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For a beginner this can be is the hardest part, it is also the most important to get right. It is possible to create a vector by typing data directly into R using the combine function ‘c’ x same as x creates the vector x...

An API for Embedded Scientific Computing

userweb.eng.gla.ac.uk - The purpose of this tutorial is to introduce students to the frequently used tools for NGS analysis as well as giving experience in writing one-liners. Copy the required files to your current directory, change directory (cd) to the linuxTutorial...

www.homolog.us - These tutorials are written for hundreds of bioinformaticians trying to cope with large volume of next-generation sequencing (NGS) data. NGS technologies brought a dramatic shift in the world of sequencing. Merely five years back, genome sequencing...

Short term perl training for geneticist

github.com - SNPGenie is a Perl script for estimating evolutionary parameters, mainly from pooled next-generation sequencing (NGS) single-nucleotide polymorphism (SNP) variant data. SNP reports (acceptable in a variety of formats) much each correspond to a...

Perl's second wave of adoption came from the growth of the world wide web. Dynamic web pages—the precursor to modern web applications—were easy to create with Perl and CGI. Thanks to Perl's ubiquity as a language for system...

manuals.bioinformatics.ucr.edu - 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...

The benchmark module is a great tool to know the time the code takes to run. The output is usually in terms of CPU time. This module provides us with a way to optimize our code. With the advent of petascale computing and other multicore processor it...

wikis.utexas.edu - The Integrative Genomics Viewer (IGV) from the Broad Center allows you to view several types of data files involved in any NGS analysis that employs a reference genome, including how reads from a dataset are mapped, gene annotations, and predicted...