Submission Number: 36
Submission ID: 62
Submission UUID: fc9dca69-989e-4d05-8e87-dea6178abb8a
Submission URI: /form/project

Created: Thu, 05/21/2020 - 16:01
Completed: Thu, 05/21/2020 - 16:01
Changed: Thu, 09/23/2021 - 12:25

Remote IP address: 173.48.192.21
Submitted by: Northeast Cyberteam
Language: English

Is draft: No
Webform: Project
Project Title Grey matter density, heredity, and psychotic disorders with alcohol misuse: Moving toward new diagnostic conceptualization through biotypes.
Program Northeast
Project Leader David Gansler
Email mpietrzykowski@su.suffolk.edu
Mobile Phone 8603833011
Work Phone
Mentor(s) Malvina Pietrzykowski
Student-facilitator(s) Ben Burnett
Mentee(s)
Project Description These data will be used to further understand the biomarker of grey matter density (GMD) in relation to schizophrenia, schizoaffective disorder, and bipolar disorder with psychosis and their heredity. This research will enhance the conceptual understanding of the biotypes of these disorders introduced through the results of the Bipolar and Schizophrenia Network for Intermediate Phenotypes (BSNIP) project by conducting analyses of the effects of alcohol misuse.
Project Deliverables For successful completion of the project, researchers will need a job submission script for the image processing pipeline which submits each subject separately. It would be helpful for software to be installed as modules, as opposed to locally in user folders, and for deletion of intermediate files to be automated. Additionally, ideally the statistical analysis in QDEC will be done outside of the GUI.
Project Deliverables
Student Research Computing Facilitator Profile Graduate student with some experience in bash and a desire to learn about structural neuroimaging analysis software (i.e., FreeSurfer, FSL). Researchers are located in downtown Boston and able to meet over Zoom weekly if student is not in Boston.
Mentee Research Computing Profile
Student Facilitator Programming Skill Level
Mentee Programming Skill Level
Project Institution Suffolk University
Project Address
Anchor Institution NE-MGHPCC
Preferred Start Date 02/13/2020
Start as soon as possible. No
Project Urgency Already behind3Start date is flexible
Expected Project Duration (in months)
Launch Presentation
Launch Presentation Date
Wrap Presentation
Wrap Presentation Date
Project Milestones
  • Milestone Title: Startup
    Milestone Description: RCF will become familiar with (1) c3ddb cluster and job scheduler and (2) the dataset and methods being used for the project.
  • Milestone Title: Software install and first pass parallelization
    Milestone Description: RCF will (1) install necessary software onto c3ddb and (2) scale up initial processing pipeline for parallel processing of individual subjects (including QA). RCF will (3) work with graduate student to determine which intermediate files can be deleted and troubleshoot script to remove files after processing is completed.
  • Milestone Title: Transition to headless script and processing of data set
    Milestone Description: RCF will (1) work with graduate student to transition statistical analysis to headless script and (2) scale up for parallel processing.
  • Milestone Title: Submission for publication
    Milestone Description: RCF will assist with (1) abstract submission for INS at the end of the summer (for main scientific findings as co-author), and (2) for abstract and poster detailing Cyberteam relevant process for submission to PEARC21. Student will complete abstract and poster preparation for PEARC21 before end of project, submission and presentation will occur after end date for project.
Github Contributions
Planned Portal Contributions (if any)
Planned Publications (if any) Project findings will be submitted for poster presentation, and a manuscript will be prepared for publication in a peer-reviewed journal.
What will the student learn? The student will learn about structural neuroimaging analysis software and how to optimize these pipelines on HPC resources. Additionally, the student will learn how to prepare and communicate scientific findings.
What will the mentee learn?
What will the Cyberteam program learn from this project? The Cyberteam program will learn about workflows for neuroimaging datasets, and this information can be provided to future researchers.
HPC resources needed to complete this project? 864 subjects x 6 CPU hours = 5184 CPU Hours
Raw Data + Intermediate Files + End Product = ~0.75 GB x 864 subjects = 648 GB of storage which can be cut down immediately after processing is completed to ~350 GB
Each subject would need ideally 8 GB of RAM and go into the scheduler separately
2 software programs take up 15 GB of space each
Notes
What is the impact on the development of the principal discipline(s) of the project?
What is the impact on other disciplines?
Is there an impact physical resources that form infrastructure?
Is there an impact on the development of human resources for research computing?
Is there an impact on institutional resources that form infrastructure?
Is there an impact on information resources that form infrastructure?
Is there an impact on technology transfer?
Is there an impact on society beyond science and technology?
Lessons Learned
Overall results