BOL: Related items

BlasR Mapping single molecule sequencing reads using Basic Local Alignment with Successive Refinement (BLASR): Theory and Application,

Jit — Wed, 23 May 2018 06:54:32 -0500

BLASR (Basic Local Alignment with Successive Refinement) for mapping Single Molecule Sequencing (SMS) reads that are thousands to tens of thousands of bases long with divergence between the read and genome dominated by insertion and deletion error.

Here is how I use the blasr to align PacBio reads to the contigs (target.fasta). The “target.fasta.sa” is the suffix array from “target.fasta” generated by sawriter.

blasr query.fa ./target.fasta -sa ./target.fasta.sa -bestn 40 -maxScore -500 -m 4 -nproc 24 -out target.m4 -maxLCPLength 15

the output format option “-m 4″ generate the alignment coordinate. Not fully documented, but I can explain that to you.

I use a 24 cores / 48G ram server for the alignment. It took about 2 to 3 hours aligning 3G PacBio Reads to 10^6 sequences of short read contigs with a mean 3.5kbp length.

Address of the bookmark: http://bix.ucsd.edu/projects/blasr/

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

Mugsy: multiple whole genome alignment tool

Jit — Fri, 08 Dec 2017 17:41:14 -0600

Mugsy is a multiple whole genome aligner. Mugsy uses Nucmer for pairwise alignment, a custom graph based segmentation procedure for identifying collinear regions, and the segment-based progressive multiple alignment strategy from Seqan::TCoffee. Mugsy accepts draft genomes in the form of multi-FASTA files and does not require a reference genome.

To cite Mugsy, use:

Angiuoli SV and Salzberg SL. Mugsy: Fast multiple alignment of closely related whole genomes.Bioinformatics 2011 27(3):334-4

Address of the bookmark: http://mugsy.sourceforge.net/

HISAT2: a fast and sensitive alignment program for mapping next-generation sequencing reads

Rahul Nayak — Tue, 08 May 2018 04:27:22 -0500

HISAT2 is a fast and sensitive alignment program for mapping next-generation sequencing reads (both DNA and RNA) to a population of human genomes (as well as to a single reference genome). Based on an extension of BWT for graphs [Sirén et al. 2014], we designed and implemented a graph FM index (GFM), an original approach and its first implementation to the best of our knowledge. In addition to using one global GFM index that represents a population of human genomes, HISAT2 uses a large set of small GFM indexes that collectively cover the whole genome (each index representing a genomic region of 56 Kbp, with 55,000 indexes needed to cover the human population). These small indexes (called local indexes), combined with several alignment strategies, enable rapid and accurate alignment of sequencing reads. This new indexing scheme is called a Hierarchical Graph FM index (HGFM).

more at https://ccb.jhu.edu/software/hisat2/index.shtml

Address of the bookmark: https://github.com/infphilo/hisat2

Gblocks: eliminates poorly aligned positions and divergent regions of a DNA or protein alignment

Poonam Mahapatra — Sat, 02 Jun 2018 07:36:05 -0500

Gblocks eliminates poorly aligned positions and divergent regions of a DNA or protein alignment so that it becomes more suitable for phylogenetic analysis. This server implements the most important features of the Gblocks program to make its use as simple as possible without loosing the functionality that it is necessary in most of the cases. Other options can be changed in the stand-alone program. You can see here an example output file showing the blocks selected from a protein alignment. Further information can be found in the online documentation.

Address of the bookmark: http://molevol.cmima.csic.es/castresana/Gblocks_server.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/

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