BOL: Related items

MaxBin: software for binning assembled metagenomic sequences based on an Expectation-Maximization algorithm.

Jit — Mon, 06 Mar 2017 04:03:38 -0600

MaxBin is software for binning assembled metagenomic sequences based on an Expectation-Maximization algorithm. Users can understand the underlying bins (genomes) of the microbes in their metagenomes by simply providing assembled metagenomic sequences and the reads coverage information or sequencing reads. For users' convenience MaxBin will report genome-related statistics, including estimated completeness, GC content and genome size in the binning summary page.

Users can use MEGAN or similar software on MaxBin bins to find the taxonomy of each bin after the binning process is finished.

https://academic.oup.com/bioinformatics/article/32/4/605/1744462/MaxBin-2-0-an-automated-binning-algorithm-to

The most recent version of MaxBin is 2.2, which supports the analysis of coassemblies of multiple samples. It is available at this JBEI downloads sites as well as MaxBin and MaxBin 2.0 sourceforge sites.

Address of the bookmark: http://downloads.jbei.org/data/microbial_communities/MaxBin/MaxBin.html

Mulan: Multiple-sequence local alignment and visualization for studying function and evolution

Jit — Fri, 24 Aug 2018 09:50:01 -0500

Mulan: Multiple-sequence local alignment and visualization for studying function and evolution

Mulan (http://mulan.dcode.org/), a novel method and a network server for comparing multiple draft and finished-quality sequences to identify functional elements conserved over evolutionary time. Mulan brings together several novel algorithms: the TBA multi-aligner program for rapid identification of local sequence conservation, and the multiTF program for detecting evolutionarily conserved transcription factor binding sites in multiple alignments. In addition, Mulan supports two-way communication with the GALA database; alignments of multiple species dynamically generated in GALA can be viewed in Mulan, and conserved transcription factor binding sites identified with Mulan/multiTF can be integrated and overlaid with extensive genome annotation data using GALA.

Address of the bookmark: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC540288/

GroopM: Metagenomic binning toolset

Jit — Tue, 07 Mar 2017 08:59:45 -0600

GroopM is a metagenomic binning toolset. It leverages spatio-temoral
dynamics (differential coverage) to accurately (and almost automatically)
extract population genomes from multi-sample metagenomic datasets.

GroopM is largely parameter-free. Use: groopm -h for more info.

For installation and usage instructions see : http://ecogenomics.github.io/GroopM/

Address of the bookmark: https://github.com/ecogenomics/GroopM

MSAProbs - Parallel and accurate multiple sequence alignment

Neel — Tue, 09 Jul 2019 23:58:44 -0500

MSAProbs is a well-established state-of-the-art multiple sequence alignment algorithm for protein sequences. The design of MSAProbs is based on a combination of pair hidden Markov models and partition functions to calculate posterior probabilities. Assessed using the popular benchmarks: BAliBASE, PREFAB, SABmark and OXBENCH, MSAProbs achieves statistically significant accuracy improvements over the existing top performing aligners, including ClustalW, MAFFT, MUSCLE, ProbCons and Probalign. In addition, MSAProbs is optimized for shared-memory CPUs by employing a multi-threaded design, and further parallelized for distributed-memory systems using MPI to overcome high memory overhead barrier and achieve good parallel and data-size scalability.

Address of the bookmark: http://msaprobs.sourceforge.net/homepage.htm#latest

Multigenome assembly

Jit — Tue, 14 Mar 2017 04:41:23 -0500

This project contains scripts and tutorials on how to assemble individual microbial genomes from metagenomes, as described in:

Genome sequences of rare, uncultured bacteria obtained by differential coverage binning of multiple metagenomes

Mads Albertsen, Philip Hugenholtz, Adam Skarshewski, Gene W. Tyson, Kåre L. Nielsen and Per .H. Nielsen

Nature Biotechnology 2013, doi: 10.1038/nbt.2579

See the associated online guide for detailed information.

https://github.com/MadsAlbertsen/multi-metagenome

Address of the bookmark: https://github.com/MadsAlbertsen/multi-metagenome

VG: variation graph data structures, interchange formats, alignment, genotyping, and variant calling methods

Jit — Tue, 28 Jan 2020 03:53:24 -0600

Variation graphs provide a succinct encoding of the sequences of many genomes. A variation graph (in particular as implemented in vg) is composed of:

nodes, which are labeled by sequences and ids
edges, which connect two nodes via either of their respective ends
paths, describe genomes, sequence alignments, and annotations (such as gene models and transcripts) as walks through nodes connected by edges

Address of the bookmark: https://github.com/vgteam/vg

UniAligner: a parameter-free framework for fast sequence alignment

Abhi — Fri, 08 Mar 2024 23:36:12 -0600

UniAligner (formerly, TandemAligner) is the first parameter-free algorithm for sequence alignment that introduces a sequence-dependent alignment scoring that automatically changes for any pair of compared sequences. Classical alignment approaches, such as the Smith-Waterman algorithm, that work well for most sequences, fail to construct biologically adequate alignments of extra-long tandem repeats (ETRs), such as human centromeres and immunoglobulin loci. This limitation was overlooked in the previous studies since the sequences of the centromeres and other ETRs across multiple genomes only became available recently.

More at https://www.nature.com/articles/s41592-023-01970-4

Address of the bookmark: https://github.com/seryrzu/unialigner

Seal: SEquence ALignment evaluation suite

Jit — Wed, 03 Jan 2018 05:05:46 -0600

Seal is a comprehensive sequencing simulation and alignment tool evaluation suite. This software (implemented in Java) provides several utilities that can be used to evaluate alignment algorithms, including:

Reading a pre-existing reference genome from one or more FASTA files.
Alternatively, generating an artificial reference genome based on input parameters (length, repeat count, repeat length, repeat variability rate).
Simulating reads from random locations in the genome based on input parameters of read length, coverage, sequencing error rate, and indel rate.
Applying alignment tools to the genome and the reads through a standardized interface.
Parsing the output of the alignment tool and calculating the number of reads that were correctly or incorrectly mapped.
Computing run times and measures of accuracy.

Seal has interfaces to evaluate the following software packages:

Bowtie
BWA
MAQ
mrFAST
mrsFAST
Novoalign
SHRiMP
SOAPv2

Address of the bookmark: http://compbio.case.edu/seal/

Selecting between Python 2 and Python 3?

Rahul Agarwal — Wed, 10 Jul 2013 16:30:58 -0500

Which version is best for bioinformatician to work on?

Metagenomics assembly workshop !!

Jit — Tue, 18 Apr 2017 04:28:19 -0500

Welcome to the one-day metagenomics assembly workshop. This tutorial will guide you through the typical steps of metagenome assembly and binning.

Address of the bookmark: http://denbi-metagenomics-workshop.readthedocs.io/en/latest/index.html