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The Ficklin Research Program

About

The Ficklin research program in the Dept. of Horticulture at Washington State University is a computational dry lab dedicated to the creation of software tools, computational approaches and systems-level models that address basic and applied hypothesis at the molecular-level of agricultural systems.

Areas of Focus

  • Biosignature discovery:  identification of dynamic molecular markers (i.e., gene expression, metabolite abundance) for environmentally controlled traits in plants using machine learning.
  • Machine-learning and image processing for automated physiological trait rating in horticultural crops.
  • Systems genetics: using multiomic networks to link the molecular underpinnings to traits of interest.
  • Community biological database development using the Tripal software.
  • Whole genome assembly and annotation.

Stephen P. Ficklin, Ph.D.

Associate Professor, Dept of Horticulture, Washington State University

Contact Information

Office: Plant Science Building #403A
Phone: (509) 335-4295
Email: stephen.ficklin@wsu.edu

Department of Horticulture
Washington State University
PO Box 646414
Pullman, WA 99164-6414

 

Educational Background

  • Ph.D. Plant and Environmental Sciences, Clemson University (2013)
  • M.S. Computer Science, Clemson University (2003)
  • B.S. Computer Science, Brigham Young University (2000)

Projects

Summary Measures of Health for Dairy Cattle

Project Dates: to

NIFA

Funded by the USDA NIFA IDEAS program, this projects seeks to create a time-based summary measure of dairy cow health using transcriptomics, the microbiome and trait data that can be used to assess the comparative importance of diseases and injuries affecting animal wellbeing and economic losses across dairy populations.

NRSP10: National Database Resources for Crop Genomics, Genetics and Breeding Research

Project Dates: to

NIFANRSP10  (https://www.nrsp10.org/) is one of seven National Research Support Project (NRSP) funded  by the State Agricultural Experiment Stations (SAES) from the Hatch Multistate Research Fund (MRF) provided by the National Institute for Food and Agriculture (NIFA).  The mission is to establish a robust, dynamic, and widely available genomics, genetics and breeding online database platform as a resource for crops of national significance that are currently underserved (Citrus, Cool Season Food Legumes, Cotton, Rosaceae, and Vaccinium), that is flexible enough to be readily implemented for other crops and organisms valuable to U.S. agriculture.  The role of our program is to provide core development support and outreach for Tripal (http://tripal.info)

Analysis of the Antagonistic and Mutualistic Interactions Within Potato, Protist & Virus

Project Dates: to

NIFA

Awarded jointly by the NSF and USDA , this project seeks to explore the mutualistic relationship between the soil borne Spongospora subterranea f. sp. subterranea (a protist parasite), and the potato mop-top virus (PMTV) as they antagonistically interact with potato plants.  A systems-level time-series analysis will be performed to identify candidate gene sets that underlie disease susceptibility, resistance and mutualism.

Assessment of smoke taint risk in vineyards exposed to smoke from wildfires

Project Dates: to

WSDA

Funded by the Washington State Department of Agriculture Specialty Block Program, this project addresses the grape and wine industry's need for methods that assess the risk to grape and wine quality associated with vineyard exposure to smoke from wildfires. 

Apple genomes for postharvest fruit quality biomarkers

Project Dates: to

Washington Tree Fruit Research Commission

This project funded by the Washington Tree Fruit Research Commission seeks to develop tools for identification of postharvest biomarkers in apple fruit that assess response to storage conditions and predict risk for disorders or loss of quality.

"Big Data" Tree Crop Cyberinfrastructure

Project Dates: to

National Science Foundation

Standards and Cyberinfrastructure that Enable "Big-Data" Driven Discovery for Tree Crop Research is a project funded by the US National Science Foundation (award #1444573) to develop standards and infrastucture for the integration of high quality, curated, phenotypic and genotypic data with geo-location and environmental data.  This project will both leverage and coordinate funded efforts to enhance or update tree crop databases (Genome Database for Rosaceae, Citrus Genome Database, TreeGene and Hardwood Genomics Web) to Tripal that will support cross-site communication, adoption of existing standards, and "big data" integration and analysis.

