BOL: Related items

AnchorWave

Neel — Wed, 23 Feb 2022 08:14:35 -0600

AnchorWave (Anchored Wavefront Alignment) identifies collinear regions via conserved anchors (full-length CDS and full-length exon have been implemented currently) and breaks collinear regions into shorter fragments, i.e., anchor and inter-anchor intervals. By performing sensitive sequence alignment for each shorter interval via a 2-piece affine gap cost strategy and merging them together, AnchorWave generates a whole-genome alignment for each collinear block. AnchorWave implements commands to guide collinear block identification with or without chromosomal rearrangements and provides options to use known polyploidy levels or whole-genome duplications to inform alignment.

Address of the bookmark: https://github.com/baoxingsong/AnchorWave

MetaGraph: Ultra Scalable Framework for DNA Search, Alignment, Assembly

Abhi — Sat, 08 Jun 2024 16:15:25 -0500

The MetaGraph framework is designed to work with a wide range of input data sets, indexing from a few samples up to the contents of entire archives with hundreds of thousands of records. The indexing workflow always follows the same principle, transforming single input samples into error-removed, refined sample graphs, which are then merged into a joint metagraph index. Each input sample is annotated in the joint index as a subgraph. This graph index enriched with metadata can then be used for downstream applications such as sequence search or differential assembly.

Searcg link https://metagraph.ethz.ch/search

Pre-print https://www.biorxiv.org/content/10.1101/2020.10.01.322164v4

Address of the bookmark: https://metagraph.ethz.ch/

CrocoBLAST: Optimized parallel implementation of local sequence alignment algorithms

Jit — Tue, 25 Jul 2017 05:03:10 -0500

Local sequence alignment is a cornerstone of bioinformatics, allowing to compare the amino-acid sequences of different proteins, or the nucleotide sequences of different pieces of DNA. The Basic Local Alignment Search Tool (BLAST) has revolutionized the field of bioinformatics, and is currently implemented in all free and commercial bioinformatics packages. However, with the advent of Next Generation Sequencing (NGS) and the development of new sequencing techniques, the utility of traditional BLAST implementations is limited. CrocoBLAST combines the accuracy and general applicability of BLAST with computational efficiency, accessibility, and user experience, so that NGS data can be analyzed efficiently even when only modest computational resources are available.

https://webchem.ncbr.muni.cz/Platform/App/CrocoBLAST

Address of the bookmark: https://webchem.ncbr.muni.cz/Platform/App/CrocoBLAST

kSNP3.0: SNP detection and phylogenetic analysis of genomes without genome alignment or reference genome

Jit — Fri, 08 Dec 2017 16:48:40 -0600

Sept. 20, 2017 Version 3.1 released. Major upgrade. Version 3.1 fixes the problems with SNP annotation that arose when NCBI discontinued use of GI numbers. Please read carefully the Preface (page 3) and the File of annotated genomes section (pages 9-10) in the version 3.1 User Guide. Thanks to Tom Slezak for revsing the get_genbank_file3 script and to Tod Stuber (USDA) for testing version 3.1 even though he doesn't need the annotation feature. All users are encouraged to upgrade to version 3.1.

Address of the bookmark: https://sourceforge.net/projects/ksnp/files/

MUMmer4: A fast and versatile genome alignment system

Jit — Sat, 03 Feb 2018 04:59:17 -0600

MUMmer4, a substantially improved version of MUMmer that addresses genome size constraints by changing the 32-bit suffix tree data structure at the core of MUMmer to a 48-bit suffix array, and that offers improved speed through parallel processing of input query sequences. With a theoretical limit on the input size of 141Tbp, MUMmer4 can now work with input sequences of any biologically realistic length. We show that as a result of these enhancements, the nucmer program in MUMmer4 is easily able to handle alignments of large genomes;

Address of the bookmark: https://mummer4.github.io/

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/

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

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/