BOL: Related items

Installing Perl GD Module

Jit — Mon, 22 Jul 2013 14:02:01 -0500

In comparative genome analysis work, we usually compare more than two genomes and looks for syntenic regions amongst them. In my research I used Evolution Highway (RH) http://eh-demo.ncsa.uiuc.edu/, which is a collaborative project designed to provide a visual means for simultaneously comparing genomes of multiple amniote species. The tool removes the burden of manually aligning these maps and allows cognitive skills to be used toward something more valuable than preparation and transformation of data. In addition to EH, attractive Circos (http://circos.ca/) is also very popular for this kind of analysis.

The EH is available online, and can be easily access and use, whereas Circos installation is not entirely straightforward. One of the most difficult parts of the installation involves installing the GD library. Since there weren't good instructions for installing this library on the internet I decided to post instructions here in case they are useful to anyone else.

Following are the steps to install GD modules in Mac OS

1. Setup

Create a folder for the files:

$ mkdir -p /SourceCache
$ cd /SourceCache

Get and unpack the required Jpeg-6b and GD libraries:
Download Jpeg-6b (http://code.google.com/p/google-desktop-for-linux-mirror/downloads/detail?name=jpeg-6b.tar.gz&can=2&q)
Download GD (http://search.cpan.org/~lds/GD-2.46/)

Place the "tar.gz" files in "/SourceCache" and double click to unpack.

2. Install libjpeg

Copy the "config.sub" and "config.guess" files to "/SourceCache". Note that your "config.sub" and ""config.guess" files may be in a slightly different location. The commands below show where they were on my machine:

$ cd /SourceCache/jpeg-6b/src
$ cp /usr/share/libtool/config/config.sub .
$ cp /usr/share/libtool/config/config.guess .

Configure libjpeg as follows. Note that this was installed on a 64 bit machine. However, this method may configure it in a 32 bit format. This may not be the best way to configure the installation but it works.

$ .configure --enable-shared
$ make

Check to see if the following directories exist on your machine. Create the missing directories in the following manner:

$ mkdir -p /usr/local/include
$ mkdir -p /usr/local/bin
$ mkdir -p /usr/local/lib
$ mkdir -p /usr/local/man/man1

Finish making and installing libjpeg:

$ make install

3. Install GD

$ cd /SourceCache/GD-2.46/GD/
$ perl Makefile.PL
$ make
$ make test (optional)
$ make html (optional)
$ make install

Other way for Mac OS
The easiest way to get a lot of these is with a program called Fink, which is similar in nature to the CPAN installer, but installs common GNU utilities. Fink is available from <http://sourceforge.net/projects/fink/>.

Follow the instructions for setting up Fink. Once it's installed, you'll want to run the following as root: fink install gd

It will prompt you for a number of dependencies, type 'y' and hit enter to install all of the dependencies. Then watch it work.

To prevent creating conflicts with the software that Apple installs by default, Fink creates its own directory tree at /sw where it installs most of the software that it installs. This means your libraries and headers for libgd will be at /sw/lib and /sw/include instead of /usr/lib and /usr/local/include. Because of these changed locations for the libraries, the Perl GD module will not install directly via CPAN, because it looks for the specific paths instead of getting them from your environment. But there's a way around that :-)

Instead of typing "install GD" at the cpan> prompt, type look GD. This should go through the motions of downloading the latest version of the GD module, then it will open a shell and drop you into the build directory. Apply below patch to the Makefile.PL file (save the patch into a file and use the command patch < patchfile.)

Then, run these commands to finish the installation of the GD module:

perl Makefile.PL
make
make test
make install
And don't forget to run exit to get back to CPAN.

Install on MS Window, using PPM

C:\Documents and Settings\Owner>ppm
PPM interactive shell (2.2.0) - type 'help' for available commands.
PPM> install GD
Install package 'GD?' (y/N): y
Installing package 'GD'...
Downloading http://ppm.ActiveState.com/PPMPackages/5.6plus/MSW. ...
Installing C:\Perl\site\lib\auto\GD\GD.bs
Installing C:\Perl\site\lib\auto\GD\GD.dll
Installing C:\Perl\site\lib\auto\GD\GD.exp
Installing C:\Perl\site\lib\auto\GD\GD.lib
Installing C:\Perl\html\site\lib\GD.html
Installing C:\Perl\site\lib\GD.pm
Installing C:\Perl\site\lib\qd.pl
Installing C:\Perl\site\lib\auto\GD\autosplit.ix
PPM>

If you can't install it from ppm. You can download it:
http://ppm.ActiveState.com/PPMPackages/5.6plus/MSW.

