Computational Method Speeds Up Estimates Of Gene Expression

April 21, 2014

PITTSBURGH, Penn., April 21 — With gene expression analysis growing in importance for both basic researchers and medical practitioners, researchers at Carnegie Mellon University and the University of Maryland have developed a new computational method that dramatically speeds up estimates of gene activity from RNA sequencing (RNA-seq) data.

With the new method, dubbed Sailfish after the famously speedy fish, estimates of gene expression that previously took many hours can be completed in a few minutes, with accuracy that equals or exceeds previous methods. The researchers’ report on their new method is being published online April 20 by the journal Nature Biotechnology.

Gigantic repositories of RNA-seq data now exist, making it possible to re-analyze experiments in light of new discoveries. “But 15 hours a pop really starts to add up, particularly if you want to look at 100 experiments,” said Carl Kingsford, an associate professor in CMU’s Lane Center for Computational Biology. “With Sailfish, we can give researchers everything they got from previous methods, but faster.”

Though an organism’s genetic makeup is static, the activity of individual genes varies greatly over time, making gene expression an important factor in understanding how organisms work and what occurs during disease processes. Gene activity can’t be measured directly, but can be inferred by monitoring RNA, the molecules that carry information from the genes for producing proteins and other cellular activities.

RNA-seq is a leading method for producing these snapshots of gene expression; in genomic medicine, it has proven particularly useful in analyzing certain cancers.

The RNA-seq process results in short sequences of RNA, called “reads.” In previous methods, the RNA molecules from which they originated could be identified and measured only by painstakingly mapping these reads to their original positions in the larger molecules.

But Kingsford, working with Rob Patro, a post-doctoral researcher in the Lane Center, and Stephen M. Mount, an associate professor in Maryland’s Department of Cell Biology and Molecular Genetics and its Center for Bioinformatics and Computational Biology, found that the time-consuming mapping step could be eliminated. Instead, they found they could allocate parts of the reads to different types of RNA molecules, much as if each read acted as several votes for one molecule or another.

Without the mapping step, Sailfish can complete its RNA analysis 20-30 times faster than previous methods.

This numerical approach might not be as intuitive as a map to a biologist, but it makes perfect sense to a computer scientist, Kingsford said. Moreover, the Sailfish method is more robust — better able to tolerate errors in the reads or differences between individuals’ genomes. These errors can prevent some reads from being mapped, he explained, but the Sailfish method can make use of all the RNA read “votes,” which improves the method’s accuracy.

The Sailfish code has been released and is available for download at http://www.cs.cmu.edu/~ckingsf/software/sailfish/.

This work was supported in part by the National Science Foundation and the National Institutes of Health.

About Carnegie Mellon University

Carnegie Mellon (www.cmu.edu) is a private, internationally ranked research university with programs in areas ranging from science, technology and business, to public policy, the humanities and the arts. More than 12,000 students in the university’s seven schools and colleges benefit from a small student-to-faculty ratio and an education characterized by its focus on creating and implementing solutions for real problems, interdisciplinary collaboration and innovation. A global university, Carnegie Mellon has campuses in Pittsburgh, Pa., California’s Silicon Valley and Qatar, and programs in Africa, Asia, Australia, Europe and Mexico.

Source: Carnegie Mellon University

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industy updates delivered to you every week!

Google Frames Quantum Race as Two-Dimensional

April 26, 2018

Quantum error correction, essential for achieving universal fault-tolerant quantum computation, is one of the main challenges of the quantum computing field and it’s top of mind for Google’s John Martinis. At a pres Read more…

By Tiffany Trader

Affordable Optical Technology Needed Says HPE’s Daley

April 26, 2018

While not new, the challenges presented by computer cabling/PCB circuit routing design – cost, performance, space requirements, and power management – have coalesced into a major headache in advanced HPC system desig Read more…

By John Russell

AI-Focused ‘Genius’ Supercomputer Installed at KU Leuven

April 24, 2018

Hewlett Packard Enterprise has deployed a new approximately half-petaflops supercomputer, named Genius, at Flemish research university KU Leuven. The system is built to run artificial intelligence (AI) workloads and, as Read more…

By Tiffany Trader

HPE Extreme Performance Solutions

Hybrid HPC is Speeding Time to Insight and Revolutionizing Medicine

High performance computing (HPC) is a key driver of success in many verticals today, and health and life science industries are extensively leveraging these capabilities. Read more…

New Exascale System for Earth Simulation Introduced

April 23, 2018

After four years of development, the Energy Exascale Earth System Model (E3SM) will be unveiled today and released to the broader scientific community this month. The E3SM project is supported by the Department of Energy Read more…

By Staff

Google Frames Quantum Race as Two-Dimensional

April 26, 2018

Quantum error correction, essential for achieving universal fault-tolerant quantum computation, is one of the main challenges of the quantum computing field an Read more…

By Tiffany Trader

Affordable Optical Technology Needed Says HPE’s Daley

April 26, 2018

While not new, the challenges presented by computer cabling/PCB circuit routing design – cost, performance, space requirements, and power management – have Read more…

By John Russell

AI-Focused ‘Genius’ Supercomputer Installed at KU Leuven

April 24, 2018

Hewlett Packard Enterprise has deployed a new approximately half-petaflops supercomputer, named Genius, at Flemish research university KU Leuven. The system is Read more…

By Tiffany Trader

Cray Rolls Out AMD-Based CS500; More to Follow?

