BOL: Related items

Termal: a fast and interactive terminal-based viewer for multiple sequence alignments

LEGE — Mon, 22 Sep 2025 23:51:02 -0500

termal, a fast, interactive, terminal-based viewer for multiple sequence alignments (MSAs), designed for use on remote systems such as high-performance computing (HPC) clusters.

https://academic.oup.com/bioinformaticsadvances/advance-article/doi/10.1093/bioadv/vbaf208/8257678?login=true

Address of the bookmark: https://github.com/sib-swiss/termal

Alignment of closely related whole genomes/scaffolds

Rahul Nayak — Fri, 29 Jan 2016 10:37:27 -0600

With the relative ease and low cost of current generation sequencing technologies has led to a dramatic increase in the number of sequenced genomes for species across the tree of life. This increasing volume of data requires tools that can quickly compare multiple whole-genome sequences, millions of base pairs in length, to aid in the study of populations, pan-genomes, and genome evolution.This bookmaks have been created to report new tools for whole genome alignments.

Please report new whole genome alignment tools under comment sections.

Address of the bookmark: http://www.cs.utoronto.ca/~brudno/721.full.pdf

Understanding reads mapping and flags !

Jit — Thu, 25 Apr 2019 09:06:20 -0500

Linear Alignment: An alignment of a read to a single reference sequence that may include insertions, deletions, skips and clipping, but may not include direction changes (i.e. one portion of the alignment on forward strand and another portion of alignment on reverse strand).

Chimeric Alignment: An alignment of a read that cannot be represented as a linear alignment. Typically, one of the linear alignments in a chimeric alignment is considered the “representative” alignment, and the others are called “supplementary” and are distinguished by the supplementary alignment flag.

Chimeric reads are indicative of structural variation in DNA-seq and it may indicate the presence of chimeric genes in RNA-seq.

In short, chimeric reads can be split in to two or more parts, each part would be mapped to reference(it’s not hard-clipped), the total length of the mapped part is longger than read length.

Representative alignment: A chimeric alignment that is represented as a set of linear alignments that do not have large overlaps typically has one linear alignment that is considered the representative alignment.

One read can align to multiple positions, we can find one alignmnet position which sequence do not have large overlaps, it called representative alighment, for other alignment positions, we called them supplementary alignment.

It seems that GATK can realignment those representative reads to the correctly position via RealignerTargetCreator and IndelRealigner. (WARNING: I am not quite sure if I understand this correctly. If someone could help me, please leave me a message below, thanks, thanks.)

Supplementary Alignment: A chimeric reads but not a representative reads.

Primary Alignment and Secondary Alignment: A read may map ambiguously to multiple locations, e.g. due to repeats. Only one of the multiple read alignments is considered primary, and this decision may be arbitrary. All other alignments have the secondary alignment flag.

Many-to-many pairwise alignments of two sequence sets

Poonam Mahapatra — Tue, 19 Jun 2018 08:34:15 -0500

needleall reads a set of input sequences and compares them all to one or more sequences, writing their optimal global sequence alignments to file. It uses the Needleman-Wunsch alignment algorithm to find the optimum alignment (including gaps) of two sequences along their entire length. The algorithm uses a dynamic programming method to ensure the alignment is optimum, by exploring all possible alignments and choosing the best. A scoring matrix is read that contains values for every possible residue or nucleotide match. Needleall finds the alignment with the maximum possible score where the score of an alignment is equal to the sum of the matches taken from the scoring matrix, minus penalties arising from opening and extending gaps in the aligned sequences. The substitution matrix and gap opening and extension penalties are user-specified.

Address of the bookmark: http://emboss.sourceforge.net/apps/release/6.6/emboss/apps/needleall.html

BLAST options, setting and defaults

Jit — Mon, 10 Dec 2018 08:29:37 -0600

BLAST stands for Basic Local Alignment Search Tool and was developed by Altschul et al. (1990) and significantly improved by Altschul et al. (1997). It is a very fast search algorithm that is used to separately search protein or DNA databases. BLAST is best used for sequence similarity searching, rather than for motif searching. For searches using a query sequence of fewer than twenty residues, PatMatch is the best choice. Another sequence alignment tool that may yield different results from BLAST, and may be useful for motif searching, is FASTA. To search nonplant datasets, try NCGR BLAST or NCBI BLAST.

A fairly complete on-line guide to BLAST searching can be found at the NCBI BLAST Help Manual. For a theoretical overview of BLAST, see the NCBI BLAST Course. Additional information can be found in the BLAST 2.0 Release Notes

	BLASTN	BLASTP	BLASTX	TBLASTN	TBLASTX	PSIBLAST
Gap opening penalty: cost to open a gap [integer]	default = 5	default = 11 limited values are supported	default = 11 limited values are supported	default = 11 limited values are supported	default = 11 limited values are supported	default = 5
Gap extension penalty: cost to extend a gap [integer]	default = 2	default = 1 a 0 in this field means to use the default	default = 1 a 0 in this field means to use the default	default = 1 a 0 in this field means to use the default	default = 1 a 0 in this field means to use the default	default = 2
Nucleic match: reward for a match in the BLAST portion of run [integer]	default = 1	n/a	n/a	n/a	n/a	default = 1
Nucleic mismatch: penalty for a mismatch in the blast portion of run [integer]	default = -3	n/a	n/a	n/a	n/a	default = -3
Expectation value: (E) [real]	default = 10.0	default = 10.0	default = 10.0	default = 10.0	default = 10.0	default = 10.0
Word size: the size of the initial word that must be matched between the database and the query sequence	default = 11	default = 3	default = 3	default = 3	default = 3	default = 11
Max scores: Number of one-line descriptions (V) [Integer]	default = 25	default = 25	default = 25	default = 25	default = 25	default = 25
Max alignments: number of alignments to show (B) [integer]	default = 15	default = 15	default = 15	default = 15	default = 15	default = 15
Query filter: filter applied to the query sequence	default = DUST	default = SEG	default = SEG	default = SEG	default = SEG	default = DUST
Query genetic code: genetic code to be used in BLASTX translation of the query	n/a	n/a	default = universal	default = universal	default = universal	n/a
Matrix: substitution matrix to be used for amino acid comparisons	no default	default = blosum62	default = blosum62	default = blosum62	default = blosum62	no default