BTW,All Perl 5.6.1 Modules are located at:

http://ppm.ActiveState.com/PPMPackages/5.6plus/MSW.

Install the Perl GD Module on Linux

$ sudo perl -MCPAN -e shell

Since it was the first time I had run this command on this particular machine I had to answer a lot of questions but simply selected the defaults for everything as this usually works for me. Once in the CPAN shell I entered

$ install Bundle::CPAN

and selected all of the defaults again. Once the CPAN bundle had finished installing I tried to install GD::Graph by typing

$ install GD::Graph

but it failed with hundreds of errors – the first of which was

GD.xs:7:16: error: gd.h: No such file or directory

This was fixed with the following apt-get command (in the bash shell)

$ sudo apt-get install libgd2-xpm-dev

back in the CPAN shell I still couldn’t get GD::Graph to build and I guessed this was because of some left over files from the failed build. I don’t know the command to clean things up inside the CPAN shell and am too lazy to read the docs so I simply went into the .cpan/build directory in my home directory and deleted anything that started with GD – eg

$ rm -rf GD-2.35-HC_vkB

$ rm -rf GDGraph-1.44-Evfibe

and so on. Those strings at the end (VkB and so on) look random so they might be different on your machine. Then I went back into the CPAN shell and ran

$ install GD::Graph

There were a few dependencies which the script fetched and installed for me but everything worked smoothly.

Manual and other Perl Module instalation are mentioned in my previous blog @ http://bioinformaticsonline.com/blog/view/710/how-to-install-perl-modules-manually-using-cpan-command-and-other-quick-ways

Next Generation Sequencing (NGS) Tutorials

Jitendra Narayan — Sat, 24 Aug 2013 06:01:37 -0500

Institute of computational biomedicine, Cornell University provide an NGS workshop tutorial at http://chagall.med.cornell.edu/NGScourse/

You can also add your favourite NGS educational material, or workshop tutorial by commenting on this bookmarks for user benefit.

Understanding the basics of genome sequencing:

Tutorial by Luke Jostins.

http://www.genetic-inference.co.uk/blog/2009/04/basics-sequencing-dna-part-1/

http://www.genetic-inference.co.uk/blog/2009/08/basics-sequencing-dna-part-2/

A window into third-generation sequencing

http://hmg.oxfordjournals.org/content/19/R2/R227.full.pdf

==============================================

NGS data analysis pipelines

Detecting and annotating genetic variations using the HugeSeq pipeline DOI: 10.1038/nbt.2134
NARWHAL, a primary analysis pipeline for NGS data http://bioinformatics.oxfordjournals.org/cgi/content/abstract/28/2/284?etoc
RseqFlow: Workflows for RNA-Seq data analysis DOI: 10.1093/bioinformatics/btr441
ngs_backbone: a pipeline for read cleaning, mapping and SNP calling using Next Generation Sequence 10.1186/1471-2164-12-285
A framework for variation discovery and genotyping using next-generation DNA sequencing data PubMed: 21478889
SNiPlay: a web-based tool for detection, management and analysis of SNPs. Application to grapevine diversity projects DOI: 10.1186/1471-2105-12-134 Abstract: http://www.biomedcentral.com/1471-2105/12/134/abstract
WEP: a high-performance analysis pipeline for whole-exome data http://www.biomedcentral.com/1471-2105/14/S7/S11
DDBJ read annotation pipeline: a cloud computing-based pipeline for high-throughput analysis of next-generation sequencing data. http://www.ncbi.nlm.nih.gov/pubmed/23657089
GATK: a Toolkit for Genome Analysis http://www.broadinstitute.org/gatk/
Metagenomics:http://www.nbic.nl/education/nbic-phd-school/course-schedule/ngsmetagenomics/
RNASeq:http://www.nbic.nl/education/nbic-phd-school/course-schedule/ngsrnaseq/
Bioinformatics and Seq courses: http://www.isb-sib.ch/training/training-activities-schedule/archive-2013.html
Variant Detection (Model organism) Advanced tutorial https://docs.google.com/document/pub?id=1CuKkKylVDb03tnN7RSWl5EUzleetn0ctjmvaidPKLxM
Variant Detection Introductory tutorial https://docs.google.com/document/pub?id=1ZRzrjjOCvtAu3m-IKL-rbJ1f4On60dDL_IEwG7oejdI
Microbial de novo Assembly for Illumina Data Introductory tutorial https://docs.google.com/document/pub?id=1N3AB9ptISUu4zULqe1kXpVF0BDyGb5f5yzxWSJd_WNM
RNAseq Differential Gene Expression Introductory tutorial https://docs.google.com/document/pub?id=1KbTiBHtvHLfPRZ39AY3uriazrINA8TJzgjjwn1zPP7Y

