The ability to monitor sequencing runs in real time helps users identify issues that prevent costly sequencing errors. Many users rely on the Sequencing Analysis Viewer (SAV) to access detailed quality metrics generated by the real-time analysis software on Illumina instruments.
BaseSpace Sequence Hub has enabled users to remotely monitor their sequencing runs with the Run Charts function with a very similar interface to that of SAV. We have recently released a synchronized update with SAV to offer an expanded set of metrics for monitoring run quality. At the same time, we have added a few capabilities previously only present in SAV. These enhancements provide a consistent experience and enable users to make informed decisions on the quality of their sequencing runs – whether they are standing in front of their instrument accessing SAV or monitoring the run remotely using BaseSpace Sequence Hub.
Expanded menu of metrics that maintains consistency with SAV
BaseSpace Sequence Hub now includes per cycle Phasing and Pre-phasing metrics, % No Call, and Median QScore measures in the Charts section of Run Monitoring. These measures were also released as part of SAV 2.4.5. % No Call & Median QScores are available for all sequencing platforms. The new Phasing/Pre-phasing metrics are available for all platforms except MiSeq and HiSeq 2000/2500.
Traditional Phasing (and pre-phasing) metrics, which were calculated once at cycle 25, are now listed as “Legacy Phasing Rate.” The new per-cycle weights are listed as “Phasing Weight” in the Run Charts.
The Charts section of Run Monitoring now includes the same menu structure as SAV 2.4.5. Now, metrics in the drop down menus only appear if they are available for the cycle, significantly improving the usability of the charts.
Extracted, Called, and Scored cycles have a minimum-maximum range
Run Monitoring now provides Extracted, Called, and Scored cycles as a minimum-maximum range during an instrument run. Previously, Run Monitoring showed only the maximum cycles. A wide spread between the leading and lagging tile might be an indication of a run problem. Now users can easily spot a problem with their run on both SAV and BaseSpace Sequence Hub.
New Metrics in Both SAV and BaseSpace Sequence Hub
In addition to the changes enumerated above, both SAV and BaseSpace Sequence Hubnow include Occupied Count (K) and % Occupied measures in the Charts section of Run Monitoring for NovaSeq systems. The Occupied Count is a measure of the number of wells on the flow cell with DNA. Adding these new metrics will help users understand their loading concentrations and identify issues with their sequencing run.
For Research Use Only. Not for use in diagnostic procedures.
BaseSpace Cohort Analyzer enables users to automatically aggregate and analyze subjects with genomics and phenotype data in a few clicks. Ultimately, users can analyze and share data for biomarker discovery, translational research, and clinical trials.
One of the most powerful features of BaseSpace Cohort Analyzer is the ability to centralize all available information for a subject into a single record. This includes phenotype obtained from various phenotypic databases, lab and image data, and genomic, methylation, proteomics, and expression data, to name a few. Breaking down siloed data in this way enables users to perform integrative analyses to make meaningful discoveries in aggregated data. Now, users of BaseSpace Cohort Analyzer can take advantage of a new beta feature: the Data Uploader.
Data Uploader: Import Somatic, CNV, RNA-Seq and >500 Phenotypical Attributes
You can now easily import your genomic data (somatic mutation or copy number variations between tumor and normal samples), or RNA-Seq data into BaseSpace Cohort Analyzer for analysis. Either upload your own files or directly import from a BaseSpace Sequence Hub Enterprise account. The uploader supports >500 phenotype and subject measurements.
Uploading and Analyzing Data
1. Upload in 2 Steps through the Data Uploader (beta)
- Load data with >500 of phenotypic attributes, including age, gender, condition, therapies, overall survival and other outcomes.
- Load genomic data and RNA-seq data directly from BaseSpace Sequence Hub, or from a desktop in multiple formats.
- Check your data to catch formatting errors prior to ingestion.
2. Process and integrate your data so you can analyze it in real time within BaseSpace Cohort Analyzer.
- Monitor and view study import status through a user interface
- Automatically add meaningful content for analysis such as calculating tumor mutation burden for all uploaded somatic mutation data
3. Analyze Data in BaseSpace Cohort Analyzer
After your data is uploaded, perform cohort analysis using over 100 bioinformatic workflows and
- Compare your data with other datatypes or technologies
- Load and view everything associated to a single subject in one place
- Filter and select a cohort based on any phenotype or molecular marker(s).
- Integrate and analyze your data with clinical outcomes and therapies
- Understand the survival, molecular, and clinical differences between two groups
- Find expression outliers in your cohort of interest
- Research meaningful biomarkers and drug targets
For more information about BaseSpace Cohort Analyzer, the Data Uploader or to sign up for a free trial, please contact us at email@example.com.
For Research Use Only. Not for use in diagnostic procedures.
BaseSpace Cohort Analyzer enables users to apply complex genomic data in novel ways across the entire drug discovery and development process. Pharmaceutical and biotechnology organizations can incorporate data analysis and interpretation into biomarker discovery, translational research, and clinical trials.
We are writing to summarize recent changes to BaseSpace Cohort Analyzer and to share our plans for 2017.
Last year our main focus was on enabling you to upload basic cancer data in a quick, easy, automated and secure manner. We implemented the following features:
We are pleased to announce a minor release of BaseSpaceCLI (0.8.10) with some improvements to existing tools and a new tool –
wait command for BaseSpaceCLI is analogous to the shell command wait and was designed to help connect together separate app launches. The
wait command accepts as arguments one or more appsessions and will then wait for these appsessions to finish, polling based on a specified interval (default 60 seconds). Once they have all finished,
bs wait returns the appresults that have been generated by the provided appsessions. The intention is that these appresults can then be passed into another app launch, providing some limited app-chaining capabilities.
We are pleased to announce the third release (version 0.8) of BaseSpaceCLI, which includes a major new tool and a number of minor features. To install the new release, run this script:
$ sudo bash -c "$(curl -L https://bintray.com/artifact/download/basespace/helper/install.sh)"
With this release of BaseSpaceCLI we are introducing a new high-performance copy tool called BaseSpace Copy or bscp, which provides the following features:
- Rich and flexible URI mechanism to specify source and target for copies
- Multi-threaded for performance and to cope with high-latency connections
- Excellent data integrity, all part data is hashed and verified. Ability to export md5sum compatible sum file for future data verification.
- Resumable downloading
We’ve recently added some improvements to the Sequencing Runs list. These updates should help to quickly get basic quality information about each run, without needing to click into Run details pages.
For example, % reads passed filter (%PF), average %Q30, yield, and cycles (for Read1 and Read2) are now columns on the Runs list.