Browse
Submit Data
Databases
API
Help

Dataset Information

26 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Lra: A long read aligner for sequences and contigs.

ABSTRACT: It is computationally challenging to detect variation by aligning single-molecule sequencing (SMS) reads, or contigs from SMS assemblies. One approach to efficiently align SMS reads is sparse dynamic programming (SDP), where optimal chains of exact matches are found between the sequence and the genome. While straightforward implementations of SDP penalize gaps with a cost that is a linear function of gap length, biological variation is more accurately represented when gap cost is a concave function of gap length. We have developed a method, lra, that uses SDP with a concave-cost gap penalty, and used lra to align long-read sequences from PacBio and Oxford Nanopore (ONT) instruments as well as de novo assembly contigs. This alignment approach increases sensitivity and specificity for SV discovery, particularly for variants above 1kb and when discovering variation from ONT reads, while having runtime that are comparable (1.05-3.76×) to current methods. When applied to calling variation from de novo assembly contigs, there is a 3.2% increase in Truvari F1 score compared to minimap2+htsbox. lra is available in bioconda (https://anaconda.org/bioconda/lra) and github (https://github.com/ChaissonLab/LRA).

SUBMITTER: Ren J

PROVIDER: S-EPMC8248648 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Meta-aligner: long-read alignment based on genome statistics.

Project description:BackgroundCurrent development of sequencing technologies is towards generating longer and noisier reads. Evidently, accurate alignment of these reads play an important role in any downstream analysis. Similarly, reducing the overall cost of sequencing is related to the time consumption of the aligner. The tradeoff between accuracy and speed is the main challenge in designing long read aligners.ResultsWe propose Meta-aligner which aligns long and very long reads to the reference genome very efficiently and accurately. Meta-aligner incorporates available short/long aligners as subcomponents and uses statistics from the reference genome to increase the performance. Meta-aligner estimates statistics from reads and the reference genome automatically. Meta-aligner is implemented in C++ and runs in popular POSIX-like operating systems such as Linux.ConclusionsMeta-aligner achieves high recall rates and precisions especially for long reads and high error rates. Also, it improves performance of alignment in the case of PacBio long-reads in comparison with traditional schemes.

| S-EPMC5324271 | biostudies-literature

Reordering contigs of draft genomes using the Mauve aligner.

Project description:SummaryMauve Contig Mover provides a new method for proposing the relative order of contigs that make up a draft genome based on comparison to a complete or draft reference genome. A novel application of the Mauve aligner and viewer provides an automated reordering algorithm coupled with a powerful drill-down display allowing detailed exploration of results.AvailabilityThe software is available for download at http://gel.ahabs.wisc.edu/mauve.

| S-EPMC2723005 | biostudies-literature

BIGMAC : breaking inaccurate genomes and merging assembled contigs for long read metagenomic assembly.

Project description:BackgroundThe problem of de-novo assembly for metagenomes using only long reads is gaining attention. We study whether post-processing metagenomic assemblies with the original input long reads can result in quality improvement. Previous approaches have focused on pre-processing reads and optimizing assemblers. BIGMAC takes an alternative perspective to focus on the post-processing step.ResultsUsing both the assembled contigs and original long reads as input, BIGMAC first breaks the contigs at potentially mis-assembled locations and subsequently scaffolds contigs. Our experiments on metagenomes assembled from long reads show that BIGMAC can improve assembly quality by reducing the number of mis-assemblies while maintaining or increasing N50 and N75. Moreover, BIGMAC shows the largest N75 to number of mis-assemblies ratio on all tested datasets when compared to other post-processing tools.ConclusionsBIGMAC demonstrates the effectiveness of the post-processing approach in improving the quality of metagenomic assemblies.

| S-EPMC5084376 | biostudies-literature

Assembly of chromosome-scale contigs by efficiently resolving repetitive sequences with long reads.