" Please add your favourite NGS link below in comment section for the benefit of bioinformatics community ".

Address of the bookmark: http://chagall.med.cornell.edu/NGScourse/

Scaffolding of a bacterial genome using MinION nanopore sequencing

Rahul Agarwal — Tue, 07 Jul 2015 16:59:25 -0500

Second generation sequencing has revolutionized genomic studies. However, most genomes contain repeated DNA elements that are longer than the read lengths achievable with typical sequencers, so the genomic order of several generated contigs cannot be easily resolved. A new generation of sequencers offering substantially longer reads is emerging, notably the Pacific Biosciences (PacBio) RS II system and the MinION system, released in early 2014 by Oxford Nanopore Technologies through an early access program.

Address of the bookmark: http://www.nature.com/srep/2015/150707/srep11996/full/srep11996.html

Live Webinar on RNA-Seq Data Analysis on 9 Nov 2016

Strand — Wed, 19 Oct 2016 05:25:27 -0500

Live Webinar on RNA-Seq Data Analysis

Abstract: Strand NGS supports an extensive workflow for the analysis and visualization of RNA-Seq data. The workflow includes Transcriptome / Genome alignment, Differential expression analysis with Statistical approach and Splicing events detection. Strand NGS also supports novel discovery like identification of novel genes, exons and Novel splice junctions, alongside it can also detect gene fusion events. Further downstream analysis such as GO and pathway analysis can be performed on the set of interesting genes. The product has an option to create pipelines for time consuming jobs which automates analysis and leaves more time for end data interpretation. This webinar will give an overview of the features in the RNA-Seq data analysis workflow in Strand NGS and also highlights on parameters within each feature that can be optimized depending on datasets and analysis needs.

Speaker: Mr. Sugandan Sivamani, Senior Application Scientist, Strand Life Sciences

Date: 9th Nov, Session 1 for SAPK/ APFO: 2:30 PM IST Date: 9th Nov, Session 2 for AFO/ EMEA: 9:00 AM PST

Quick next generation sequencing (NGS) terms definition

Neel — Fri, 09 Jun 2017 04:52:26 -0500

fragment size: the Illumina WGS protocol generates paired-end reads from both ends of longer fragments. The lengths of these fragments are assumed to be sampled from a normal distribution. Therefore, in the absence of structural variants, mapping locations of the paired ends span within an interval [δmin,δmax]. Most (>90%) of paired-end reads are sampled from no-SV regions, therefore the fragment size distribution can be learned empirically for each WGS data set separately.

concordant reads: a read pair is called concordant if they can be mapped to the reference genome as “expected”: (a) mapped to opposing strands where the upstream read is mapped to the forward strand and the downstream read is mapped to the reverse strand2, (b) the distance between ends is between the minimum and maximum expected fragment size.

discordant reads: briefly, any non-concordant read pair is considered discordant. Note that, by definition, the discordant read pairs signal potential SVs. The sequence signature produced by these type of reads is known as read-pair signature.

split reads: a read that can only be mapped to the reference genome by breaking into two sub-reads is called a split-read. These types of reads also indicate a potential SV or a short insertion or deletion (indel).

read depth: number of reads that map within a region of the genome. Overall genome-wide read depth is also referred to as depth of coverage. It is expected that the number of reads that “cover” each base-pair to follow a Poisson distribution. Therefore, if the read depth over a certain region deviates significantly from this distribution, it signals for a potential copy number variation (CNV).

