BOL: Related items

mrFAST: Micro Read Fast Alignment Search Tool

Neel — Tue, 26 Apr 2016 03:50:06 -0500

mrFAST is a read mapper that is designed to map short reads to reference genome with a special emphasis on the discovery of structural variation and segmental duplications. mrFAST maps short reads with respect to user defined error threshold, including indels up to 4+4 bp. This manual, describes how to choose the parameters and tune mrFAST with respect to the library settings. mrFAST is designed to find 'all' mappings for a given set of reads, however it can return one "best" map location if the relevant parameter is invoked.

More at http://mrfast.sourceforge.net/manual.html

Address of the bookmark: http://mrfast.sourceforge.net/manual.html

LoRMA: a tool for correcting sequencing errors in long reads such those produced by Pacific Biosciences sequencing machines

Jit — Wed, 15 Jun 2016 17:18:36 -0500

LoRMA is a tool for correcting sequencing errors in long reads such those produced by Pacific Biosciences sequencing machines.

Publication:

L. Salmela, R. Walve, E. Rivals, and E. Ukkonen: Accurate selfcorrection of errors in long reads using de Bruijn graphs. Accepted to RECOMB-Seq 2016.

Download:

Address of the bookmark: https://www.cs.helsinki.fi/u/lmsalmel/LoRMA/

ART: Set of Simulation Tools

Jit — Thu, 03 Nov 2016 08:28:25 -0500

ART is a set of simulation tools to generate synthetic next-generation sequencing reads. ART simulates sequencing reads by mimicking real sequencing process with empirical error models or quality profiles summarized from large recalibrated sequencing data. ART can also simulate reads using user own read error model or quality profiles. ART supports simulation of single-end, paired-end/mate-pair reads of three major commercial next-generation sequencing platforms: Illumina's Solexa, Roche's 454 and Applied Biosystems' SOLiD. ART can be used to test or benchmark a variety of method or tools for next-generation sequencing data analysis, including read alignment, de novo assembly, SNP and structure variation discovery. ART was used as a primary tool for the simulation study of the 1000 Genomes Project . ART is implemented in C++ with optimized algorithms and is highly efficient in read simulation. ART outputs reads in the FASTQ format, and alignments in the ALN format. ART can also generate alignments in the SAM alignment or UCSC BED file format. ART can be used together with genome variants simulators (e.g. VarSim) for evaluating variant calling tools or methods.

Address of the bookmark: http://www.niehs.nih.gov/research/resources/software/biostatistics/art/

SpeedSeq

Jit — Fri, 20 Jan 2017 06:05:43 -0600

A flexible framework for rapid genome analysis and interpretation

C Chiang, R M Layer, G G Faust, M R Lindberg, D B Rose, E P Garrison, G T Marth, A R Quinlan, and I M Hall. SpeedSeq: ultra-fast personal genome analysis and interpretation. Nat Meth (2015). doi:10.1038/nmeth.3505.

http://www.nature.com/nmeth/journal/vaop/ncurrent/full/nmeth.3505.html

Address of the bookmark: https://github.com/hall-lab/speedseq

CABOG: Celera Assembler with Best Overlap Graph

Abhimanyu Singh — Mon, 15 May 2017 05:04:39 -0500

CABOG (Celera Assembler with Best Overlap Graph) is scientific software for DNA research. CABOG has been a critical component of many genome sequencing projects. CABOG operates on small genomes such as bacterial as well as large genomes such as mammalian. CABOG is an extension of the Celera Assembler software that was originally developed at Celera for the 2001 publication of the first draft human genome sequence. The software was released to the public domain in 2004. Its open source repository on Source Forge is an internet resource for scientists around the world.

CABOG is one of many software programs called genome assemblers. These programs exist to overcome the fundamental limitation of all sequencing machines, namely, that they read out very few DNA letters at a time. These programs reconstruct genomes that are billions of letters long from the hundreds of letters per read that modern sequencers provide. What these programs do is often described as a scaled up version of a family solving a jigsaw puzzle.