Project description:The abundant repetitive sequences in complex eukaryotic genomes cause fragmented assemblies, which lose value as reference genomes, often due to incomplete gene sequences and unanchored or mispositioned contigs on chromosomes. Here we report a genome assembly method HERA, which resolves repeats efficiently by constructing a connection graph from an overlap graph. We test HERA on the genomes of rice, maize, human, and Tartary buckwheat with single-molecule sequencing and mapping data. HERA correctly assembles most of the previously unassembled regions, resulting in dramatically improved, highly contiguous genome assemblies with newly assembled gene sequences. For example, the maize contig N50 size reaches 61.2 Mb and the Tartary buckwheat genome comprises only 20 contigs. HERA can also be used to fill gaps and fix errors in reference genomes. The application of HERA will greatly improve the quality of new or existing assemblies of complex genomes.

| S-EPMC6877557 | biostudies-literature

Identification of avian W-linked contigs by short-read sequencing.

Project description:The female-specific W chromosomes and male-specific Y chromosomes have proven difficult to assemble with whole-genome shotgun methods, creating a demand for new approaches to identify sequence contigs specific to these sex chromosomes. Here, we develop and apply a novel method for identifying sequences that are W-specific.Using the Illumina Genome Analyzer, we generated sequence reads from a male domestic chicken (ZZ) and mapped them to the existing female (ZW) genome sequence. This method allowed us to identify segments of the female genome that are underrepresented in the male genome and are therefore likely to be female specific. We developed a Bayesian classifier to automate the calling of W-linked contigs and successfully identified more than 60 novel W-specific sequences.Our classifier can be applied to improve heterogametic whole-genome shotgun assemblies of the W or Y chromosome of any organism. This study greatly improves our knowledge of the W chromosome and will enhance future studies of avian sex determination and sex chromosome evolution.

| S-EPMC3428670 | biostudies-literature

Block Aligner: an adaptive SIMD-accelerated aligner for sequences and position-specific scoring matrices.

Project description:MotivationEfficiently aligning sequences is a fundamental problem in bioinformatics. Many recent algorithms for computing alignments through Smith-Waterman-Gotoh dynamic programming (DP) exploit Single Instruction Multiple Data (SIMD) operations on modern CPUs for speed. However, these advances have largely ignored difficulties associated with efficiently handling complex scoring matrices or large gaps (insertions or deletions).ResultsWe propose a new SIMD-accelerated algorithm called Block Aligner for aligning nucleotide and protein sequences against other sequences or position-specific scoring matrices. We introduce a new paradigm that uses blocks in the DP matrix that greedily shift, grow, and shrink. This approach allows regions of the DP matrix to be adaptively computed. Our algorithm reaches over 5-10 times faster than some previous methods while incurring an error rate of less than 3% on protein and long read datasets, despite large gaps and low sequence identities.Availability and implementationOur algorithm is implemented for global, local, and X-drop alignments. It is available as a Rust library (with C bindings) at https://github.com/Daniel-Liu-c0deb0t/block-aligner.

| S-EPMC10457662 | biostudies-literature

SRPRISM (Single Read Paired Read Indel Substitution Minimizer): an efficient aligner for assemblies with explicit guarantees.

Project description:Alignment of sequence reads generated by next-generation sequencing is an integral part of most pipelines analyzing next-generation sequencing data. A number of tools designed to quickly align a large volume of sequences are already available. However, most existing tools lack explicit guarantees about their output. They also do not support searching genome assemblies, such as the human genome assembly GRCh38, that include primary and alternate sequences and placement information for alternate sequences to primary sequences in the assembly. This paper describes SRPRISM (Single Read Paired Read Indel Substitution Minimizer), an alignment tool for aligning reads without splices. SRPRISM has features not available in most tools, such as (i) support for searching genome assemblies with alternate sequences, (ii) partial alignment of reads with a specified region of reads to be included in the alignment, (iii) choice of ranking schemes for alignments, and (iv) explicit criteria for search sensitivity. We compare the performance of SRPRISM to GEM, Kart, STAR, BWA-MEM, Bowtie2, Hobbes, and Yara using benchmark sets for paired and single reads of lengths 100 and 250 bp generated using DWGSIM. SRPRISM found the best results for most benchmark sets with error rate of up to ∼2.5% and GEM performed best for higher error rates. SRPRISM was also more sensitive than other tools even when sensitivity was reduced to improve run time performance. We present SRPRISM as a flexible read mapping tool that provides explicit guarantees on results.

| S-EPMC7172022 | biostudies-literature

BarraCUDA - a fast short read sequence aligner using graphics processing units.

