BaseSpace™ Sequence Hub is used by investigators around the world to facilitate and scale their sequencing and genomic data analysis operations. At Illumina, we understand that security, privacy, and confidentiality are complex issues, and we are committed to protecting our software-as-a-service (SaaS) customers’ data.
To ensure that our customers remain compliant with upcoming changes to the EU General Data Protection Regulation (GDPR), we’ve made a number of updates to privacy practices, policies and agreements that are effective May 25, 2015 for all users globally. These changes include explaining in more detail how we use your information, including your choices, rights, and controls.
Privacy and compliance is a shared responsibility between Illumina and our customers. We are responsible for the security of the BaseSpace Sequence Hub platform. Our cloud provider, Amazon Web Services (AWS) is responsible for providing the tools, services and functionality that enable both the data controller (our customers) and the data processor (Illumina) to be successful.
Figure 1: Shared responsibility Model
A short summary of our changes:
- Improved clarity and transparency.As a key part of GDPR compliance, we’ve described our data processing practices in clear language. For instruments sending Performance Data (IPD) to BaseSpace Sequence Hub, or connected in the Run Monitoring or Storage and Analysis mode, our updated Illumina®Proactive Technical Note (Link) clearly explains what data is sent to BaseSpace in each of the connectivity modes.
- Data Protection Addendum:BaseSpace Sequence Hub leverages AWS to deliver its services. The updated AWS Service Terms (Link) incorporate the GDPR Data Processing Addendum (DPA) and will automatically apply to all customers. Illumina is willing to sign a DPA for customers who ask for it.
- Opt-in & Opt-out:Sharing data with BaseSpace Sequence Hub, irrespective of connectivity mode, is entirely controlled by our customers. If you would like to opt out of sharing Instrument Performance Data (IPD), Run Monitoring, or Storage and Analysis mode, you can do so at any time.
In addition, we are continually reviewing and updating our security best practices to safeguard your data and the services we provide. We are ISO 27001 certified, which has a direct emphasis on international compliance and governance. Please review our security and data privacy whitepaper (Link) to learn more about our security practices.
We hope this makes your use of our SaaS products much easier. As always, please contact us at firstname.lastname@example.org if you have any questions.
Integration and interoperability between laboratory systems –or lack thereof—remains a challenge for those performing next-generation sequencing (NGS) or other genomics studies.[i] To address this challenge, we developed version 2.2 of the integration between BaseSpace Clarity LIMS and the NovaSeq 6000 instrument. This integration now supports the NovaSeq S1 flow cell.
The NovaSeq S1 flow cell delivers up to 0.5TB of output in two days and is ideally suited for high-intensity sequencing applications. Users can now sequence up to 8 human genomes or 80 exomes per run in approximately 24 hours.[ii] And now, users of both Basespace Clarity LIMS and NovaSeq 6000 instrument can access this out-of-the box integration to quickly get up and running with their system.
The NovaSeq 6000 version 2.0 Workflow in BaseSpace Clarity LIMS that supports the integration version 2.2.1
The integration helps users track samples throughout the workflow. Specifically, it:
- Supports S1, S2, and S4 flow cells per sample
- Supports different applications on the same flow cell
- Calculates samples and reagents volumes based on the flow cell type
- Creates an output file for use with liquid handling robots
- Validates every step in the workflow
The integration also tracks sequencing run information in BaseSpace Clarity LIMS to help with troubleshooting or trending:
- Run recipe files (JSON) are automatically generated to set up and initiate the run
- Sample sheets, which are compatible with BaseSpace Sequence Hub and bcl2fastq v 2.19, are automatically generated and placed directly on the NovaSeq 6000 instrument
- Sequencing run are tracked and run metrics are parsed per lane and per flow cell
If you have questions about this integration, please contact Technical Support.
For Research Use Only. Not for use in diagnostic procedures.
[i] Next-Generation Sequencing Informatics: Challenges and … http://www.bing.com/cr?IG=74008A18392242E59F11965A936C0331&CID=1B0873003B0C6EB91053783A3A0A6F0E&rd=1&h=qZ8eqx6ov_OxkAzDtTWfrbsSZM2WP_pCoQuO66f-AVI&v=1&r=http%3a%2f%2fwww.archivesofpathology.org%2fdoi%2f10.5858%2farpa.2015-0507-RA&p=DevEx,5067.1. Accessed November 14, 2017.
