BOL: Related items

Sequencing By Xpansion

Jitendra Narayan — Wed, 17 Jun 2015 20:58:11 -0500

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

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

SRF Bioinformatics job position in National Institute of Plant Genome Research (NIPGR)

Mon, 19 Sep 2016 05:43:38 -0500

SRF Bioinformatics job position in National Institute of Plant Genome Research (NIPGR)
Title : “Transcriptome and small RNA diversity analysis of developing seed contrasting rice varieties”
Qualification : Candidates having M.Sc./M.Tech. degree or equivalent (with minimum 60% marks) in Bioinformatics with a minimum of two years of post M.Sc./M.Tech research experience are eligible to apply.
No. of Post : 01
How to apply
Application should reach to Dr. Pinky Agarwal, Staff Scientist, National Institute of Plant Genome Research (NIPGR) Aruna Asaf Ali Marg, P.O. Box NO. 10531, New Delhi - 110067 on or before 30/09/2016

More at http://www.nipgr.res.in/careers/vacancies_latest.php#

Strudel

Anjana — Fri, 30 Sep 2016 09:47:02 -0500

Strudel is our graphical tool for visualizing genetic and physical maps of genomes for comparative purposes. The application aims to let the user examine their data at a variety of different levels of resolution, from entire maps to individual markers, and explore syntenic relationships between genomes. All browsing and interaction with Strudel happens in real-time – there is no need to wait while the maps are generated. It is built using Java 1.6 and ships with its own JRE, so there is no need for users to install or update Java.

Address of the bookmark: https://ics.hutton.ac.uk/strudel/

MIRO : miRNA omics

Jit — Tue, 04 Oct 2016 14:50:48 -0500

The MIRO (the miRNA omics) pipeline is a flexible and powerful tool for the analysis of miRNA (or more generall short RNA) expression using short-read deep sequencing data. In its present implementation MIRO is especially adapted for the analysis of reads generated with the Illumina sequencing platform. MIRO allows to preprocess the Solexa-reads, map them flexibly to several reference genomes using one of four different mappers, create differential gene (miRNA) expression profiles and cluster reads using one of several algorithm. MIRO output is furthermore compatible with software such as genome browsers and miRDeep.

Address of the bookmark: http://seq.crg.es/download/software/Miro/

Cgaln

Jit — Wed, 22 Feb 2017 05:14:15 -0600

Cgaln (Coarse grained alignment) is a program designed to align a pair of whole genomic sequences of not only bacteria but also entire chromosomes of vertebrates on a nominal desktop computer. Cgaln performs an alignment job in two steps, at the block level and then at the nucleotide level. The former "coarse-grained" alignment can explore genomic rearrangements and reduce the regions to be analyzed in the next step. The latter is devoted to detailed alignment within the limited regions found in the first stage. The output of Cgaln is 'glocal' in the sense that rearrangements are taken into consideration while each alignable region is extended as long as possible. Thus, Cgaln is not only fast and memory-efficient, but also can filter noisy outputs without missing the most important homologous segment pairs.

http://www.iam.u-tokyo.ac.jp/chromosomeinformatics/rnakato/cgaln/

Address of the bookmark: http://www.iam.u-tokyo.ac.jp/chromosomeinformatics/rnakato/cgaln/

gbtools: Interactive Visualization of Metagenome Bins in R

Jit — Sun, 26 Mar 2017 15:41:31 -0500

We have developed gbtools, a software package that allows users to visualize metagenomic assemblies by plotting coverage (sequencing depth) and GC values of contigs, and also to annotate the plots with taxonomic information. Different sets of annotations, including taxonomic assignments from conserved marker genes or SSU rRNA genes, can be imported simultaneously; users can choose which annotations to plot. Bins can be manually defined from plots, or be imported from third-party binning tools and overlaid onto plots, such that results from different methods can be compared side-by-side. gbtools reports summary statistics of bins including marker gene completeness, and allows the user to add or subtract bins with each other.

Tool at https://github.com/kbseah/genome-bin-tools

Address of the bookmark: http://journal.frontiersin.org/article/10.3389/fmicb.2015.01451/full

DESCHRAMBLER

Jit — Thu, 29 Jun 2017 11:54:59 -0500

DESCHRAMBLER is shown to produce highly accurate reconstructions using data simulation and by benchmarking it against other reconstruction tools

You can find the detail of reconstructed data at http://bioinfo.konkuk.ac.kr/DESCHRAMBLER/

Address of the bookmark: https://github.com/jkimlab/DESCHRAMBLER

Rectangle Graph for Repeat Resolution in Genome Assembly

Rahul Nayak — Thu, 28 Dec 2017 09:43:03 -0600

Ultimate tool for resolving repeats in genome assemblies.

Though the specific implementation of the idea of the rectangle graph approach is already included into the current SPAdes distribution, we're also releasing the Rectangle Graph Module (RGM) as the separate code which can be run independently of SPAdes. Although RGM differs from the current implementation of the rectangle graph approach in SPAdes, in the future we plan to integrate RGM in SPAdes. RGM can be run with other genome assemblers if they use the graph format as SPAdes files.

For more details see: Nikolay Vyahhi, Son K. Pham, Pavel Pevzner. From de Bruijn Graphs to Rectangle Graphs for Genome Assembly, Lecture Notes in Bioinformatics 7534 (2012), pp. 249-261.

Address of the bookmark: http://bioinf.spbau.ru/en/rectangles

Genome assembly stats plotting

Jit — Wed, 28 Feb 2018 03:45:39 -0600

A de novo genome assembly can be summarised b

y a number of metrics, including:

Overall assembly length
Number of scaffolds/contigs
Length of longest scaffold/contig
Scaffold/contig N50 and N90Assembly base composition, in particular percentage GC and percentage Ns
CEGMA completeness
Scaffold/contig length/count distribution

assembly-stats supports two widely used presentations of these values, tabular and cumulative length plots, and introduces an additional circular plot that summarises most commonly used assembly metrics in a single visualisation. Each of these presentations is generated using javascript from a common (JSON) data structure, allowing toggling between alternative views, and each can be applied to a single or multiple assemblies to allow direct comparison of alternate assemblies.

Tabular presentation allows direct comparison of exact values between assemblies, the limitations of this approach lie in the necessary omission of distributions and the challenge of interpreting ratios of values that may vary by several orders of magnitude.

Address of the bookmark: https://github.com/rjchallis/assembly-stats