‘Sailfish’ Accelerates Gene Expression Analysis

By Tiffany Trader

April 24, 2014

“Sailfish” is a new computational method out of Carnegie-Mellon University and the University of Maryland that speeds up RNA sequencing analysis by a factor of 20 or greater.

The method – dubbed Sailfish after the super-speedy fish – provides quantification estimates of gene expression much faster than previous methods such that a job that once took hours can now be completed in a few minutes without loss of accuracy. Details of the research have been published online in the journal Nature Biotechnology.

Gene expression is the process by which genes (stretches of DNA that encode information) interact to produce different traits, such as blue eyes or a predisposition toward cancer. Gene expression occurs in all known life – it’s how the genetic code stored in DNA is “interpreted.”

Along with major advances in genomics, gene expression analysis has grown in importance both for basic researchers and medical practitioners. There now exists large stores of RNA-seq data that scientists are using to re-analyze experiments, however the analysis is notoriously time-intensive with an average run taking about 15 hours.

Fifteen hours might not seem like a lot, but when you multiply that by 100 experiments, it adds up, says paper co-author Carl Kingsford, an associate professor in CMU’s Lane Center for Computational Biology, adding “with Sailfish, we can give researchers everything they got from previous methods, but faster.”

An organism’s genetic makeup is static, but the activity of individual genes varies greatly over time, explains the writeup from Carnegie Mellon. Gene expression is the key – it’s a research area that holds tremendous promise for disease prevention. Although gene activity can’t be measured directly, it can be inferred by tracking RNA, large molecules that perform vital roles in the coding, decoding, regulation, and expression of genes.

To observe RNA, scientists typically use a method called RNA-seq, which has been useful in the field of genomic medicine in the analysis of certain cancers. The process results in short segments of RNA, called “reads.” In previous methods, reconstructing RNA molecules in order to measure them employed a process called mapping where reads were mapped back to their original positions in the larger molecules like pieces in a puzzle. The research team was able to eliminate this time-consuming step by allocating parts of the reads to different types of RNA molecules. Essentially each read provides several up-votes for a given molecule. By leaving out the mapping step, Sailfish is able to perform its RNA analysis 20-30 times faster than previous methods.

The numerical approach will be more familiar to computer scientists than biologists, Kingsford notes, but Sailfish is more robust and better able to tolerate errors. Errors that would disrupt a mapping are not a problem for the “+1” approach. The result is increased accuracy.

“By facilitating frequent reanalysis of data and reducing the need to optimize parameters, Sailfish exemplifies the potential of lightweight algorithms for efficiently processing sequencing reads,” the authors write in the paper abstract.

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

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!

China’s TianHe-2A will Use Proprietary Accelerator and Boast 94 Petaflops Peak

September 25, 2017

The details of China’s upgrade to TianHe-2 (MilkyWay-2) – now TianHe-2A – were revealed last week at the Third International High Performance Computing Forum (IHPCF2017) in China. The TianHe-2A will use a proprieta Read more…

By John Russell

SC17 Preview: Invited Talk Lineup Includes Gordon Bell, Paul Messina and Many Others

September 25, 2017

With the addition of esteemed supercomputing pioneer Gordon Bell to its invited talk lineup, SC17 now boasts a total of 12 invited talks on its agenda. As SC explains, "Invited Talks are a premier component of the SC Read more…

By Tiffany Trader

GlobalFoundries Puts Wind in AMD’s Sails with 12nm FinFET

September 24, 2017

From its annual tech conference last week (Sept. 20), where GlobalFoundries welcomed more than 600 semiconductor professionals (reaching the Santa Clara venue’s max capacity and doubling 2016 attendee numbers), the one Read more…

By Tiffany Trader

HPE Extreme Performance Solutions

HPE Prepares Customers for Success with the HPC Software Portfolio

High performance computing (HPC) software is key to harnessing the full power of HPC environments. Development and management tools enable IT departments to streamline installation and maintenance of their systems as well as create, optimize, and run their HPC applications. Read more…

Machine Learning at HPC User Forum: Drilling into Specific Use Cases

September 22, 2017

The 66th HPC User Forum held September 5-7, in Milwaukee, Wisconsin, at the elegant and historic Pfister Hotel, highlighting the 1893 Victorian décor and art of “The Grand Hotel Of The West,” contrasted nicely with Read more…

By Arno Kolster

China’s TianHe-2A will Use Proprietary Accelerator and Boast 94 Petaflops Peak

September 25, 2017

The details of China’s upgrade to TianHe-2 (MilkyWay-2) – now TianHe-2A – were revealed last week at the Third International High Performance Computing Fo Read more…

By John Russell

GlobalFoundries Puts Wind in AMD’s Sails with 12nm FinFET

September 24, 2017

From its annual tech conference last week (Sept. 20), where GlobalFoundries welcomed more than 600 semiconductor professionals (reaching the Santa Clara venue Read more…

By Tiffany Trader

Machine Learning at HPC User Forum: Drilling into Specific Use Cases

September 22, 2017

The 66th HPC User Forum held September 5-7, in Milwaukee, Wisconsin, at the elegant and historic Pfister Hotel, highlighting the 1893 Victorian décor and art o Read more…

By Arno Kolster

Stanford University and UberCloud Achieve Breakthrough in Living Heart Simulations

September 21, 2017

Cardiac arrhythmia can be an undesirable and potentially lethal side effect of drugs. During this condition, the electrical activity of the heart turns chaotic, Read more…

