BOL: Related items

MetaBAT: An Efficient Tool for Accurately Reconstructing Single Genomes from Complex Microbial Communities

Jit — Mon, 06 Mar 2017 03:44:34 -0600

MetaBAT, An Efficient Tool for Accurately Reconstructing Single Genomes from Complex Microbial Communities

Grouping large genomic fragments assembled from shotgun metagenomic sequences to deconvolute complex microbial communities, or metagenome binning, enables the study of individual organisms and their interactions. Here we developed an automated metagenome binning software, called MetaBAT, which integrates empirical probabilistic distances of genome abundance and tetranucleotide frequency. Tested on both synthetic and real metagenome datasets, MetaBAT outperforms alternative methods in both accuracy and computational efficiency. Applying MetaBAT to an assembly from 1,704 human gut samples formed 1,634 genome bins (>200kb) in 3 hours, where 621 genome bins are >50% complete with <5% contamination from other species. Further analysis shows that the quality of these genome bins approaches manually curated genomes.

Address of the bookmark: https://bitbucket.org/berkeleylab/metabat

ABACAS

Surabhi Chaudhary — Thu, 16 Feb 2017 12:15:55 -0600

ABACAS is intended to rapidly contiguate (align, order, orientate) , visualize and design primers to close gaps on shotgun assembled contigs based on a reference sequence. It uses MUMmer to find alignment positions and identify syntenies of assembly contigs against the reference. The output is then processed to generate a pseudomolecule taking overlaping contigs and gaps in to account. MUMmer's alignment generating programs, Nucmer and Promer are used followed by the 'delta-filter' utility function. Users could also run tblastx on contigs that are not used to generate the pseudomolecule.

Address of the bookmark: http://abacas.sourceforge.net/Manual.html#9._Colour_code

FinisherSC: a repeat-aware and scalable tool for upgrading de novo assembly using long reads

Jit — Mon, 27 Feb 2017 09:49:45 -0600

FinisherSC, a repeat-aware and scalable tool for upgrading de novo assembly using long reads. Experiments with real data suggest that FinisherSC can provide longer and higher quality contigs than existing tools while maintaining high concordance.

Address of the bookmark: http://kakitone.github.io/finishingTool/

PhenoGram

Jit — Tue, 07 Mar 2017 08:35:12 -0600

With PhenoGram researchers can create chomosomal ideograms annotated with lines in color at specific base-pair locations, or colored base-pair to base-pair regions, with or without other annotation. PhenoGram allows for annotation of chromosomal locations and/or regions with shapes in different colors, gene identifiers, or other text. PhenoGram also allows for creation of plots showing expanded chromosomal locations, providing a way to show results for specific chromosomal regions in greater detail.

Address of the bookmark: http://ritchielab.psu.edu/software/phenogram-downloads

DBG2OLC:Efficient Assembly of Large Genomes Using Long Erroneous Reads of the Third Generation Sequencing Technologies

Jit — Wed, 19 Apr 2017 10:09:51 -0500

DBG2OLC:Efficient Assembly of Large Genomes Using Long Erroneous Reads of the Third Generation Sequencing Technologies

Our work is published in Scientific Reports:

Ye, C. et al. DBG2OLC: Efficient Assembly of Large Genomes Using Long Erroneous Reads of the Third Generation Sequencing Technologies. Sci. Rep. 6, 31900; doi: 10.1038/srep31900 (2016).

http://www.nature.com/articles/srep31900

The manual can be downloaded from:

https://github.com/yechengxi/DBG2OLC/raw/master/Manual.docx

To use precompiled versions,please go to:

https://github.com/yechengxi/DBG2OLC/tree/master/compiled

Address of the bookmark: https://github.com/yechengxi/DBG2OLC

Bacterial genome assembly !!

Jit — Fri, 05 May 2017 06:11:22 -0500

This tutorial will serve as an example of how to use free and open-source genome assembly and secondary scaffolding tools to generate high quality assemblies of bacterial sequence data. The bacterial sample used in this tutorial will be referred to simply as “Species” since it is live data. This data is paired-end data, meaning that there are forward and reverse reads, which we will designate as Sample_R1.fastq and Sample_R2.fastq, respectively.

https://github.com/jennomics/WorkflowPaper/blob/master/Genome%20Assembly%20and%20Annotation.md

Address of the bookmark: http://bioinformatics.uconn.edu/bacterial-genome-assembly-tutorial/

Redundans

Jit — Thu, 01 Sep 2016 08:28:11 -0500

Redundans pipeline assists an assembly of heterozygous genomes.
Program takes as input assembled contigs, paired-end and/or mate pairs sequencing libraries and returns scaffolded homozygous genome assembly, that should be less fragmented and with total size smaller than the input contigs. In addition, Redundans will automatically close the gaps resulting from genome assembly or scaffolding more details.

The pipeline consists of three steps/modules:

redundancy reduction: detection and selectively removal of redundant contigs from an initial de novo assembly
scaffolding: joining of genome fragments using paired-end and/or mate-pairs reads
gap closing

Redundans is:

fast & lightweight, multi-core support and memory-optimised, so it can be run even on the laptop for small-to-medium size genomes
flexible toward many sequencing technologies (Illumina, 454 or Sanger) and library types (paired-end, mate pairs, fosmids)
modular: every step can be ommited or replaced by another tools

Address of the bookmark: https://github.com/Gabaldonlab/redundans

Minia

Jit — Thu, 08 Dec 2016 05:07:00 -0600

Minia is a short-read assembler based on a de Bruijn graph, capable of assembling a human genome on a desktop computer in a day. The output of Minia is a set of contigs. Minia produces results of similar contiguity and accuracy to other de Bruijn assemblers (e.g. Velvet).

Download

Minia 2.0.7 Linux 64-bits binaries (Source code) (Legacy codebase)

For the impatient

A typical Minia command line looks like:

./minia -in reads.fa -kmer-size 31 -abundance-min 3 -out output_prefix

Type

./minia

for a quick explanation of the parameters.

For more information, refer to the manual.

KmerGenie can be used to determine the best k-mer size, minimum abundance of correct k-mers, and genome size estimation for your dataset.

Address of the bookmark: http://minia.genouest.org/

Velvet tutorial

Poonam Mahapatra — Fri, 09 Dec 2016 04:19:07 -0600

The objective of this activity is to help you understand how to run Velvet in general, how to accurately estimate the insert size of a paired-end library through the use of Bowtie, the primary parameters of velvet, and the process involved in producing a de novo assembly from Illumina reads.

http://evomics.org/learning/assembly-and-alignment/velvet/

Address of the bookmark: http://evomics.org/learning/assembly-and-alignment/velvet/

PEAR

Jit — Mon, 19 Dec 2016 09:28:30 -0600

PEAR is an ultrafast, memory-efficient and highly accurate pair-end read merger. It is fully parallelized and can run with as low as just a few kilobytes of memory.

PEAR evaluates all possible paired-end read overlaps and without requiring the target fragment size as input. In addition, it implements a statistical test for minimizing false-positive results. Together with a highly optimized implementation, it can merge millions of paired end reads within a couple of minutes on a standard desktop computer.

Address of the bookmark: http://sco.h-its.org/exelixis/web/software/pear/doc.html