Precision Dairying: Transcriptomics/Phenomics Pilot Project

Project Dates: to

WSU

Funded by a Livestock Health and Food Security internal grant by the College of Veterinary Medicine (CVM)  and the College of Agricultural, Human and Natural Resources (CAHNRS) at WSU, the Precision Dairying project seeks to apply high-throughput data collection technologies in transcriptomics and phenomics to identify biomarkers predictive of animal health.

Scientific Data at Scale (SciDAS)

Project Dates: to

National Science Foundation

SciDAS is a multi-institutional project funded by the National Science Foundation (award #1659300). The goal for SciDAS is to provide advanced cyberinfrastructure to support the creation of a National-level distributed compute infrastructure for the efficient injection of data and workflows compute environments. The Ficklin Lab is responsible for working with the project team to develop a Systems-Biology use case for large-scale development of gene co-expression networks across the tree of life.  The project also contains a Tripal component to integrate Tripal sites with the SciDAS infrastructure.  See the official SciDAS home page for more information.

Lentil Transcriptomics/Phenomics Pilot Project

Project Dates: to

WSU

Funded by the College of Agricultural, Human and Natural Resources (CAHNRS) at WSU, the Lentil Emerging Issues Pilot project explores integration of transcriptomic, phenomics and phenotype data using a systems genetic approach to explore new protocols for identification of disease resistance biomarkers in Lentil.

Tripal Gateway

Project Dates: to

National Science Foundation

The Tripal Gateway Project is a US National Science Foundation (NSF) Funded (award #1443040) project designed to create infrastructure to support two important needs within the Tripal community: data exchange and big data analysis.   Modern sequencing technologies have expanded the need for workflow-based analytics to meet the demands of community expectations.  The ability to move data between the community database and the high performance computing cluster is critical for meeting performance expectations. The Tripal Gateway Project attempts to meet these needs through the addition of RESTful web services to Tripal, second, integration of Tripal with Galaxy such that Tripal sites can provide analytical workflows to their users, and third development and exploration of methods to improve data transfer between Tripal sites and computing centers where Galaxy jobs are executed.  

People

The Ficklin Lab comprises full time technical and research staff, postdocs, graduate students and undergraduate students. Current members of the Ficklin Lab are listed below in alphabetical order.

Active

P. Layton Ashmore

Postdoctoral Researcher
P. Layton Ashmore
Focus Areas

Application of data science to identify biomarkers from large untargeted masspec datasets for wildfire smoke-related compounds in wine grapes.  Co-advised by Tom Collins.

Sean Buehler

Scientific Application Web Developer
Sean Buehler
Focus Areas

Tripal v3 and v4 Core Development and Tripal Help Desk support.

Zach Hall

Undergraduate Researcher
Zach Hall
Focus Areas

Data analytics, biomarker development

Nhan Nguyen

Machine Learning Software Development
Nahn Nguyen
Focus Areas

Lead Developer of Granny, a machine learning tools for pome fruit trait ratings.

Risharde Ramnath

Scientific Application Web Developer
Richarde Ramnath
Focus Areas

Tripal v3 and v4 Core Development and Tripal Help Desk support.

Fabiola Ramirez Torres

Horticulture PhD Student
Fabiola Ramirez Torres
Focus Areas

Gene editing techniques

Joel Alejandro Velasco

Horticulture PhD Student
Joel Alejandro Velasco
Focus Areas

Identification of genes underlying root rot (Aphanomyces) resistance in lentils

Huiting Zhang

Postdoctoral Researcher
Huiting Zhang
Focus Areas

Use of functional genomics and bioinformatics to explore the genetic control of post-harvest fruit quality  of pome fruits.  Works in both the Ficklin and Honnas research programs.

Alumni

Tyler Biggs

Postdoctoral Researcher
Tyler Biggs
Focus Areas

Python development for PynomeGSForge, and workflow development of massive gene co-expression network construction with SciDAS project. Data analysis, Machine Learning, High Performance Computing,   Ph.D. in Organic Chemistry

Josh Burns

Research Associate
Josh Burns
Focus Areas

Software developer for ACE KINC Using C++, OpenCL, QT and OpenMPI; GPU optimzation.  Development of the AnnoTater workflow for execution on Kuberntes clusters.

