BOL: Related items

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/

Flye: Fast and accurate de novo assembler for single molecule sequencing reads

Rahul Nayak — Sat, 06 Jul 2019 03:48:22 -0500

Flye is a de novo assembler for single molecule sequencing reads, such as those produced by PacBio and Oxford Nanopore Technologies. It is designed for a wide range of datasets, from small bacterial projects to large mammalian-scale assemblies. The package represents a complete pipeline: it takes raw PB / ONT reads as input and outputs polished contigs. Flye also includes a special mode for metagenome assembly.

Address of the bookmark: https://github.com/fenderglass/Flye

Rcorrector: efficient and accurate error correction for Illumina RNA-seq reads

BioStar — Tue, 04 Feb 2020 23:23:16 -0600

Rcorrector has an accuracy higher than or comparable to existing methods, including the only other method (SEECER) designed for RNA-seq reads, and is more time and memory efficient. With a 5 GB memory footprint for 100 million reads, it can be run on virtually any desktop or server. The software is available free of charge under the GNU General Public License from https://github.com/mourisl/Rcorrector/.

Usage: perl run_rcorrector.pl [OPTIONS]
OPTIONS:
	Required
	-s seq_files: comma separated files for single-end data sets
	-1 seq_files_left: comma separated files for the first mate in the paried-end data sets
	-2 seq_files_right: comma separated files for the second mate in the paired-end data sets
	-i seq_files_interleaved: comma sperated files for interleaved paired-end data sets
	Optional
	-k INT: kmer_length (<=32, default: 23)
	-od STRING: output_file_directory (default: ./)
	-t INT: number of threads to use (default: 1)
	-trim : allow trimming (default: false)
	-maxcorK INT: the maximum number of correction within k-bp window (default: 4)
	-wk FLOAT: the proportion of kmers that are used to estimate weak kmer count threshold, lower for more divergent genome (default: 0.95)
	-ek INT: expected number of kmers; does not affect the correctness of program but affects the memory usage (default: 100000000)
	-stdout: output the corrected reads to stdout (default: not used)
	-verbose: output some correction information to stdout (default: not used)
	-stage INT: start from which stage (default: 0)
		0-start from begining(storing kmers in bloom filter) ;
		1-start from count kmers showed up in bloom filter;
		2-start from dumping kmer counts into a jf_dump file;
		3-start from error correction.

Address of the bookmark: https://github.com/mourisl/Rcorrector/

DADA2: Fast and accurate sample inference from amplicon data with single-nucleotide resolution

Jit — Tue, 10 Nov 2020 20:26:00 -0600

The DADA2 tutorial goes through a typical workflow for paired end Illumina Miseq data: raw amplicon sequencing data is processed into the table of exact amplicon sequence variants (ASVs) present in each sample.

The DADA2 Workflow on Big Data goes through workflow optimized to run on large datasets (10s of millions to billions of reads).

An ITS-specific version of the DADA2 workflow identifies and verifiably removes primers on both ends of each ITS read, a key step due to the variable length of the ITS region.

Short demonstrations of assigning taxonomy and assigning species to sequences.

Address of the bookmark: https://benjjneb.github.io/dada2/index.html

HELIANO: A fast and accurate tool for detection of Helitron-like elements

LEGE — Tue, 13 Aug 2024 07:16:34 -0500

Helitron-like elements (HLE1 and HLE2) are DNA transposons. They have been found in diverse species and seem to play significant roles in the evolution of host genomes. Although known for over twenty years, Helitron sequences are still challenging to identify. Here, we propose HELIANO (Helitron-like elements annotator) as an efficient solution for detecting Helitron-like elements.

https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkae679/7730539?login=true

Address of the bookmark: https://github.com/Zhenlisme/heliano/

Shouji: a fast and efficient pre-alignment filter for sequence alignment

Jit — Mon, 04 Nov 2019 07:09:45 -0600

The ability to generate massive amounts of sequencing data continues to overwhelm the processing capacity of existing algorithms and compute infrastructures. In this work, we explore the use of hardware/software co-design and hardware acceleration to significantly reduce the execution time of short sequence alignment, a crucial step in analyzing sequenced genomes.

We introduce Shouji, a highly parallel and accurate pre-alignment filter that remarkably reduces the need for computationally-costly dynamic programming algorithms. The first key idea of our proposed pre-alignment filter is to provide high filtering accuracy by correctly detecting all common subsequences shared between two given sequences. The second key idea is to design a hardware accelerator design that adopts modern FPGA (field-programmable gate array) architectures to further boost the performance of our algorithm.

More at https://github.com/CMU-SAFARI/Shouji

Address of the bookmark: https://github.com/CMU-SAFARI/Shouji

CLARK: Fast, accurate and versatile sequence classification system

Jit — Sat, 15 Feb 2020 01:49:01 -0600

CLARK, a method based on a supervised sequence classification using discriminative k-mers. Considering two distinct specific classification problems (see the article for details), namely (1) the taxonomic classification of metagenomic reads to known bacterial genomes, and (2) the assignment of BAC clones and transcript to chromosome arms/centromeres (in the absence of a finished assembly for the reference genome), CLARK outperforms in classification speed and precision the best state-of-the-art methods.

http://clark.cs.ucr.edu/Spaced/

Address of the bookmark: http://clark.cs.ucr.edu/Spaced/

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/

P_RNA_scaffolder: a fast and accurate genome scaffolder using paired-end RNA-sequencing reads

BioStar — Fri, 07 Sep 2018 05:19:06 -0500

P_RNA_scaffolder is a novel scaffolding tool using Pair-end RNA-seq to scaffold genome fragments. The method is suitable for most genomes. The program could utilize Illumina Paired-end RNA-sequencing reads from target speciesies. Our method provides another practical alternative to existing mate-pair_based approaches or other Protein-based approaches (for instance, PEP_scaffolder ) for scaffolding genome sequences. The most important feature of this method is to improve the completeness of gene regions and long-coding gene regions (for instance, circRNA).

Address of the bookmark: http://www.fishbrowser.org/software/P_RNA_scaffolder/#

Jaeger : an accurate and fast deep-learning tool to detect bacteriophage sequences

LEGE — Sun, 31 Aug 2025 06:30:16 -0500

Jaeger is a tool that utilizes homology-free machine learning to identify phage genome sequences that are hidden within metagenomes. It is capable of detecting both phages and prophages within metagenomic assemblies.

Address of the bookmark: https://github.com/MGXlab/Jaeger