X

Quality Statement

Pacific Biosciences is committed to providing high-quality products that meet customer expectations and comply with regulations. We will achieve these goals by adhering to and maintaining an effective quality-management system designed to ensure product quality, performance, and safety.

X

Image Use Agreement

By downloading, copying, or making any use of the images located on this website (“Site”) you acknowledge that you have read and understand, and agree to, the terms of this Image Usage Agreement, as well as the terms provided on the Legal Notices webpage, which together govern your use of the images as provided below. If you do not agree to such terms, do not download, copy or use the images in any way, unless you have written permission signed by an authorized Pacific Biosciences representative.

Subject to the terms of this Agreement and the terms provided on the Legal Notices webpage (to the extent they do not conflict with the terms of this Agreement), you may use the images on the Site solely for (a) editorial use by press and/or industry analysts, (b) in connection with a normal, peer-reviewed, scientific publication, book or presentation, or the like. You may not alter or modify any image, in whole or in part, for any reason. You may not use any image in a manner that misrepresents the associated Pacific Biosciences product, service or technology or any associated characteristics, data, or properties thereof. You also may not use any image in a manner that denotes some representation or warranty (express, implied or statutory) from Pacific Biosciences of the product, service or technology. The rights granted by this Agreement are personal to you and are not transferable by you to another party.

You, and not Pacific Biosciences, are responsible for your use of the images. You acknowledge and agree that any misuse of the images or breach of this Agreement will cause Pacific Biosciences irreparable harm. Pacific Biosciences is either an owner or licensee of the image, and not an agent for the owner. You agree to give Pacific Biosciences a credit line as follows: "Courtesy of Pacific Biosciences of California, Inc., Menlo Park, CA, USA" and also include any other credits or acknowledgments noted by Pacific Biosciences. You must include any copyright notice originally included with the images on all copies.

IMAGES ARE PROVIDED BY Pacific Biosciences ON AN "AS-IS" BASIS. Pacific Biosciences DISCLAIMS ALL REPRESENTATIONS AND WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, INCLUDING, BUT NOT LIMITED TO, NON-INFRINGEMENT, OWNERSHIP, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. IN NO EVENT SHALL Pacific Biosciences BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, PUNITIVE, OR CONSEQUENTIAL DAMAGES OF ANY KIND WHATSOEVER WITH RESPECT TO THE IMAGES.

You agree that Pacific Biosciences may terminate your access to and use of the images located on the PacificBiosciences.com website at any time and without prior notice, if it considers you to have violated any of the terms of this Image Use Agreement. You agree to indemnify, defend and hold harmless Pacific Biosciences, its officers, directors, employees, agents, licensors, suppliers and any third party information providers to the Site from and against all losses, expenses, damages and costs, including reasonable attorneys' fees, resulting from any violation by you of the terms of this Image Use Agreement or Pacific Biosciences' termination of your access to or use of the Site. Termination will not affect Pacific Biosciences' rights or your obligations which accrued before the termination.

I have read and understand, and agree to, the Image Usage Agreement.

I disagree and would like to return to the Pacific Biosciences home page.

Pacific Biosciences
Contact:
November 1, 2018

Combining probabilistic alignments with read pair information improves accuracy of split-alignments.

Split-alignments provide base-pair-resolution evidence of genomic rearrangements. In practice, they are found by first computing high-scoring local alignments, parts of which are then combined into a split-alignment. This approach is challenging when aligning a short read to a large and repetitive reference, as it tends to produce many spurious local alignments leading to ambiguities in identifying the correct split-alignment. This problem is further exacerbated by the fact that rearrangements tend to occur in repeat-rich regions.We propose a split-alignment technique that combats the issue of ambiguous alignments by combining information from probabilistic alignment with positional information from paired-end reads. We demonstrate…

Read More »

October 1, 2018

Generic accelerated sequence alignment in SeqAn using vectorization and multi-threading.