Mitchell Greer

Undergraduate in EECS
Mitchell Greer
Focus Areas

C++, CUDA, OpenCL Developer.  Assisted in Development of KINC.

John Hadish

MPS Ph.D. Graduate 8/2023
John Hadish
Focus Areas

Exploration of improved computational methods towards development of biosignatures for post-harvest fruit quality in apples. Lead developer of GEMmaker.

Matt McGowan

MPS Ph.D. Graduate 5/2022
Matt McGowan
Focus Areas

Noise reduction strategies, Network & GWAS integration, condition-specific subnetworks.  Works in both the Ficklin and Zhang research programs.

Sai Oruganti Sai Prakash

Former Hort Ph.D. Student
Sai Oruganti Sai Prakash
Focus Areas

Top-down metabolic networks construction for identification of condition-specific interactions and integration with gene expression data.

Yue Shang

Hort MS Graduate 5/2023
Yue Shang
Focus Areas

Researches chemical composition changes in smoke tainted grape and wine using GC-MS and Q-TOF. Works in the Collins lab, co-advised in the Ficklin lab.

Brian Soto

Undergraduate in EECS
Brian Soto
Focus Areas

Software developer (PHP, JavaScript, Python) working on the Tripal Galaxy Module and blend4php

Shawna Spoor

Research Associate
Shawna Spoor
Focus Areas

Works on the Tripal v3 and the Tripal Gateway Project, including development and outreach.  Highly experienced Drupal developer.

Connor Wytko

Undergraduate in EECS
Connor Wytko
Focus Areas

Software developer (PHP, JavaScript, Python) working on the Tripal Galaxy Module and blend4php

Publications

The Ficklin Lab in the Department of Horticulture at WSU began in July of 2015. The following is a list of peer-reviewed publications with lab members as primary or as co-author since 2015.


2022

2021

2020

2019

2018

2017

2016

2015

Software

The Ficklin lab actively develops software that implements new approaches for Systems Genetics and the Tripal database platform. A list of these software packages is provided below.

ACE

The Accelerated Computational Engine (ACE) is a C++ library that provides a generic interface for construction of analytical tools.  It provides a common interface for GPU utilization, visualization using the Qt package, and multi-node execution using OpenMPI.   ACE provides an open file format for all output files that supports meta-data and provenance.  ACE was created as the base for KINC, but can be used for any scientific application.  

blend4php

blend4php

blend4php is a PHP library that interacts directly with the Galaxy Project API.  This tools was developed for use by the Tripal Galaxy Module, but was designed to be independent to allow anyone with a PHP-based site to directly interact with workflows housed in Galaxy.  The blend4php package will allow a site to add, modify and launch workflows, view and download histories, create datasets and more.

FUNC-E

FUNC-E provides a DAVID-style command-line tool for functional enrichment of gene sets.  It performs Fisher's test, multiple-testing correction, and KAPPA statistics for term clustering.   FUNC-E allows a user to provide their own genome background and annotation sets. 

GEMmaker

GEMmaker Logo

GEMmaker is a Nextflow workflow for large-scale gene expression sample processing, expression-level quantification and Gene Expression Matrix (GEM) construction. Results from GEMmaker are useful for differential gene expression (DGE) and gene co-expression network (GCN) analyses. The GEMmaker workflow currently supports Illumina RNA-seq datasets.

GSForge

GSForge is a Python software package that assists researchers through use of data management, visualization and machine learning approaches in the selection of gene sets with potential association to an experimental condition or phenotypic trait, which offers new potential hypotheses for gene-trait causality.

KINC

KINC

The Knowledge Independent Network Construction (KINC) package generates gene co-expression networks using Pearson and Spearman and Mutual Information,  employs Random Matrix Theory (RMT) for automated network thresholding and optionally employs Gaussian Mixture Models (GMMs) to identify potential condition-specific gene expression.  KINC v3.0 is built off of the Accelerated Computing Engine (ACE)--another Ficklin Lab software product.