[ii] Illumina.com. (2017). Illumina Releases NovaSeq S4 Flow Cell and NovaSeq Xp Workflow. [online] Available at: https://www.illumina.com/company/news-center/press-releases/2017/2308795.html [Accessed 16 Nov. 2017].
A guest blog, written by GoSeqIt
In an increasingly globalized world, bacteria can spread rapidly and easily. Furthermore, they often contain genes that make them resistant to antibiotics or confer high virulence. Sequencing the entire genome of bacteria enables a thorough characterization and thus makes it possible for researchers to monitor the spread of particular strains of bacteria or sets of genes.
In collaboration with the Illumina BaseSpace Sequence Hub development team, GoSeqIt has published two apps for characterization of bacterial single isolates. Both of these apps are now available to BaseSpace Sequence Hub users:
The input for both apps is a bacterial complete or draft genome in FASTA format (only files with the extension .fa or .fasta are accepted).
Bacterial Analysis Pipeline App
The Bacterial Analysis Pipeline app will initially predict the species of the bacterial draft genome based on the number of kmers (oligonucleotides with the length k) co-occurring between the input genome and bacterial genomes in a reference database (1). Further, acquired antimicrobial resistance genes are identified using a BLAST-based approach, where the nucleotide sequence of the input genome is compared to the genes in the ResFinder database (2). Depending on the identified species, Multilocus Sequence Typing (MLST) is performed, also using a BLAST-based approach (3). One-hundred-twenty-five (125) MLST schemes are currently available.
If the input genome is recognized as belonging to Enterobacteriaceae or the gram positive bacteria (Enterococcus, Streptococcus, or Staphylococcus), BLAST is used to search for plasmid replicons using the PlasmidFinder database (4). Identified plasmids of the incF, IncH1, IncH2, IncI1, IncN, or IncA/C type are further subtyped by plasmid MLST (4). Finally, identified Escherichia coli, Enterococcus sp., Listeria sp., and Staphylococcus aureus are compared to the VirulenceFinder database containing known virulence genes (5). For more information, refer to the article titled “Bacterial Analysis Platform: An Integrated System for Analysing Bacterial Whole Genome Sequencing Data for Clinical Diagnostics and Surveillance.” Figure 1 illustrates the output for species prediction and MLST, while figure 2 illustrates the output for the prediction of acquired antimicrobial resistance genes.
Figure 1: Example of output from the Bacterial Analysis Pipeline app for species prediction and MLST of the input genome.
Figure 2: Example of output from the Bacterial Analysis Pipeline app for acquired antimicrobial resistance genes in the input genome.
E. coli Serotyping App
The E. coli Serotyping app uses a BLAST-based approach to predict the serotype of E. coli isolates by comparing the input genome with a database of specific O-antigen processing system genes for O typing and flagellin genes for H typing (7). The app outputs the predicted serotype along with the identified O-antigen genes (wzx, wzy, wzm, and wzt) and flagellin genes (fliC, flkA, fllA, flmA, and flnA).
Figure 3: Example of output from the E. coli Serotyping app. So far, only E. coli isolates can in this way be in silico serotyped.
Using the New Apps
The price for using the Bacterial Analysis Pipeline app is 5 iCredits per uploaded file plus the cost of computing. The E. coli Serotyping app costs 1 iCredit per uploaded file plus the cost of computing.
Both apps use methods that have been throughly described and published in renowned scientific journals.
1) Larsen MV, Cosentino S, Lukjancenko O, Saputra D, Rasmussen S, Hasman H, Sicheritz-Pontén T, Aarestrup FM, Ussery DW, Lund O. Benchmarking of methods for genomic taxonomy. J Clin Microbiol. 2014 May;52(5):1529-39. PMID: 24574292.
2) Zankari E, Hasman H, Cosentino S, Vestergaard M, Rasmussen S, Lund O, Aarestrup FM, Larsen MV. Identification of acquired antimicrobial resistance genes. J Antimicrob Chemother. 2012 Nov;67(11):2640-4. PMID: 22782487.
3) Larsen MV, Cosentino S, Rasmussen S, Friis C, Hasman H, Marvig RL, Jelsbak L, Sicheritz-Pontén T, Ussery DW, Aarestrup FM, Lund O. Multilocus sequence typing of total-genome-sequenced bacteria. J Clin Microbiol. 2012 Apr;50(4):1355-61. PMID: 22238442.
