Topic: Data Science

The NIAID-funded International epidemiology Databases to Evaluate AIDS (IeDEA) consortium is a global HIV observational research network with seven geographic regions and over 350 participating HIV care and treatment clinics. The data scientists and data managers of IeDEA established the Harmonist Project to develop informatics-driven methodologies, data standards, and tools to catalyze IeDEA data sharing and scientific collaboration. In this presentation, we will share the process and outcomes, demos of generalizable tools built on REDCap and R Shiny, and potential uses for other large observational research networks.

Speakers:

• Stephany Duda, Ph.D.

Associate Professor of Biomedical Informatics

Vanderbilt University Medical Center

• Judy Lewis, Ph.D.

Lead Developer, Harmonist Data Toolkit

Adjunct Assistant Professor of Biomedical Engineering

Vanderbilt University Medical Center

Dr. Pjotr Prins and Arun Isaac will present their Concise Common Workflow Language (CCWL). CCWL makes code reusable and adaptable across a variety of software and hardware environment while following FAIR+ (Findable, Accessible, Interoperable, Reusable, and Computable) principles. They will also discuss their prototype COVID-19 cloud setup, with a hands-on demonstration of the universal software deployment system Guix, part of the open-source operating system GNU.

CWL is of particular interest to cancer researchers because it provides a standardized machine-readable semantics model for running workflows on virtual environments. Attendees will learn how CCWL, as a CWL compiler, works with a package manager like GNU Guix to improve reproducibility and validation of bioinformatics workflows.

This webinar is part of the monthly Containers and Workflow Interest Group (CWIG) webinar series. CWIG brings together data scientists, bioinformaticians, computer scientists, and researchers to learn more about cloud computing and container technologies, workflows, and pipelines that could drive cancer data science.

The webinar series features a variety of presenters from across NIH, industry, and academia. Though cancer research is the focus of the series, unrelated data science and cloud computing topics are still welcome. In the last year, the CWIG webinar speakers have discussed:

• NIH cloud programs like the NCI Cloud Resources and NIH STRIDES.
• commercial cloud platforms for biomedical data storage and computing.
• pipelines and tools for deep learning and various omics analysis.

Speakers:

Pjotr Prins, Ph.D.

Dr. Prins is a bioinformatician at-large and assistant (coding) professor at the Department of Genetics, Genomics, and Informatics at the University of Tennessee Health Science Center. He is also the director of Genenetwork.org and writes critical software for genetics and pangenomics

Arun Isaac

Mr. Isaac is a doctoral student at the Department of Computational and Data Sciences, Indian Institute of Science. He regularly contributes to GNU Guix and is the author of guile-email, an email parser for Guile.

Register for the 2021 Clinical Proteomics Tumor Analysis Consortium (CPTAC) Virtual Scientific Symposium to hear CPTAC investigators share their latest discoveries in the field of cancer proteogenomics, cancer research, and data analysis tools.

In addition to scientific talks on tumor biology and translational studies, there will be demonstrations of these CPTAC-developed data analysis tools:

• FragPipe Computational Pipeline (for comprehensive analysis of mass spectrometry-based proteomics data)
• ProTrack-Kinase Activity Portal (for querying/visualizing/downloading kinase activity scores of multiple cancer types)
• BayesDebulk (analysis method for inferring cell-type composition in bulk tissue using proteogenomics data)

The CPTAC program is a national effort coordinated through NCI’s Office of Cancer Clinical Proteomics Research to accelerate the understanding of cancer biology through the marriage of large-scale proteome and genome analysis, or proteogenomics. Proteogenomics allows CPTAC researchers to paint a more detailed picture of tumor carcinogenesis and progression, micro-environments, and immune landscapes. This information can then be leveraged therapeutically to improve patient care.

Presenter:

Trevor Bedford, Ph.D.
Associate Professor
Vaccine and Infectious Disease Division
Human Biology Division
Herbold Computational Biology Program
Fred Hutchinson Cancer Research Center

Genomic epidemiology has enabled critical insights during the COVID-19 pandemic.  At the forefront of these insights has been SARS-CoV-2’s remarkable potential for adaptive evolution.  Dr. Bedford will discuss the evolutionary dynamics of SARS-CoV-2 with a focus on the emergence of variant of concern and variant of interest viruses.  He will characterize mutational patterns in these variant viruses and chart their spread across geographies.  He also will provide a larger perspective on genomic surveillance, projected future viral circulation patterns, and strategies for ongoing pandemic management.

Dr. Bedford is an associate professor in the vaccine and infectious disease division, the human biology division, and the Herbold Computational Biology Program at Fred Hutch.  The Bedford lab studies the rapid spread and evolution of viruses, including those that cause COVID-19, influenza, Ebola, and Zika.  Bedford’s visual representations of viral family trees are used to show how the fate of dangerous outbreaks is often determined by the genetics of the infectious agent, human behavior, and geography.

Link now to https://videocast.nih.gov/ical.ics?live=43795 to add this to your Outlook calendar.  Continuing Medical Education (CME) credits will be available; the code will be announced at the start of the lecture.

Register Now

Faculty: Joao Xavier, PhD – Memorial Sloan Kettering Cancer Center; NCI CSBC

Moderator: Matthew J. Reilley, MD – University of Virginia

Target Audience
This series will serve as an excellent resource for all stakeholders interested in expanding their knowledge in computation immune-oncology. Specifically, early career scientists who want to further their training in computational immuno-oncology, as well as more senior career individuals who want to implement these techniques for the first time will greatly benefit from the series.

Learning Objectives
A key goal of this training program is to ensure participants remain on the cutting edge of computational immuno-oncology, to increase the participants’ awareness of the NCI-supported Cancer Moonshot Immunotherapy Networks, to enhance scientific engagements between the Cancer Moonshot(SM) Immunotherapy Networks and the broader cancer immunotherapy community, and to fulfill the Blue Ribbon Panel goal of acceleration of progress in cancer research.