Pairwise sequence alignment is undoubtedly a central tool in many bioinformatics analyses. In this paper, we present a generically accelerated module for pairwise sequence alignments applicable for a broad range of applications. In our module, we unified the standard dynamic programming kernel used for pairwise sequence alignments and extended it with a generalized inter-sequence vectorization layout, such that many alignments can be computed simultaneously by exploiting SIMD (single instruction multiple data) instructions of modern processors. We then extended the module by adding two layers of thread-level parallelization, where we (a) distribute many independent alignments on multiple threads and (b) inherently…

Read More »

July 1, 2018

A fast approximate algorithm for mapping long reads to large reference databases.

Emerging single-molecule sequencing technologies from Pacific Biosciences and Oxford Nanopore have revived interest in long-read mapping algorithms. Alignment-based seed-and-extend methods demonstrate good accuracy, but face limited scalability, while faster alignment-free methods typically trade decreased precision for efficiency. In this article, we combine a fast approximate read mapping algorithm based on minimizers with a novel MinHash identity estimation technique to achieve both scalability and precision. In contrast to prior methods, we develop a mathematical framework that defines the types of mapping targets we uncover, establish probabilistic estimates of p-value and sensitivity, and demonstrate tolerance for alignment error rates up to 20%.…

Read More »

June 1, 2018

A short note on dynamic programming in a band.

Third generation sequencing technologies generate long reads that exhibit high error rates, in particular for insertions and deletions which are usually the most difficult errors to cope with. The only exact algorithm capable of aligning sequences with insertions and deletions is a dynamic programming algorithm.In this note, for the sake of efficiency, we consider dynamic programming in a band. We show how to choose the band width in function of the long reads' error rates, thus obtaining an [Formula: see text] algorithm in space and time. We also propose a procedure to decide whether this algorithm, when applied to semi-global…

Read More »

March 24, 2018

Darwin: A genomics co-processor provides up to 15,000 X acceleration on long read assembly

of life in fundamental ways. Genomics data, however, is far outpacing Moore’s Law. Third-generation sequencing tech- nologies produce 100× longer reads than second generation technologies and reveal a much broader mutation spectrum of disease and evolution. However, these technologies incur prohibitively high computational costs. Over 1,300 CPU hours are required for reference-guided assembly of the human genome (using [47]), and over 15,600 CPU hours are required for de novo assembly [57]. This paper describes “Darwin” — a co-processor for genomic sequence alignment that, without sacrificing sensitivity, provides up to 15,000× speedup over the state-of-the-art software for reference-guided assembly of third-generation…

Read More »

February 1, 2018

Jointly aligning a group of DNA reads improves accuracy of identifying large deletions.

Performing sequence alignment to identify structural variants, such as large deletions, from genome sequencing data is a fundamental task, but current methods are far from perfect. The current practice is to independently align each DNA read to a reference genome. We show that the propensity of genomic rearrangements to accumulate in repeat-rich regions imposes severe ambiguities in these alignments, and consequently on the variant calls-with current read lengths, this affects more than one third of known large deletions in the C. Venter genome. We present a method to jointly align reads to a genome, whereby alignment ambiguity of one read…

Read More »

January 1, 2018

ReMILO: reference assisted misassembly detection algorithm using short and long reads.

Contigs assembled from the second generation sequencing short reads may contain misassemblies, and thus complicate downstream analysis or even lead to incorrect analysis results. Fortunately, with more and more sequenced species available, it becomes possible to use the reference genome of a closely related species to detect misassemblies. In addition, long reads of the third generation sequencing technology have been more and more widely used, and can also help detect misassemblies.Here, we introduce ReMILO, a reference assisted misassembly detection algorithm that uses both short reads and PacBio SMRT long reads. ReMILO aligns the initial short reads to both the contigs…

Read More »

January 1, 2018

MUMmer4: A fast and versatile genome alignment system.