The CABOG software was the first to accomplish many scientific goals. It was the first to assemble the genome of a multicellular organism (Drosophila melanogaster, 2000). It was the first to assemble both parental haplotypes of one human genome (J. Craig Venter, 2007). It was the first to assemble environmental sequence from the oceans (Sargasso Sea in 2004 and Global Ocean Sampling in 2007). It was first to combine reads from first-generation Sanger sequencing machines and second-generation pyrosequencing machines (Marine microbes, 2006). Today, CABOG is one of the leading assembly programs for data sets that include paired end data from the Roche 454 line of sequencing machines.

Address of the bookmark: http://www.jcvi.org/cms/research/projects/cabog/overview/

Consed--A Finishing Package (BAM File Viewer, Assembly Editor, Autofinish, Autoreport, Autoedit, and Align Reads To Reference Sequence)

Neel — Fri, 07 Feb 2020 07:16:22 -0600

Supports Illumina, 454, other Next-Gen and Sanger Reads and allows mixtures of these read types
Consed includes BamScape which can view bam files with unlimited numbers of reads. BamScape can bring up consed to edit reads and the reference sequence in targeted regions.
Consed is compatible with Newbler, Cross_match, Phrap, MIRA, Velvet and PCAP output.
Quickly takes the user to each variant site for viewing (also available as an automated report)
Overview of assembly can help detect and fix misassemblies
Editing time reduced by the program's ability to pin-point problem areas
Editing is guided by error probabilities

Address of the bookmark: http://www.phrap.org/consed/consed.html

BEAR: Better Emulation for Artificial Reads

BioStar — Sat, 06 Jul 2024 04:27:53 -0500

Created by Stephen Johnson, Brett Trost, Dr. Jeffrey R. Long, Dr. Anthony Kusalik University of Saskatchewan, Department of Computer Science

BEAR is intended to be an easy-to-use collection of scripts for generating simulated WGS metagenomic reads with read lengths, quality scores, error profiles, and species abundances derived from real user-supplied WGS data.

Address of the bookmark: https://github.com/sej917/BEAR

AlignGraph: algorithm for secondary de novo genome assembly guided by closely related references

Manisha Mishra — Tue, 17 Apr 2018 16:21:20 -0500

AlignGraph is a software that extends and joins contigs or scaffolds by reassembling them with help provided by a reference genome of a closely related organism.

Using AlignGraph

AlignGraph --read1 reads_1.fa --read2 reads_2.fa --contig contigs.fa --genome genome.fa --distanceLow distanceLow --distanceHigh distancehigh --extendedContig extendedContigs.fa --remainingContig remainingContigs.fa [--kMer k --insertVariation insertVariation --coverage coverage --part p --fastMap --ratioCheck --iterativeMap --misassemblyRemoval --resume]

Address of the bookmark: https://github.com/baoe/AlignGraph

OrthoANI: An improved algorithm and software for calculating average nucleotide identity

Abhimanyu Singh — Wed, 12 Dec 2018 08:36:08 -0600

OAT uses OrthoANI to measure the overall similarity between two genome sequences. ANI and OrthoANI are comparable algorithms: they share the same species demarcation cut-off at 95~96% and large comparison studies have demonstrated both algorithms to produce near identical reciprocal similarities. Details of the OrthoANI algorithm is given in (Lee et al. 2015). OAT employs an easy-to-follow Graphical User Interface that allow researchers to calculate OrthoANI values between genomes of interest without unfamiliar Command Line Environments. Moreover, the OAT_cmd command-line software can be integrated into preexisting bioinformatics pipelines.

Address of the bookmark: https://www.ezbiocloud.net/tools/orthoani

The wavefront alignment (WFA) algorithm

BioStar — Sun, 28 Jun 2020 10:17:50 -0500

The wavefront alignment (WFA) algorithm is an exact gap-affine algorithm that takes advantage of
homologous regions between the sequences to accelerate the alignment process. As opposed to traditional dynamic programming algorithms that run in quadratic time, the WFA runs in time O(ns), proportional to the read length n and the alignment score s, using O(s^2) memory. Moreover, the WFA exhibits simple data dependencies that can be easily vectorized, even by the automatic features of modern compilers, for different architectures, without the need to adapt the code.

Address of the bookmark: https://github.com/smarco/WFA