 https://bioinformaticsonline.com/bookmarks/view/43101/luigi-a-python-package-that-helps-you-build-complex-pipelines-of-batch-jobs <![CDATA[Luigi: a Python package that helps you build complex pipelines of batch jobs.]]> 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

]]> Neel https://bioinformaticsonline.com/bookmarks/view/35800/scikit-bio%E2%84%A2-is-an-open-source-bsd-licensed-python-package-providing-data-structures-algorithms-and-educational-resources-for-bioinformatics Fri, 02 Mar 2018 04:29:47 -0600 https://bioinformaticsonline.com/bookmarks/view/35800/scikit-bio%E2%84%A2-is-an-open-source-bsd-licensed-python-package-providing-data-structures-algorithms-and-educational-resources-for-bioinformatics <![CDATA[scikit-bio™ is an open-source, BSD-licensed, python package providing data structures, algorithms, and educational resources for bioinformatics.]]> 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/

]]> Jit 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/bookmarks/view/39720/snakemake-workflow-dna-seq-gatk-variant-calling Thu, 25 Jul 2019 12:55:07 -0500 https://bioinformaticsonline.com/bookmarks/view/39720/snakemake-workflow-dna-seq-gatk-variant-calling <![CDATA[Snakemake workflow: dna-seq-gatk-variant-calling]]> This Snakemake pipeline implements the GATK best-practices workflow for calling small genomic variants.

Address of the bookmark: https://github.com/snakemake-workflows/dna-seq-gatk-variant-calling

]]> Jit https://bioinformaticsonline.com/bookmarks/view/43290/the-snakemake-wrappers-repository Thu, 19 Aug 2021 04:39:34 -0500 https://bioinformaticsonline.com/bookmarks/view/43290/the-snakemake-wrappers-repository <![CDATA[The Snakemake Wrappers repository]]> The Snakemake Wrapper Repository is a collection of reusable wrappers that allow to quickly use popular tools from Snakemake rules and workflows.

More at https://github.com/snakemake/snakemake-wrappers

Address of the bookmark: https://snakemake-wrappers.readthedocs.io/en/stable/

]]> BioStar https://bioinformaticsonline.com/bookmarks/view/43863/snakemake-tutorials Mon, 09 May 2022 05:20:41 -0500 https://bioinformaticsonline.com/bookmarks/view/43863/snakemake-tutorials <![CDATA[Snakemake Tutorials !]]> A lesson introducing the Snakemake workflow system for bioinformatics analysis.

Prerequisites

This is an intermediate lesson and assumes learners have already done some bioinformatics:

  • Familiarity with the BASH command shell, including concepts like pipes, variables and loops.
  • Knowledge of bioinformatics fundamentals like the FASTQ file format and transcriptome sequencing, in order to understand the example workflow.

No previous knowledge of Snakemake or workflow systems is required.

https://carpentries-incubator.github.io/snakemake-novice-bioinformatics/index.html

Address of the bookmark: https://carpentries-incubator.github.io/snakemake-novice-bioinformatics/aio/index.html

]]> Rahul Nayak https://bioinformaticsonline.com/bookmarks/view/38039/vgsc-a-web-based-vector-graph-toolkit-of-genome-synteny-and-collinearity Tue, 30 Oct 2018 10:46:28 -0500 https://bioinformaticsonline.com/bookmarks/view/38039/vgsc-a-web-based-vector-graph-toolkit-of-genome-synteny-and-collinearity <![CDATA[VGSC: A Web-Based Vector Graph Toolkit of Genome Synteny and Collinearity]]> VGSC, the Vector Graph toolkit of genome Synteny and Collinearity, and its online service, to visualize the synteny and collinearity in the common graphical format, including both raster (JPEG, Bitmap, and PNG) and vector graphic (SVG, EPS, and PDF). 

Address of the bookmark: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4783527/

]]> Abhimanyu Singh