<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/40272?offset=10 https://bioinformaticsonline.com/news/view/14024/grapher Thu, 14 Aug 2014 14:02:17 -0500 https://bioinformaticsonline.com/news/view/14024/grapher <![CDATA[GrapheR !!!]]> What a wonderful gem GrapheR is.... Oh yes it is. GrapheR is a GUI for base graphics in R by http://www.maximeherve.com/. The package provides a graphical user interface for creating base charts in R. It is ideal for beginners in R, as the user interface is very clear and the code is written along side into a text file, allowing users to recreate the charts directly in the console.

Adding and changing legends? Messing around with the plotting window settings? It is much easier/quicker with this GUI than reading the help file and trying to understand the various parameters.
Here is a little example using the iris data set.

library(GrapheR)
data(iris)
run.GrapheR()

This will bring up a window that helps me to create the chart and tweak the various parameters.

image

Finally, I find the underlying R code in a file created by GrapheR. For more details read also the package vignette, which is available in English, French and German!

]]> John Parker https://bioinformaticsonline.com/news/view/14186/pybedtools Wed, 20 Aug 2014 01:03:41 -0500 https://bioinformaticsonline.com/news/view/14186/pybedtools <![CDATA[pybedtools]]> pybedtools is a Python wrapper for Aaron Quinlan's BEDtools programs (https://github.com/arq5x/bedtools), which are widely used for genomic interval manipulation or "genome algebra". pybedtools extends BEDTools by offering feature-level manipulations from with Python. See full online documentation, including installation instructions, at http://pythonhosted.org/pybedtools/.

More at http://pythonhosted.org/pybedtools/

A powerful toolset for genome arithmetic.http://code.google.com/p/bedtools/

]]> Shruti Paniwala https://bioinformaticsonline.com/poll/view/15000/which-mathstatistics-programming-languageapplication-do-you-most-frequently-use-in-bioinformatics Thu, 04 Sep 2014 17:46:41 -0500 https://bioinformaticsonline.com/poll/view/15000/which-mathstatistics-programming-languageapplication-do-you-most-frequently-use-in-bioinformatics <![CDATA[Which math/statistics programming language/application do you most frequently use in bioinformatics?]]> I'm doing a bit more statistical analysis on some bioinformatics things lately, and I'm curious if there are any programming languages that are particularly good for this NGS computation. What suggestions do you guys have? Are there any languages that have exceptionally good libraries?

]]> John Parker https://bioinformaticsonline.com/news/view/22793/sequencing-by-xpansion Wed, 17 Jun 2015 20:58:11 -0500 https://bioinformaticsonline.com/news/view/22793/sequencing-by-xpansion <![CDATA[Sequencing By Xpansion]]> Sequencing By Xpansion (SBX) is a DNA sequencing method that uses a simple biochemical reaction to encode the sequence of a DNA molecule into a highly measurable surrogate called an Xpandomer. This single molecule approach produces enough Xpandomer in a single drop reaction to sequence an entire human genome 1000X over. To achieve this, an Xpandomer replaces each DNA sequence with a sequence of large, high signal reporter molecules using the SBX molecular expansion technology. The DNA sequence is then read out as the Xpandomer reporters pass sequentially through a nanopore detector. SBX is a molecular engineering platform that benefits from core design principles that separate the multiple molecular functions. This systems approach enables efficient development and incorporation of improvements to SBX and is key to reconfiguring and optimizing Xpandomer measurement for different detection platforms.

http://www.stratosgenomics.com/stratos-genomics-technology

]]> Jitendra Narayan 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 https://bioinformaticsonline.com/bookmarks/view/3013/python-and-biopython-tutorial Fri, 23 Aug 2013 06:47:40 -0500 https://bioinformaticsonline.com/bookmarks/view/3013/python-and-biopython-tutorial <![CDATA[Python and BioPython Tutorial]]> A quickstart tutorial that allows to become familiar with the Python language. The exercises expect knowledge of basic concepts of programming. A group of 2nd year computer science students with no previous Python knowledge required 60'-90' to complete the exercises. With about 3 hours time, the exercise is suitable for non-programmers as well.

Address of the bookmark: http://www.biotnet.org/training-materials/python-programmers

]]> Manshi Raghubanshi 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/pages/view/36603/learning-python-programming-a-bioinformatician-perspective Mon, 14 May 2018 16:33:03 -0500 https://bioinformaticsonline.com/pages/view/36603/learning-python-programming-a-bioinformatician-perspective <![CDATA[Learning Python Programming - a bioinformatician perspective !]]> Python Programming is a general purpose programming language that is open source, flexible, powerful and easy to use. One of the most important features of python is its rich set of utilities and libraries for data processing and analytics tasks. In the current era of big biological data, python and biopython is getting more popularity due to its easy-to-use features which supports big data processing.

In this tutorial series article, I will explore features and packages of python which are widely used in the big data, NGS, and bioinformatics. I will also walk through a real biological example which shows NGS data processing with the help of python packages and programming.

Python has a couple of points to recommend it to biologists and scientists specifically:

  • It's widely used in the scientific community
  • It has a couple of very well designed libraries for doing complex scientific computing (although we won't encounter them in this book)
  • It lend itself well to being integrated with other, existing tools
  • It has features which make it easy to manipulate strings of characters (for example, strings of DNA bases and protein amino acid residues, which we as biologists are particularly fond of)

In general, following are some of the important features of python which makes it a perfect fit for rapid application development.

  • Python is interpreted language so the program does not need to be compiled. Interpreter parses the program code and generates the output.
  • Python is dynamically typed, so the variables types are defined automatically.
  • Python is strongly typed. So the developers need to cast the type manually.
  • Less code and more use makes it more acceptable.
  • Python is portable, extendable and scalable.

There are two major Python versions, Python 2 and Python 3. Python 2 and 3 are quite different. This tutorial uses Python 3, because it more semantically correct and supports newer features.

I will post tutorial on daily basis on this page. Check the sub-pages on right side.

]]> Rahul Nayak https://bioinformaticsonline.com/news/view/39606/amity-university-bioinformatics-summer-program-kolkata Tue, 11 Jun 2019 21:27:10 -0500 https://bioinformaticsonline.com/news/view/39606/amity-university-bioinformatics-summer-program-kolkata <![CDATA[Amity University Bioinformatics Summer Program - Kolkata]]> Registrations are now open for the 2019 Summer Bioinformatics Training program at Amity University, Kolkata. The program will focus on introductory topics for life science students. We will review important history, topics and challenges bioinformatics can help address in the context of basic research, discovery and industry.

Read more: https://edu.t-bio.info/amity-university-summer-bioinformatics-program-registrations-are-open/

]]> eliabrodsky https://bioinformaticsonline.com/bookmarks/view/19980/seqloc-06 Sun, 28 Dec 2014 12:51:29 -0600 https://bioinformaticsonline.com/bookmarks/view/19980/seqloc-06 <![CDATA[seqloc 0.6]]> The Bio.SeqLoc modules in seqloc are designed to represent positions and locations (ranges of positions) on sequences, particularly nucleotide sequences. My original motivation for writing these packages was handing the locations of genes in eukaryotic genomes.

Handle sequence locations for bioinformatics http://www.ingolia-lab.org/seqloc-tutorial.html

Address of the bookmark: http://www.stackage.org/snapshot/nightly-2014-12-28/package/seqloc-0.6

]]> Gudiya Pal