Supported and Suggested Values for Gap Open and Extension in BLASTP, BLASTX, TBLASTN, and TBLASTX

Gaps Open	Gap Extension
10	1
10	2
11	1
8	2
9	2

Address of the bookmark: https://www.arabidopsis.org/Blast/BLASToptions.jsp

lordFAST: sensitive and Fast Alignment Search Tool for LOng noisy Read sequencing Data

BioJoker — Tue, 27 Nov 2018 04:43:57 -0600

lordFAST is a sensitive tool for mapping long reads with high error rates. lordFAST is specially designed for aligning reads from PacBio sequencing technology but provides the user the ability to change alignment parameters depending on the reads and application.

lordFAST, a novel long-read mapper that is specifically designed to align reads generated by PacBio and potentially other SMS technologies to a reference. lordFAST not only has higher sensitivity than the available alternatives, it is also among the fastest and has a very low memory footprint.

Address of the bookmark: https://github.com/vpc-ccg/lordfast

RaGOO: Fast Reference-Guided Scaffolding of Genome Assembly Contigs

Jit — Sun, 27 Oct 2019 00:57:23 -0500

Alonge M, Soyk S, Ramakrishnan S, Wang X, Goodwin S, Sedlazeck FJ, Lippman ZB, Schatz MC: Fast and accurate reference-guided scaffolding of draft genomes. bioRxiv 2019.

RaGOO is a tool for coalescing genome assembly contigs into pseudochromosomes via minimap2 alignments to a closely related reference genome. The focus of this tool is on practicality and therefore has the following features:

Good performance. On a MacBook Pro using Arabidopsis data, pseudochromosome construction takes less than a minute and the whole pipeline with SV calling takes ~2 minutes.
Intact ordering and orienting of contigs.
Misassembly correction
GFF lift-over
Structural variant calling with and integrated version of Assemblytics
Confidence scores associated with the grouping, localization, and orientation for each contig.

Address of the bookmark: https://github.com/malonge/RaGOO

PLAST: A fast, accurate and NGS scalable bank-to-bank sequence similarity search tool

Jit — Fri, 01 Dec 2017 04:10:54 -0600

PLAST is a fast, accurate and NGS scalable bank-to-bank sequence similarity search tool providing significant accelerations of seeds-based heuristic comparison methods, such as the Blast suite of algorithms.

Relying on unique software architecture, PLAST takes full advantage of recent multi-core personal computers without requiring any additional hardware devices.

PLAST stands for Parallel Local Sequence Alignment Search Tool and is was published in BMC Bioinformatics.

PLAST is a general purpose sequence comparison tool providing the following benefits:

PLAST is a high-performance sequence comparison tool designed to compare two sets of sequences (query vs. reference),
Reduces the processing time of sequences comparisons while providing highest quality results,
Contains a fully integrated data filtering engine capable of selecting relevant hits with user-defined criteria (E-Value, identity, coverage, alignment length, etc.),
Does not require any additional hardware, since it is a software solution. It is easy to install, cost-effective, takes full advantage of multi-core processors and uses a small RAM footprint,
Ready to be used on desktop computer, cluster, cloud as well as within distributed system running Hadoop.

https://plast.inria.fr/

Address of the bookmark: https://plast.inria.fr/

MMseqs2.0: ultra fast and sensitive protein search and clustering suite

Jit — Thu, 22 Mar 2018 10:40:51 -0500

MMseqs2 (Many-against-Many sequence searching) is a software suite to search and cluster huge protein sequence sets. MMseqs2 is open source GPL-licensed software implemented in C++ for Linux, MacOS, and (as beta version, via cygwin) Windows. The software is designed to run on multiple cores and servers and exhibits very good scalability. MMseqs2 can run 10000 times faster than BLAST. At 100 times its speed it achieves almost the same sensitivity. It can perform profile searches with the same sensitivity as PSI-BLAST at over 400 times its speed.

The MMseqs2 user guide is available as Github Wiki or as PDF file (Thanks to pandoc!)

Please cite: Steinegger M and Soeding J. MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets. Nature Biotechnology, doi: 10.1038/nbt.3988 (2017).

Address of the bookmark: https://github.com/soedinglab/MMseqs2

WhatsHap: fast and accurate read-based phasing

Jit — Mon, 28 May 2018 09:52:16 -0500

WhatsHap is a software for phasing genomic variants using DNA sequencing reads, also called read-based phasing or haplotype assembly. It is especially suitable for long reads, but works also well with short reads.

Features

Very accurate results (Martin et al., WhatsHap: fast and accurate read-based phasing)

Works well with Illumina, PacBio, Oxford Nanopore and other types of reads

It phases SNVs, indels and even “complex” variants (such as TCG → AGAA)

Pedigree phasing mode uses reads from related individuals (such as trios) to improve results and to reduce coverage requirements (Garg et al., Read-Based Phasing of Related Individuals).

WhatsHap is easy to install

It is easy to use: Pass in a VCF and one or more BAM files, get out a phased VCF. Supports multi-sample VCFs.

It produces standard-compliant VCF output by default

If desired, get output that is compatible with ReadBackedPhasing

Open Source (MIT license)

Address of the bookmark: https://whatshap.readthedocs.io/en/latest/