4) Carattoli A, Zankari E, García-Fernández A, Voldby Larsen M, Lund O, Villa L, Møller Aarestrup F, Hasman H. In silico detection and typing of plasmids using PlasmidFinder and plasmid multilocus sequence typing. Antimicrob Agents Chemother. 2014 Jul;58(7):3895-903. PMID: 24777092.
5) Joensen KG, Scheutz F, Lund O, Hasman H, Kaas RS, Nielsen EM, Aarestrup FM. Real-time whole-genome sequencing for routine typing, surveillance, and outbreak detection of verotoxigenic Escherichia coli. J Clin Microbiol. 2014 May;52(5):1501-10. PMID: 24574290.
6) Thomsen MC, Ahrenfeldt J, Cisneros JL, Jurtz V, Larsen MV, Hasman H, Aarestrup FM, Lund O. A Bacterial Analysis Platform: An Integrated System for Analysing Bacterial Whole Genome Sequencing Data for Clinical Diagnostics and Surveillance. PLoS One. 2016 Jun 21;11(6):e0157718. PMID: 27327771.
7) Joensen KG, Scheutz F, Lund O, Hasman H, Kaas RS, Nielsen EM, Aarestrup FM. Real-time whole-genome sequencing for routine typing, surveillance, and outbreak detection of verotoxigenic Escherichia coli. J Clin Microbiol. 2014 May;52(5):1501-10. PMID: 24574290.
For Research Use Only. Not for use in diagnostic procedures.
We want to invite all of you to the BaseSpace Developer Conference in San Francisco! We’ve been active with many BaseSpace Developer Conferences throughout the world this year, including Heidelberg, Singapore, Bangalore, and our most recent visit to the University of Tokyo in Japan!
First of all, we would like to thank all of our developers and speakers, you all made this possible. We hope it was a great learning experience and look forward to the apps we can bring to BaseSpace. Also, a big shout out to the University of Tokyo for hosting the event and our Illumina team in Japan.
The events showcase the new Native App Engine within BaseSpace with which developers can easily adapt their command-line pipelines into the BaseSpace cloud infrastructure or an infrastructure of their choice.
During the event, developers are taken through a step-by-step walkthrough where they develop two separate BaseSpace applications by the end! For anyone that is interested in learning more about BaseSpace App development, there is a lot of documentation available on the BaseSpace Developer Portal for both Native and Web applications.
We also spend time interacting with developers and users directly to brainstorm ideas and answer any questions they may have.
We are hosting another BaseSpace Developer Conference in San Francisco on December 8th, if you are interested in attending you can sign up here.
To get an idea of whats in store for you when you attend one of our developer conferences, check us out on twitter at #basedev2014.
For any further questions about BaseSpace App development, please view or post on the developer forum or contact us through BaseSpace support.
Velvet de novo Assembly FastQC
Both applications are currently available for all users and were built using the BaseSpace Native App Engine by our internal R&D groups. These two applications are also the first BaseSpace Labs Apps of many more to come, the concept behind BaseSpace Labs Apps is explained in more detail below.
BaseSpace Labs Apps are Illumina’s internally developed applications that extend the functionality within BaseSpace. Some BaseSpace Labs applications will be experimental or research focused, while others will be used as a step in a greater workflow. The Apps are reviewed regularly by our team and put through the same review process as third-party apps.
BaseSpace Labs Apps are developed using an accelerated development process in order to make them available to BaseSpace users faster than the BaseSpace Core Apps. It is important to note that, unlike BaseSpace Core Apps, BaseSpace Labs Apps are not officially supported by Illumina Customer Service. Support for BaseSpace Labs applications is provided at the developer’s discretion and the apps are provided as-is without any warranty of any kind.
The FastQC app can be used to provide a quality assessment of the sequence data generated using Illumina sequencers. FastQC for BaseSpace is based on the FastQC software developed by the Bioinformatics Group at the Babraham Institute. It provides a modular set of analyses which can be used quickly to assess if there are any problems with the sequencing data before doing any additional analysis.
The above figure shows an example output from the FastQC app depicting the quality score across all bases at a given position in the reads. For an example of additional output generated by FastQC, please view this FastQC demo project.
