Pegasus statistics

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Citations per year

Number of citations per year for the bioinformatics software tool Pegasus

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Pegasus specifications


Unique identifier OMICS_16784
Name Pegasus
Software type Framework/Library
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS
Programming languages Python
License Apache License version 2.0
Computer skills Advanced
Version 4.7.4
Stability Stable
Maintained Yes




No version available



  • person_outline Ewa Deelman

Publications for Pegasus

Pegasus citations


Reproducible Large Scale Neuroimaging Studies with the OpenMOLE Workflow Management System

Front Neuroinform
PMCID: 5361107
PMID: 28381997
DOI: 10.3389/fninf.2017.00021

[…] et al., ) was one of the first general-purpose scientific workflow systems, recognizing the need for transparent and simplified access to high performance computing platforms more than a decade ago. Pegasus (Deelman et al., ) is a system that initially gained popularity for mapping complex workflows to resources resources in distributed environments without requiring input from the user.PSOM (Pip […]


Enhancing knowledge discovery from cancer genomics data with Galaxy

PMCID: 5437943
PMID: 28327945
DOI: 10.1093/gigascience/gix015

[…] me this, GUI-enabled software for automating pipeline development improves the reproducibility, accessibility, and transparency of running genomic analyses []. Examples include Galaxy [], Taverna [], Pegasus [], and commercial software packages such as Geneious []. In particular, the Galaxy project offers many attractive features for this goal while remaining open-source. Namely, Galaxy boasts ext […]


Dynamic Voltage Frequency Scaling Simulator for Real Workflows Energy Aware Management in Green Cloud Computing

PLoS One
PMCID: 5234838
PMID: 28085932
DOI: 10.1371/journal.pone.0169803

[…] re small tasks on large jobs are linked to reduce overloads. Further, it allows experiments with real workflows described in DAX format or Directed Acyclic Graphs (DAGs) in XML format [], used by the Pegasus system [] workflows in a way that new scheduling algorithms can be validated in realistic scenarios. WorkflowSim also allows mechanisms for fault simulation in task execution and moreover, it […]


PGen: large scale genomic variations analysis workflow and browser in SoyKB

BMC Bioinformatics
PMCID: 5074001
PMID: 27766951
DOI: 10.1186/s12859-016-1227-y
call_split See protocol

[…] G. Max Williams 82 Wm82.a2.v1 version [] available via Phytozome [] was used as the reference genome for this analysis. We built the PGen multi-step workflow using the Pegasus [] workflow management system (Pegasus-WMS) as shown in Fig. , using many widely accepted open-source NGS tools for quality checks, alignment of reads, variants calling, variants filtration, v […]


OSG GEM: Gene Expression Matrix Construction Using the Open Science Grid

Bioinform Biol Insights
PMCID: 4972127
PMID: 27499617
DOI: 10.4137/BBI.S38193

[…] uantities of short sequences from HTS are processed. The GEM workflow developed for the OSG may be modified to enable transfer of any HTC systems, including a local campus cluster, grid, or cloud.The Pegasus Workflow Management System enables the execution of large-scale computational workflows on a variety of infrastructures. Pegasus workflows are described as abstract directed acyclic graphs (DA […]


Evaluation of genetic variation among Brazilian soybean cultivars through genome resequencing

BMC Genomics
PMCID: 4752768
PMID: 26872939
DOI: 10.1186/s12864-016-2431-x

[…] tic NGS resequencing data analysis workflow [] developed in SoyKB for SNP and Indel calling. XSEDE [] was used as the computing infrastructure, iPlant as the data and cloud infrastructure [], and the Pegasus workflow systems [] to control and coordinate the data management and computational tasks. […]

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Pegasus institution(s)
University of Southern California, Information Sciences Institute, Marina del Rey, CA, USA; University of Southern California, Los Angeles, CA, USA; University of Wisconsin at Madison, Madison, WI, USA
Pegasus funding source(s)
Supported by The National Science Foundation under the ACI SDCI program grant #0722019 and ACI SI2-SSI program grant #1148515.

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