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:

An Interview with Baylor’s Fritz Sedlazeck on New Long-Read Algorithms

Monday, April 30, 2018

structural variation with Sniffles and NGMLR

Fritz Sedlazeck

Nature Methods just published “Accurate detection of complex structural variations using single-molecule sequencing,” a publication that presents the NGMLR aligner and Sniffles structural variant caller, both designed for use with long-read sequencing data. We chatted with developer and lead author Fritz Sedlazeck from the Human Genome Sequencing Center at Baylor to learn more.

Q: Why was a new alignment tool needed when many scientists already use BWA and other methods?

A: When I started my postdoc in Mike Schatz’s lab at Cold Spring Harbor, I had the opportunity to look at the complex SK-BR-3 cell lines. We soon discovered two challenges not addressed effectively by existing aligners: mapping split reads correctly, and handling the random short insertion and deletion errors that are characteristic of long reads.

Q: Why was Sniffles needed for structural variant detection?

A: Most of the methods for structural variant detection focus on paired-end reads. There were no appropriate structural variant calling tools at the time for long-read data, and very few callers that take into account split-read alignments. You have to have a method that parses through the full read.

Q: When you applied these tools to long-read data, what could you see that wasn’t visible before?

A: Before we started to think about how we could improve the alignments and structural variant calling, we spent a lot of time looking at IGV, focusing on single reads in complex regions like oncogenes. We knew there were some events that were hidden from us, and we saw a lot of noise coming out. That really motivated us to develop these new tools to find the signal in the noise. When we first applied them, very quickly we were detecting these structural variants. Some of the first results from Sniffles were identifications of amplification events and inversions that had not been found before.

Q: You’ve talked about plans to sequence 100 people with SMRT Sequencing from PacBio. What are the goals of that study?

A: This study is aiming at the concept of comprehensive genomes, or what Richard Gibbs calls “super-genomes.” We have SNP calls from Illumina, PacBio reads to call structural variants, and for a few samples we have 10x Genomics data for really long phasing. Our best example so far is a 67 Mb phasing block N50 for SNV and SVs. This pilot study covers many different ethnicities. The majority of samples are from African Americans, and there are many samples from Hispanic individuals as well. There are just a few Caucasians. We hope to get a good ethnicity-specific structural variant call set that we can use to inform other studies as well. We are confident that we’ll be able to identify many more structural variants that are invisible to short-read data.

Q: How much long-read coverage is needed for accurate structural variant discovery in a human genome?

A: We are aiming for about 10-fold coverage, which leaves us with 5-fold per haplotype. That’s enough for good coverage of each chromosome and lets us see the vast majority of structural variants.

For more technical detail about Sniffles and NGMLR, check out our blog post covering this paper as a preprint or attend the upcoming LabRoots webinar on May 9, in which Sedlazeck will give a talk entitled “Size Matters: Accurate Detection and Phasing of Structural Variations.”

Subscribe for blog updates:

Archives