The Velvet de novo Assembly app is a de novo assembly pipeline for bacterial samples using the Velvet assembler. One of the key features of this app is that it has an adapter trimming protocol that has been optimized for the Nextera Mate-Pair library prep kit. An application note describing the de novo assembly of 9 different bacterial using the Velvet de novo Assembly app can be found here. In many cases, a single contig representing the entire bacterial genome can be assembled. The figure below is an example of the output generate by the Velvet de novo Assembly app.
Example output generated by the Velvet de novo Assembly can be found here. We hope you enjoy the FastQC and Velvet de novo Assembly apps. For any questions, feedback, or feature requests for these applications, please send an email to email@example.com and include the name of the application. Thank you!
DeepChek®-HIV – App for genotyping by NGS and inferred drug resistance testing – for research use only
HIV genotyping and inferred drug resistance testing has become an integral part of the clinical management of patients infected with HIV. Detecting minority populations of resistant viruses is now routinely done. Next-generation sequencing (NGS) technology is replacing Sanger sequencing methodology, and end-to-end solutions combining sensitive genomic tests with advanced data management software platforms are in high demand.
DeepChek®-HIV is easy-to-use downstream analysis software for NGS data management, interpretation, and reporting for Research Use Only. DeepChek is a reliable software and database solution that is capable of handling the complexity of NGS data for all the key genomic regions involved in HIV drug resistance (reverse transcriptase, protease, integrase, GP41, and GP120/V3). The database is regularly updated with the most recent drug resistance information and provides an efficient and downstream analysis platform for clinical laboratories involved in routine HIV-1 genotyping and drug resistance testing.
Link to App in BaseSpace:
Link to example dataset with example input data and output results:
Registration is now open for the BaseSpace Developer’s Meeting at the European Molecular Biology Laboratory (EMBL) Heidelberg, Germany on May 7, 2014. This free, one-day forum is a great opportunity for both experienced and novice developers to network, exchange ideas, and learn more about the world’s most widely used cloud-based bioinformatics platform for next-generation sequencing. Participants will use the BaseSpace Native App Engine to launch their own bioinformatics apps in BaseSpace.
Why develop for BaseSpace? Because 90% of the world’s next-gen sequencing data is produced on Illumina instruments, and your novel algorithms, open-source tools, and applications for BaseSpace users can directly impact the growth of genomic research. In short, you can change the way the world analyzes genomic data.
Welcome to EMBL & Illumina’s Co-Hosting of 2014 BaseSpace WWDC
Jonathon Blake, Ph.D., Bioinformatics, EMBL
Raymond Tecotzky, Market Manager, BaseSpace, Illumina, Inc.
Keynote: BaseSpace and The Next Frontier for Genomics Storage, Sharing, and Analysis
Elliott Margulies, Ph.D., Product Owner, BaseSpace, Illumina, Inc.
Biomax PEDANT – Pathway Analysis for NGS Data
Dimitrij Frishman, Ph.D., Professor of Bioinformatics, Technical University in Munich, Germany
New Frontiers of Genome Assembly with SPAdes 3.0 on Illumina BaseSpace Platform
Anton Korobeynikov, Ph.D., Associate Professor Saint Petersberg State University, St. Petersburg, Russian Federation
ABL (Advanced Biology Laboratories/Therapy Edge) DeepChek® Hep B & C Detection App
Dr. Chalom Sayada, CEO, Advanced Biological Laboratories SA
Hands-On Session: Build Your Own BaseSpace App
Greg Roberts, Senior Staff Software Engineer, Illumina, Inc.
Mayank Tyagi, Senior Applications Support Engineer, Illumina, Inc.
Hands-On “Hackathon” Build Your Own BaseSpace App (Choose from Open-Source, Command-Line, or Bring Your Own Code)
Ilya Chorny, Sequencing Application Marketing, Illumina, Inc.
BaseSpace Onsite Introduction – Storage, Sharing, & Analysis in a Box
John Duddy, Senior Staff Software Engineer. Illumina, Inc.
Will be followed by a Networking Reception
Date: Wednesday 7 May, 2014 9:00-6:30 PM
69117 Heidelberg, Germany
Flex Lab A+B
Got a killer NGS app? Enter your original idea and win an iPad mini at the conference!