April 18, 2018

Cray was the latest OEM to bring AMD back into the fold with introduction today of a CS500 option based on AMD’s Epyc processor line. The move follows Cray’ Read more…

By John Russell

IBM: Software Ecosystem for OpenPOWER is Ready for Prime Time

April 16, 2018

With key pieces of the IBM/OpenPOWER versus Intel/x86 gambit settling into place – e.g., the arrival of Power9 chips and Power9-based systems, hyperscaler sup Read more…

By John Russell

US Plans $1.8 Billion Spend on DOE Exascale Supercomputing

April 11, 2018

On Monday, the United States Department of Energy announced its intention to procure up to three exascale supercomputers at a cost of up to $1.8 billion with th Read more…

By Tiffany Trader

Cloud-Readiness and Looking Beyond Application Scaling

April 11, 2018

There are two aspects to consider when determining if an application is suitable for running in the cloud. The first, which we will discuss here under the title Read more…

By Chris Downing

Transitioning from Big Data to Discovery: Data Management as a Keystone Analytics Strategy

April 9, 2018

The past 10-15 years has seen a stark rise in the density, size, and diversity of scientific data being generated in every scientific discipline in the world. Key among the sciences has been the explosion of laboratory technologies that generate large amounts of data in life-sciences and healthcare research. Large amounts of data are now being stored in very large storage name spaces, with little to no organization and a general unease about how to approach analyzing it. Read more…

By Ari Berman, BioTeam, Inc.

Inventor Claims to Have Solved Floating Point Error Problem

January 17, 2018

"The decades-old floating point error problem has been solved," proclaims a press release from inventor Alan Jorgensen. The computer scientist has filed for and Read more…

By Tiffany Trader

Researchers Measure Impact of ‘Meltdown’ and ‘Spectre’ Patches on HPC Workloads

January 17, 2018

Computer scientists from the Center for Computational Research, State University of New York (SUNY), University at Buffalo have examined the effect of Meltdown Read more…

By Tiffany Trader

How the Cloud Is Falling Short for HPC

March 15, 2018

The last couple of years have seen cloud computing gradually build some legitimacy within the HPC world, but still the HPC industry lies far behind enterprise I Read more…

By Chris Downing

Russian Nuclear Engineers Caught Cryptomining on Lab Supercomputer

February 12, 2018

Nuclear scientists working at the All-Russian Research Institute of Experimental Physics (RFNC-VNIIEF) have been arrested for using lab supercomputing resources to mine crypto-currency, according to a report in Russia’s Interfax News Agency. Read more…

By Tiffany Trader

Chip Flaws ‘Meltdown’ and ‘Spectre’ Loom Large

January 4, 2018

The HPC and wider tech community have been abuzz this week over the discovery of critical design flaws that impact virtually all contemporary microprocessors. T Read more…

By Tiffany Trader

How Meltdown and Spectre Patches Will Affect HPC Workloads

January 10, 2018

There have been claims that the fixes for the Meltdown and Spectre security vulnerabilities, named the KPTI (aka KAISER) patches, are going to affect applicatio Read more…

By Rosemary Francis

Nvidia Responds to Google TPU Benchmarking

April 10, 2017

Nvidia highlights strengths of its newest GPU silicon in response to Google's report on the performance and energy advantages of its custom tensor processor. Read more…

By Tiffany Trader

Deep Learning at 15 PFlops Enables Training for Extreme Weather Identification at Scale

March 19, 2018

Petaflop per second deep learning training performance on the NERSC (National Energy Research Scientific Computing Center) Cori supercomputer has given climate Read more…

By Rob Farber

Leading Solution Providers

Lenovo Unveils Warm Water Cooled ThinkSystem SD650 in Rampup to LRZ Install

February 22, 2018

This week Lenovo took the wraps off the ThinkSystem SD650 high-density server with third-generation direct water cooling technology developed in tandem with par Read more…

By Tiffany Trader

Fast Forward: Five HPC Predictions for 2018

December 21, 2017

What’s on your list of high (and low) lights for 2017? Volta 100’s arrival on the heels of the P100? Appearance, albeit late in the year, of IBM’s Power9? Read more…

By John Russell

AI Cloud Competition Heats Up: Google’s TPUs, Amazon Building AI Chip

February 12, 2018

Competition in the white hot AI (and public cloud) market pits Google against Amazon this week, with Google offering AI hardware on its cloud platform intended Read more…

By Doug Black

HPC and AI – Two Communities Same Future

January 25, 2018

According to Al Gara (Intel Fellow, Data Center Group), high performance computing and artificial intelligence will increasingly intertwine as we transition to Read more…

By Rob Farber

US Plans $1.8 Billion Spend on DOE Exascale Supercomputing

April 11, 2018

On Monday, the United States Department of Energy announced its intention to procure up to three exascale supercomputers at a cost of up to $1.8 billion with th Read more…

By Tiffany Trader

New Blueprint for Converging HPC, Big Data

January 18, 2018

After five annual workshops on Big Data and Extreme-Scale Computing (BDEC), a group of international HPC heavyweights including Jack Dongarra (University of Te Read more…

By John Russell

Momentum Builds for US Exascale

January 9, 2018

2018 looks to be a great year for the U.S. exascale program. The last several months of 2017 revealed a number of important developments that help put the U.S. Read more…

By Alex R. Larzelere

Google Chases Quantum Supremacy with 72-Qubit Processor

March 7, 2018

Google pulled ahead of the pack this week in the race toward "quantum supremacy," with the introduction of a new 72-qubit quantum processor called Bristlecone. Read more…

By Tiffany Trader

  • arrow
  • Click Here for More Headlines
  • arrow
Share This