Project description:With the maturation of next-generation DNA sequencing (NGS) technologies, the throughput of DNA sequencing reads has soared to over 600 gigabases from a single instrument run. General purpose computing on graphics processing units (GPGPU), extracts the computing power from hundreds of parallel stream processors within graphics processing cores and provides a cost-effective and energy efficient alternative to traditional high-performance computing (HPC) clusters. In this article, we describe the implementation of BarraCUDA, a GPGPU sequence alignment software that is based on BWA, to accelerate the alignment of sequencing reads generated by these instruments to a reference DNA sequence.Using the NVIDIA Compute Unified Device Architecture (CUDA) software development environment, we ported the most computational-intensive alignment component of BWA to GPU to take advantage of the massive parallelism. As a result, BarraCUDA offers a magnitude of performance boost in alignment throughput when compared to a CPU core while delivering the same level of alignment fidelity. The software is also capable of supporting multiple CUDA devices in parallel to further accelerate the alignment throughput.BarraCUDA is designed to take advantage of the parallelism of GPU to accelerate the alignment of millions of sequencing reads generated by NGS instruments. By doing this, we could, at least in part streamline the current bioinformatics pipeline such that the wider scientific community could benefit from the sequencing technology.BarraCUDA is currently available from http://seqbarracuda.sf.net.

| S-EPMC3278344 | biostudies-literature

SOAP3-dp: fast, accurate and sensitive GPU-based short read aligner.

Project description:To tackle the exponentially increasing throughput of Next-Generation Sequencing (NGS), most of the existing short-read aligners can be configured to favor speed in trade of accuracy and sensitivity. SOAP3-dp, through leveraging the computational power of both CPU and GPU with optimized algorithms, delivers high speed and sensitivity simultaneously. Compared with widely adopted aligners including BWA, Bowtie2, SeqAlto, CUSHAW2, GEM and GPU-based aligners BarraCUDA and CUSHAW, SOAP3-dp was found to be two to tens of times faster, while maintaining the highest sensitivity and lowest false discovery rate (FDR) on Illumina reads with different lengths. Transcending its predecessor SOAP3, which does not allow gapped alignment, SOAP3-dp by default tolerates alignment similarity as low as 60%. Real data evaluation using human genome demonstrates SOAP3-dp's power to enable more authentic variants and longer Indels to be discovered. Fosmid sequencing shows a 9.1% FDR on newly discovered deletions. SOAP3-dp natively supports BAM file format and provides the same scoring scheme as BWA, which enables it to be integrated into existing analysis pipelines. SOAP3-dp has been deployed on Amazon-EC2, NIH-Biowulf and Tianhe-1A.

| S-EPMC3669295 | biostudies-literature

A Long Fragment Aligner called ALFALFA.

Project description:BackgroundRapid evolutions in sequencing technology force read mappers into flexible adaptation to longer reads, changing error models, memory barriers and novel applications.ResultsALFALFA achieves a high performance in accurately mapping long single-end and paired-end reads to gigabase-scale reference genomes, while remaining competitive for mapping shorter reads. Its seed-and-extend workflow is underpinned by fast retrieval of super-maximal exact matches from an enhanced sparse suffix array, with flexible parameter tuning to balance performance, memory footprint and accuracy.ConclusionsALFALFA is open source and available at http://alfalfa.ugent.be .

| S-EPMC4449525 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data