Pynome

SciDAS

Pynome is a product of the NSF-funded SciDAS project  It is used to automate retrieval and preparation of whole genome sequences for a variety of Eukaryotic species.  Pynome integrates with iRODs to prepare large-scale genomic analyticsl workflows.

Tripal

Tripal

Tripal is a toolkit for construction of online biological (genetics, genomics, breeding, etc), community database, and is a member of the GMOD family of tools. Tripal v3 provides by default integration with the GMOD Chado database.   Tripal is used by species and clade genome databases all over the world and boasts an active distributed community of open-source developers.

Tripal Galaxy Module

Tripal

The Tripal Galaxy Module is an extension module for Tripal that integrates a Tripal-based site with the Galaxy Workflow tool.  It allows a site to provide workflows to end-users and for site developers to use Galaxy workflows to power computation of complex analytical tools.

Tripal Network Module

Tripal

The Tripal Network Module serves as an extension to Tripal and provides data management and visualization for biological networks stored in Tripal. 

Teaching

The following courses are offered to graduate-level students by the Ficklin Lab

AFS 505: Topics in Computing and Analytical Methods for Scientists

Formerly a Horticulture 503 (Special Topics) course, this course offers: 

  • Applied computational methods for researchers processing, managing, and analyzing data in scientific and engineering fields.
  • Variable-credit (1-6) course with 5-weeks per module and 1 credit per module.
  • Select from non-sequential modules to meet program needs.
  • General prerequisite is graduate standing in an agricultural, life environmental or economic science, or engineering. Other recommended preparation specific to individual modules.

Modules offered in the Fall

  • Data Structures in R
  • Data Visualization in R
  • Data Wrangling in R
Instructor: David Brown, Ph.D.

Modules offered in the Spring

  • Programming in Python
  • Data Analysis with Python
  • Computing for Big Data
Instructor: Stephen Ficklin, Ph.D.

 

Semesters Taught:
  • AFS 505 Units 1-3 Spring 2020
  • Hort 503 (Advanced Topics), Section 1 Spring 2019
  • Hort 503 (Advanced Topics), Section 1 Spring 2018

Data Analysis in Systems Biology

This course offers an introduction to approaches for modeling and analysis for systems biology.  Topics include

  • Review of gene, protein, metabolic, and signaling systems
  • Methods for modeling biological systems
  • UNIX Basics
  • High Performance Computing (HPC) introduction
  • Graph theory for network modeling
  • Network visualization

Throughout the course students work towards the generation of gene co-expression networks from RNA-seq data they select for organisms and biological functions of their own interest.  These networks are constructed using HPC and existing bioinformatics tools.

 

Semesters Taught:
  • Hort 503 (Advanced Topics), Section 2 Fall 2019
  • Hort 503 (Advanced Topics), Section 2 Fall 2017
  • Hort 503 (Advanced Topics), Section 2 Fall 2016

Join the Lab

Graduate Studies

Graduate degrees with an emphasis on Systems Genetics and Computational Biology are available with the Ficklin lab through the Department of Horticulture and the Molecular Plant Sciences (MPS) program.  Both programs offer world-class graduate-level education.  Dr. Ficklin is currently looking for students interested in graduate research both at the M.S. (Horticulture) and Ph.D. levels (Horticulture and MPS).  Please contact Dr. Ficklin  directly to express interest.

Undergraduate Research

Undergraduate research opportunities are available for motivated students with background in computer programming.  If interested, please contact Dr. Ficklin directly.

Research Staff / Postdoctoral Researchers

The Ficklin lab offers full time employment as needed by funded projects for data scientists and software developers.  At times, positions are available for Research Associates (with a B.S. or M.S. degree and relevant experience) and Postoctoral Researchers. When available, these positions are posted online at WSU's career website. If you are looking to apply for an existing opening please use that site to apply.  If you would like to inquire about potential employment, please contact Dr. Ficklin directly.