XAMPP: Starting Apache fail Ubuntu

Ram Yash Pal — Sat, 07 Jun 2014 05:52:35 -0500

Once you install XAMMP on linux, the most common problem you face is Apache failure. To fix the issues please use following command to first stop and then again start it.

sudo /etc/init.d/apache2 stop

sudo /etc/init.d/mysql stop

sudo /etc/init.d/proftpd stop

sudo /opt/lampp/lampp start

PhpMyAdmin “Wrong permissions on configuration file, should not be world writable!”

Once the Xammp is installed, it might be possible to set up the configuration file in writable mode. Try the following steps:

Just chmod 0755 the file

sudo chmod 0755 config.inc.php

MeDuSa: a multi-draft based scaffolder

Abhimanyu Singh — Wed, 14 Feb 2018 02:49:00 -0600

MeDuSa (Multi-Draft based Scaffolder), an algorithm for genome scaffolding. MeDuSa exploits information obtained from a set of (draft or closed) genomes from related organisms to determine the correct order and orientation of the contigs. MeDuSa formalises the scaffolding problem by means of a combinatorial optimisation formulation on graphs and implements an efficient constant factor approximation algorithm to solve it. In contrast to currently used scaffolders, it does not require either prior knowledge on the microrganisms dataset under analysis (e.g. their phylogenetic relationships) or the availability of paired end read libraries.

Address of the bookmark: https://github.com/combogenomics/medusa

Porechop: tool for finding and removing adapters from Oxford Nanopore reads

Rahul Nayak — Tue, 29 May 2018 07:33:44 -0500

Porechop is a tool for finding and removing adapters from Oxford Nanopore reads. Adapters on the ends of reads are trimmed off, and when a read has an adapter in its middle, it is treated as chimeric and chopped into separate reads. Porechop performs thorough alignments to effectively find adapters, even at low sequence identity.

Porechop also supports demultiplexing of Nanopore reads that were barcoded with the Native Barcoding Kit, PCR Barcoding Kit or Rapid Barcoding Kit.

Address of the bookmark: https://github.com/rrwick/Porechop

RNA-seq Analysis Workshop Course Materials

Jit — Tue, 03 Jul 2018 08:14:14 -0500

RNAseq can be roughly divided into two "types": Reference genome-based - an assembled genome exists for a species for which an RNAseq experiment is performed. It allows reads to be aligned against the reference genome and significantly improves our ability to reconstruct transcripts. This category would obviously include humans and most model organisms but excludes the majority of truly biologically intereting species (e.g., Hyacinth macaw); Reference genome-free - no genome assembly for the species of interest is available. In this case one would need to assemble the reads into transcripts using de novo approaches. This type of RNAseq is as much of an art as well as science because assembly is heavily parameter-dependent and difficult to do well. In this lesson we will focus on the Reference genome-based type of RNA seq. http://chagall.med.cornell.edu/RNASEQcourse/

Address of the bookmark: http://chagall.med.cornell.edu/RNASEQcourse/

Convert EnsEMBL GTF to Annotation table (Geneid, GeneSymbol, GeneWiseChrLocation, GeneClass, Strand) Raw

EagleEye — Fri, 24 Jun 2016 18:08:49 -0500

Bash Script source:

https://gist.github.com/santhilalsubhash/367befcf5216be4b1fd9

Information:

This script converts EnsEMBL GTF (Ex: https://gist.githubusercontent.com/santhilalsubhash/1e7cca357e52a181dc25/raw/cfb803e07900a2baefbb6534f1299fd30cb57a29/sample.GTF) file to annotation table format. It generated two files
1) Transcript wise chromosome location with information about transcripts (Ex: https://gist.githubusercontent.com/santhilalsubhash/c7dec516e0338503a4b6/raw/de0af1a39f0005c4ce7321c5ae57fc8b4a14c7f4/sample.GTF_enst_annotation.txt)
2) Gene wise chromosome location with information about genes (Ex: https://gist.githubusercontent.com/santhilalsubhash/c92006c5080f0333bec2/raw/d16e0b2440d73b09b486d3c9751cdb248a73fa0b/sample.GTF_ensg_annotation.txt)

Note: You can download GTF files from http://www.ensembl.org/info/data/ftp/index.html