BOL: Related items

DISTRUCT: a program for the graphical display of population structure

Abhimanyu Singh — Mon, 25 Mar 2019 03:33:44 -0500

distruct is a program that can be used to graphically display results produced by the genetic clustering program structure or by other similar programs. The figures produced by distructdisplay individual membership coefficients in the same form as used in "Genetic structure of human populations" Science 298: 2381-2385 (2002). Various options enable the user to control left-to-right printing order of populations, bottom-to-top printing order of clusers, colors, and other graphical details. [Example]

[Download software package (includes the manual)] (you will be directed first to a registration page and we would very much appreciate if you register)
[Download manual]
[Download software note from Molecular Ecology Notes 4: 137-138 (2004)]

To use the UNIX versions, unzip and untar the files in an appropriate directory using

gunzip filename.tar.gz; tar xvf filename.tar

where "filename.tar.gz" is the downloaded file. Winzip will unzip the Windows version. Run the program by typing

./distruct

in UNIX or

distruct

from a Dos prompt in Windows. It will produce a figure using the data that are represented in the Central/South Asia K=5 plot in Science 298: 2381-2385 (2002).

Please send comments or problems with distruct to Noah Rosenberg.

October 15, 2014 — Users of Distruct may also find CLUMPP and CLUMPAK of interest.

Address of the bookmark: https://rosenberglab.stanford.edu/distruct.html

AutoDock Vina: an open-source program for doing molecular docking.

BioStar — Sat, 13 Jun 2020 07:55:56 -0500

AutoDock Vina is an open-source program for doing molecular docking. It was designed and implemented by Dr. Oleg Trott in the Molecular Graphics Lab at The Scripps Research Institute. It is especially effective for protein-ligand docking. AutoDock 4 is available under the GNU General Public License. AutoDock is one of the most cited docking software applications in the research community.

http://vina.scripps.edu/

Address of the bookmark: http://vina.scripps.edu/

shovill: Assemble bacterial isolate genomes from Illumina paired-end reads

BioStar — Sat, 02 Jan 2021 07:05:36 -0600

Shovill is a pipeline which uses SPAdes at its core, but alters the steps before and after the primary assembly step to get similar results in less time. Shovill also supports other assemblers like SKESA, Velvet and Megahit, so you can take advantage of the pre- and post-processing the Shovill provides with those too.

Address of the bookmark: https://github.com/tseemann/shovill

COPE: an accurate k-mer-based pair-end reads connection tool to facilitate genome assembly

Jit — Wed, 06 Dec 2017 02:08:14 -0600

An efficient tool called Connecting Overlapped Pair-End (COPE) reads, to connect overlapping pair-end reads using k-mer frequencies. We evaluated our tool on 30× simulated pair-end reads from Arabidopsis thaliana with 1% base error. COPE connected over 99% of reads with 98.8% accuracy, which is, respectively, 10 and 2% higher than the recently published tool FLASH. When COPE is applied to real reads for genome assembly, the resulting contigs are found to have fewer errors and give a 14-fold improvement in the N50 measurement when compared with the contigs produced using unconnected reads.

Address of the bookmark: ftp://ftp.genomics.org.cn/pub/cope

EAGLER: a scaffolding tool for long reads.

Jit — Mon, 04 Jun 2018 05:26:03 -0500

EAGLER is a scaffolding tool for long reads. The scaffolder takes as input a draft genome created by any NGS assembler and a set of long reads. The long reads are used to extend the contigs present in the NGS draft and possibly join overlapping contigs. EAGLER supports both PacBio and Oxford Nanopore reads.

The tool should be compatible with most UNIX flavors and has been successfully tested on the following operating systems:

Mac OS X 10.11.1
Mac OS X 10.10.3
Ubuntu 14.04 LTS

https://bib.irb.hr/datoteka/844447.Diplomski_2015_Luka_terbi.pdf

Address of the bookmark: https://github.com/mculinovic/EAGLER

JBrowse: Embeddable genome browser built completely with JavaScript and HTML5

Jit — Fri, 29 Jun 2018 09:19:56 -0500

JBrowse is a fast, embeddable genome browser built completely with JavaScript and HTML5, with optional run-once data formatting tools written in Perl. Headline Features: Fast, smooth scrolling and zooming. Explore your genome with unparalleled speed. Scales easily to multi-gigabase genomes and deep-coverage sequencing. Quickly open and view data files on your computer without uploading them to any server. Supports GFF3, BED, FASTA, Wiggle, BigWig, BAM, VCF (with either .tbi or .idx index), REST, and more. BAM, BigBed, BigWig, and VCF data are displayed directly from chunks of the compressed binary files, no conversion needed. Includes an optional “faceted” track selector (see demo) suitable for large installations with thousands of tracks. Very light server resource requirements. In fact, JBrowse has no back-end server code, just tools for formatting data files to be read directly over HTTP. Serve huge datasets from a single low-cost cloud instance. Can run as a stand-alone app on OSX and Windows using the Electron platform Highly extensible plugin architecture, with a large plugin registry of existing examples here https://gmod.github.io/jbrowse-registry https://jbrowse.org/

Address of the bookmark: https://github.com/GMOD/jbrowse

Hercules: a profile HMM-based hybrid error correction algorithm for long reads

Jit — Mon, 20 Aug 2018 14:14:11 -0500

Choosing whether to use second or third generation sequencing platforms can lead to trade-offs between accuracy and read length. Several studies require long and accurate reads including de novo assembly, fusion and structural variation detection. In such cases researchers often combine both technologies and the more erroneous long reads are corrected using the short reads. Current approaches rely on various graph based alignment techniques and do not take the error profile of the underlying technology into account. Memory- and time- efficient machine learning algorithms that address these shortcomings have the potential to achieve better and more accurate integration of these two technologies. Results: We designed and developed Hercules, the first machine learning-based long read error correction algorithm. The algorithm models every long read as a profile Hidden Markov Model with respect to the underlying platformtextquoterights error profile. The algorithm learns a posterior transition/emission probability distribution for each long read and uses this to correct errors in these reads. Using datasets from two DNA-seq BAC clones (CH17-157L1 and CH17-227A2), and human brain cerebellum polyA RNA-seq, we show that Hercules-corrected reads have the highest mapping rate among all competing algorithms and highest accuracy when most of the basepairs of a long read are covered with short reads. Availability:

Hercules source code is available at https://github.com/BilkentCompGen/Hercules

Address of the bookmark: https://github.com/BilkentCompGen/Hercules

Long read assembly workshop !

Rahul Nayak — Thu, 04 Oct 2018 17:23:18 -0500

This is a tutorial for a workshop on long-read (PacBio) genome assembly.

It demonstrates how to use long PacBio sequencing reads to assemble a bacterial genome, and includes additional steps for circularising, trimming, finding plasmids, and correcting the assembly with short-read Illumina data.

Please comment if you know any other long read addembly tutorial.

Address of the bookmark: http://sepsis-omics.github.io/tutorials/modules/cmdline_assembly_v2/

Pacasus: Correction of palindromes in long reads from PacBio and Nanopore

BioStar — Mon, 12 Nov 2018 05:26:48 -0600

Tool for detecting and cleaning PacBio / Nanopore long reads after whole genome amplification. Check the poster from the Revolutionizing Next-Generation Sequencing (2nd edition) conference in the source folder: https://github.com/swarris/Pacasus/blob/master/vib2017.pdf.

The prepint version is found on http://www.biorxiv.org/content/early/2017/08/09/173872

It uses the pyPaSWAS framework for sequence alignment (https://github.com/swarris/pyPaSWAS)

Address of the bookmark: https://github.com/swarris/Pacasus

Evaluation of genome assembly software based on long reads

BioStar — Fri, 01 Feb 2019 11:55:54 -0600

TGS technologies have been used to produce highly accurate de novo assemblies of hundreds of microbial genomes and highly contiguous reconstructions of many dozens of plant and animal genomes, enabling new insights into evolution and sequence diversity. They have also been applied to resequencing analyses, to create detailed maps of structural variations in many species. Also, these new technologies have been used to fill in many of the gaps in the human reference genome.

In this report, we compare and evaluate several genome assembly software based on TSG technology. The experimentation has been performed on 4 reference genomes and the results evaluated with the QUAST software. The 11 software that have been evaluated are: Celera Assembler , Falcon , Miniasm, Newbler , SGA Assembler, Smartdenovo, Abruijn, Ra, DBG2OLC, Spades and Cerulean. The first 8 software use only long reads, while the 3 last software can merge long and short reads