By Wolfgang Gentzsch, UberCloud, and Francisco Sahli, Stanford University

PNNL’s Center for Advanced Tech Evaluation Seeks Wider HPC Community Ties

September 21, 2017

Two years ago the Department of Energy established the Center for Advanced Technology Evaluation (CENATE) at Pacific Northwest National Laboratory (PNNL). CENAT Read more…

By John Russell

Exascale Computing Project Names Doug Kothe as Director

September 20, 2017

The Department of Energy’s Exascale Computing Project (ECP) has named Doug Kothe as its new director effective October 1. He replaces Paul Messina, who is stepping down after two years to return to Argonne National Laboratory. Kothe is a 32-year veteran of DOE’s National Laboratory System. Read more…

Takeaways from the Milwaukee HPC User Forum

September 19, 2017

Milwaukee’s elegant Pfister Hotel hosted approximately 100 attendees for the 66th HPC User Forum (September 5-7, 2017). In the original home city of Pabst Blu Read more…

By Merle Giles

Kathy Yelick Charts the Promise and Progress of Exascale Science

September 15, 2017

On Friday, Sept. 8, Kathy Yelick of Lawrence Berkeley National Laboratory and the University of California, Berkeley, delivered the keynote address on “Breakthrough Science at the Exascale” at the ACM Europe Conference in Barcelona. In conjunction with her presentation, Yelick agreed to a short Q&A discussion with HPCwire. Read more…

By Tiffany Trader

How ‘Knights Mill’ Gets Its Deep Learning Flops

June 22, 2017

Intel, the subject of much speculation regarding the delayed, rewritten or potentially canceled “Aurora” contract (the Argonne Lab part of the CORAL “ Read more…

By Tiffany Trader

Reinders: “AVX-512 May Be a Hidden Gem” in Intel Xeon Scalable Processors

June 29, 2017

Imagine if we could use vector processing on something other than just floating point problems.  Today, GPUs and CPUs work tirelessly to accelerate algorithms Read more…

By James Reinders

NERSC Scales Scientific Deep Learning to 15 Petaflops

August 28, 2017

A collaborative effort between Intel, NERSC and Stanford has delivered the first 15-petaflops deep learning software running on HPC platforms and is, according Read more…

By Rob Farber

Oracle Layoffs Reportedly Hit SPARC and Solaris Hard

September 7, 2017

Oracle’s latest layoffs have many wondering if this is the end of the line for the SPARC processor and Solaris OS development. As reported by multiple sources Read more…

By John Russell

Six Exascale PathForward Vendors Selected; DoE Providing $258M

June 15, 2017

The much-anticipated PathForward awards for hardware R&D in support of the Exascale Computing Project were announced today with six vendors selected – AMD Read more…

By John Russell

Top500 Results: Latest List Trends and What’s in Store

June 19, 2017

Greetings from Frankfurt and the 2017 International Supercomputing Conference where the latest Top500 list has just been revealed. Although there were no major Read more…

By Tiffany Trader

IBM Clears Path to 5nm with Silicon Nanosheets

June 5, 2017

Two years since announcing the industry’s first 7nm node test chip, IBM and its research alliance partners GlobalFoundries and Samsung have developed a proces Read more…

By Tiffany Trader

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

Leading Solution Providers

Graphcore Readies Launch of 16nm Colossus-IPU Chip

July 20, 2017

A second $30 million funding round for U.K. AI chip developer Graphcore sets up the company to go to market with its “intelligent processing unit” (IPU) in Read more…

By Tiffany Trader

Google Releases Deeplearn.js to Further Democratize Machine Learning

August 17, 2017

Spreading the use of machine learning tools is one of the goals of Google’s PAIR (People + AI Research) initiative, which was introduced in early July. Last w Read more…

By John Russell

Russian Researchers Claim First Quantum-Safe Blockchain

May 25, 2017

The Russian Quantum Center today announced it has overcome the threat of quantum cryptography by creating the first quantum-safe blockchain, securing cryptocurrencies like Bitcoin, along with classified government communications and other sensitive digital transfers. Read more…

By Doug Black

EU Funds 20 Million Euro ARM+FPGA Exascale Project

September 7, 2017

At the Barcelona Supercomputer Centre on Wednesday (Sept. 6), 16 partners gathered to launch the EuroEXA project, which invests €20 million over three-and-a-half years into exascale-focused research and development. Led by the Horizon 2020 program, EuroEXA picks up the banner of a triad of partner projects — ExaNeSt, EcoScale and ExaNoDe — building on their work... Read more…

By Tiffany Trader

Google Debuts TPU v2 and will Add to Google Cloud

May 25, 2017

Not long after stirring attention in the deep learning/AI community by revealing the details of its Tensor Processing Unit (TPU), Google last week announced the Read more…

By John Russell

Amazon Debuts New AMD-based GPU Instances for Graphics Acceleration

September 12, 2017

Last week Amazon Web Services (AWS) streaming service, AppStream 2.0, introduced a new GPU instance called Graphics Design intended to accelerate graphics. The Read more…

By John Russell

Cray Moves to Acquire the Seagate ClusterStor Line

July 28, 2017

This week Cray announced that it is picking up Seagate's ClusterStor HPC storage array business for an undisclosed sum. "In short we're effectively transitioning the bulk of the ClusterStor product line to Cray," said CEO Peter Ungaro. Read more…

By Tiffany Trader

IBM Advances Web-based Quantum Programming

September 5, 2017

IBM Research is pairing its Jupyter-based Data Science Experience notebook environment with its cloud-based quantum computer, IBM Q, in hopes of encouraging a new class of entrepreneurial user to solve intractable problems that even exceed the capabilities of the best AI systems. Read more…

By Alex Woodie

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