The MUMmer system and the genome sequence aligner nucmer included within it are among the most widely used alignment packages in genomics. Since the last major release of MUMmer version 3 in 2004, it has been applied to many types of problems including aligning whole genome sequences, aligning reads to a reference genome, and comparing different assemblies of the same genome. Despite its broad utility, MUMmer3 has limitations that can make it difficult to use for large genomes and for the very large sequence data sets that are common today. In this paper we describe MUMmer4, a substantially improved version…

Read More »

December 19, 2017

HISEA: HIerarchical SEed Aligner for PacBio data.

The next generation sequencing (NGS) techniques have been around for over a decade. Many of their fundamental applications rely on the ability to compute good genome assemblies. As the technology evolves, the assembly algorithms and tools have to continuously adjust and improve. The currently dominant technology of Illumina produces reads that are too short to bridge many repeats, setting limits on what can be successfully assembled. The emerging SMRT (Single Molecule, Real-Time) sequencing technique from Pacific Biosciences produces uniform coverage and long reads of length up to sixty thousand base pairs, enabling significantly better genome assemblies. However, SMRT reads are…

Read More »

December 15, 2017

Sequence variation aware genome references and read mapping with the variation graph toolkit

Reference genomes guide our interpretation of DNA sequence data. However, conventional linear references are fundamentally limited in that they represent only one version of each locus, whereas the population may contain multiple variants. When the reference represents an individualtextquoterights genome poorly, it can impact read mapping and introduce bias. Variation graphs are bidirected DNA sequence graphs that compactly represent genetic variation, including large scale structural variation such as inversions and duplications. Equivalent structures are produced by de novo genome assemblers. Here we present vg, a toolkit of computational methods for creating, manipulating, and utilizing these structures as references at the…

Read More »

December 6, 2017

A survey and evaluations of histogram-based statistics in alignment-free sequence comparison.

Since the dawn of the bioinformatics field, sequence alignment scores have been the main method for comparing sequences. However, alignment algorithms are quadratic, requiring long execution time. As alternatives, scientists have developed tens of alignment-free statistics for measuring the similarity between two sequences.We surveyed tens of alignment-free k-mer statistics. Additionally, we evaluated 33 statistics and multiplicative combinations between the statistics and/or their squares. These statistics are calculated on two k-mer histograms representing two sequences. Our evaluations using global alignment scores revealed that the majority of the statistics are sensitive and capable of finding similar sequences to a query sequence. Therefore,…

Read More »

October 3, 2017

DNA sequence alignment by window based optical correlator

In genomics, pattern matching against a sequence of nucleotides plays a pivotal role for DNA sequence alignment and comparing genomes. This helps tackling some diseases, such as cancer in humans. The complexity of searching biological sequences in big databases has transformed sequence alignment problem into a challenging field of research in bioinformatics. A large number of research has been carried to solve this problem based on electronic computers. The required extensive amount of computations for handling this huge database in electronic computers leads to vast amounts of energy consumption for electrical processing and cooling. On the other hand, optical processing…

Read More »

August 8, 2017

SureMap: Versatile, error tolerant, and high sensitive read mapper

SureMap is a versatile, error tolerant and high sensitive read mapper which is able to map "difficult" reads, those requiring many edit operations to be mapped to the reference genome, with acceptable time complexity. Mapping real datasets reveal that many variants unidentifiable by other mappers can be called using Suremap. Moreover, SureMap has a very good running time and accuracy in aligning very long and noisy reads like PacBio and Nanopore against a reference genome.

Read More »

August 1, 2017

COSINE: non-seeding method for mapping long noisy sequences.

Third generation sequencing (TGS) are highly promising technologies but the long and noisy reads from TGS are difficult to align using existing algorithms. Here, we present COSINE, a conceptually new method designed specifically for aligning long reads contaminated by a high level of errors. COSINE computes the context similarity of two stretches of nucleobases given the similarity over distributions of their short k-mers (k = 3-4) along the sequences. The results on simulated and real data show that COSINE achieves high sensitivity and specificity under a wide range of read accuracies. When the error rate is high, COSINE can offer…

Read More »

February 23, 2017

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

Current 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.We 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…

Read More »

1 2 3

Subscribe for blog updates:

Archives