BOL: Related items

Programming for Lovers !

BioStar — Tue, 07 Nov 2023 23:56:30 -0600

Programming for Lovers (P4❤️) is a free online course that teaches programming using the Go programming language by immersing learners in fun scientific applications.

Each chapter focuses on a single scientific problem and contains a core text accompanied by code alongs and autograded exercises.

You can meet Phillip Compeau in our intro video. Phillip has taught programming at Carnegie Mellon University for years and is a serial online education founder. He is thrilled to bring you this course.

Address of the bookmark: https://programmingforlovers.com/

Which math/statistics programming language/application do you most frequently use in bioinformatics?

John Parker — Thu, 04 Sep 2014 17:46:41 -0500

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?

Perl One liner basics !!

Abhimanyu Singh — Sun, 24 May 2015 09:28:33 -0500

Perl has a ton of command line switches (see perldoc perlrun), but I'm just going to cover the ones you'll commonly need to debug code. The most important switch is -e, for execute (or maybe "engage" :) ). The -e switch takes a quoted string of Perl code and executes it. For example:

$ perl -e 'print "Hello, World!\n"'
Hello, World!

It's important that you use single-quotes to quote the code for -e. This usually means you can't use single-quotes within the one liner code. If you're using Windows cmd.exe or PowerShell, you must use double-quotes instead.

I'm always forgetting what Perl's predefined special variables do, and often test them at the command line with a one liner to see what they contain. For instance do you remember what $^O is?

$ perl -e 'print "$^O\n"'
linux

It's the operating system name. With that cleared up, let's see what else we can do. If you're using a relatively new Perl (5.10.0 or higher) you can use the -E switch instead of -e. This turns on some of Perl's newer features, like say, which prints a string and appends a newline to it. This saves typing and makes the code cleaner:

$ perl -E 'say "$^O"'
linux

Pretty handy! say is a nifty feature that you'll use again and again.

Frequent words problem solution by Perl

Jit — Tue, 09 Jun 2015 23:38:44 -0500

Solved with perl http://rosalind.info/problems/1a/

#Find the most frequent k-mers in a string.
#Given: A DNA string Text and an integer k.
#Return: All most frequent k-mers in Text (in any order).

use strict;
use warnings;

my $string="ACGTTGCATGTCGCATGATGCATGAGAGCT";
my $kmer=4;
my %myHash;
my $max=0;

for (my $aa=0; $aa<=(length($string)-4); $aa++) {
   my $myStr=substr $string, $aa,$kmer;
   #print "$myStr\n";
   my $km=kmerMatch ($string, $myStr, $kmer);
   if ($km > $max) { $max = $km;}
   #print "$km\t$myStr\n";
   $myHash{$myStr}=$km;

}

#Print all key which have matching values
foreach my $name (keys %myHash){
    print "$name " if $myHash{$name} == $max;
}

sub kmerMatch { #Check the exact matching kmers with sliding window
my ($string, $myStr, $kmer)=@_;
my $count=0;
for (my $aa=0; $aa<=(length($string)-4); $aa++) {
   my $myWin=substr $string, $aa,$kmer;
   if ($myWin eq $myStr) {
       #print "$myWin eq $myStr\n";
       $count++;
   }
}
return $count;
}

Clump Finding Problem Solved with Perl

Jit — Wed, 10 Jun 2015 00:17:17 -0500

The question at http://rosalind.info/problems/1d/

Script are moved to http://bioinformaticsonline.com/snippets/view/34633/clump-finding-problem-solved-with-perl

Bioinformatics Made Easy Search: Bioinformatics tools and run genomic analysis in the cloud

Rahul Nayak — Thu, 20 Aug 2015 02:21:20 -0500

InsideDNA makes hundreds of bioinformatics tools immediately available to run via an easy-to-use web interface and allows an accurate search across all functions, tools and pipelines.

With InsideDNA, you can upload and store your own genomic/genetic datasets in a limitless cloud space, and instantly analyze it with a powerful compute instance, without any tool installation or set up hassle.

More at https://insidedna.me/

Address of the bookmark: https://insidedna.me/

Genome Browser : GBrowse

Jit — Fri, 19 Feb 2016 09:22:43 -0600

Generic Genome Browser Version 2: A Tutorial for Administrators

This is an extensive tutorial to take you through the main features and gotchas of configuring GBrowse as a server. This tutorial assumes that you have successfully set up Perl, GD, BioPerl and the other GBrowse dependencies. If you haven't, please see the GBrowse HOWTO During most of the tutorial, we will be using the "in-memory" GBrowse database (no relational database required!) Later we will show how to set up a genome size database using the berkeleydb and MySQL adaptors.

More at http://elp.ucdavis.edu/tutorial/tutorial.html

Address of the bookmark: http://elp.ucdavis.edu/tutorial/tutorial.html

scikit-learn

Jitendra Prajapati — Mon, 29 Feb 2016 17:39:24 -0600

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

bipype

Jit — Thu, 01 Dec 2016 08:47:38 -0600

Bipype is a very useful program, which prepare a lot of types of bioinformatics analyses. There are three input options: amplicons, WGS (whole genome sequences) and metatranscriptomic data. If amplicons are input data, then bipype does reconstruction and pairs merging. After that biodiversity is searching. There are two types of searching depending on the amplicons types (ITS or 16S). If WGS are chosen, then bipype finds the SA coordinates of the input reads and generates alignments in the SAM format given single-end reads, aligns reads to reference sequence(s). All of these analyses will be shown with Krona program, which allows to show hierarchical data with pie charts.

Address of the bookmark: https://readthedocs.org/projects/bipype/

NGS teaching material

Jit — Wed, 05 Apr 2017 04:29:06 -0500

High throughput sequencing (HTS) technologies are being applied to a wide range of important topics in biology. However, the analyses of non-model organisms, for which little previous sequence information is available, pose specific problems. This course addresses the specific strengths and weaknesses of alternative HTS technologies, the computational resources needed for HTS, and how to analyze non-model species using HTS. The course consists of a practical training module, HTS bioinformatics training, and lecturing/seminars of HTS approaches specifically targeting non-model organisms.

Address of the bookmark: http://marinetics.org/teaching/hts/Assembly.html