Series Organizers
Kellie N. Smith, PhD – Johns Hopkins School of Medicine
Big Data and Data Sharing Committee, Chair
Song Liu, PhD – Roswell Park Comprehensive Cancer Center, NCI Cancer Moonshot IOTN & DRSN
Big Data and Data Sharing Committee, Co-Chair
Alan Hutson, PhD – Roswell Park Comprehensive Cancer Center, NCI Cancer Moonshot IOTN & DRSN
Big Data and Data Sharing Committee, Immediate Past Chair
Carsten Krieg, PhD – Medical University of South Carolina
Big Data and Data Sharing Committee, Member

Wrapping up its final webinar of 2021, the NCI Cancer Research Data Commons (CRDC) Cancer Genomics Cloud (CGC) welcomes Cold Spring Harbor Laboratory fellow Dr. Pascal Belleau. He will share his findings from recent work on the CGC, typing the Human Leukocyte Antigen (HLA) class II complex in 11,000 patient samples from The Cancer Genome Atlas (TCGA) data set.

Through his study, Dr. Belleau investigated the presence and patterns of the HLA class II complex across 33 tumor types. The HLA class II complex is a molecular component linked to the body’s immune response. Understanding how this molecular complex differs across cancer types can give us insight into how it may mediate the immune system’s response to cancer.

As one of the three Cloud Resources within the NCI CRDC, the Seven Bridges’ CGC provides researchers access to a wide variety of data sets, a catalog of tools to analyze and visualize the data directly from the browser, and scalable computational resources to perform large scale-analysis in the cloud.

Speaker:

Pascal Belleau, Ph.D.

Dr. Belleau is a computational biology postdoctoral fellow at the Quantitative Biology Department of Cold Spring Harbor Laboratory.

Register Now

Faculty: Joao Xavier, PhD – Memorial Sloan Kettering Cancer Center; NCI CSBC

Moderator: Matthew J. Reilley, MD – University of Virginia

Target Audience
This series will serve as an excellent resource for all stakeholders interested in expanding their knowledge in computation immune-oncology. Specifically, early career scientists who want to further their training in computational immuno-oncology, as well as more senior career individuals who want to implement these techniques for the first time will greatly benefit from the series.

Learning Objectives
A key goal of this training program is to ensure participants remain on the cutting edge of computational immuno-oncology, to increase the participants’ awareness of the NCI-supported Cancer Moonshot Immunotherapy Networks, to enhance scientific engagements between the Cancer Moonshot(SM) Immunotherapy Networks and the broader cancer immunotherapy community, and to fulfill the Blue Ribbon Panel goal of acceleration of progress in cancer research.

Series Organizers
Kellie N. Smith, PhD – Johns Hopkins School of Medicine
Big Data and Data Sharing Committee, Chair
Song Liu, PhD – Roswell Park Comprehensive Cancer Center, NCI Cancer Moonshot IOTN & DRSN
Big Data and Data Sharing Committee, Co-Chair
Alan Hutson, PhD – Roswell Park Comprehensive Cancer Center, NCI Cancer Moonshot IOTN & DRSN
Big Data and Data Sharing Committee, Immediate Past Chair
Carsten Krieg, PhD – Medical University of South Carolina
Big Data and Data Sharing Committee, Member

This course provides detailed information on managing and sharing data from the first data planning stage, through the data life cycle, to data archiving, and finally to selecting an appropriate repository for data preservation. By the end of this course, participants will have an understanding of data management best practices, data management tools, and resources that enable data sharing.

This is an introductory two-part course for those who want to learn about research data management and sharing, or for those who are interested in a refresher. Part 1 of this training will cover understanding research data, how to manage research data, and how to work with data. Audience: Researchers, fellows, post-docs, and trainees. You must register separately for Part 2 of this class.

This course provides detailed information on managing and sharing data from the first data planning stage, through the data life cycle, to data archiving, and finally to selecting an appropriate repository for data preservation. By the end of this course, participants will have an understanding of data management best practices, data management tools, and resources that enable data sharing.

This is an introductory two-part course for those who want to learn about research data management and sharing, or for those who are interested in a refresher. During Part 2 of this training, participants will learn about sharing and archiving data. Audience: Researchers, fellows, post-docs, and trainees. You must register separately for Part 1 of this class.

Register Now

Faculty: Yi Xing, PhD – Children’s Hospital of Pennsylvania/University of Pennsylvania; NCI Cancer Moonshot IOTN

Moderator: Kellie N. Smith, PhD – Johns Hopkins School of Medicine

Target Audience
This series will serve as an excellent resource for all stakeholders interested in expanding their knowledge in computation immune-oncology. Specifically, early career scientists who want to further their training in computational immuno-oncology, as well as more senior career individuals who want to implement these techniques for the first time will greatly benefit from the series.

Learning Objectives
A key goal of this training program is to ensure participants remain on the cutting edge of computational immuno-oncology, to increase the participants’ awareness of the NCI-supported Cancer Moonshot Immunotherapy Networks, to enhance scientific engagements between the Cancer Moonshot(SM) Immunotherapy Networks and the broader cancer immunotherapy community, and to fulfill the Blue Ribbon Panel goal of acceleration of progress in cancer research.

Series Organizers
Kellie N. Smith, PhD – Johns Hopkins School of Medicine
Big Data and Data Sharing Committee, Chair
Song Liu, PhD – Roswell Park Comprehensive Cancer Center, NCI Cancer Moonshot IOTN & DRSN
Big Data and Data Sharing Committee, Co-Chair
Alan Hutson, PhD – Roswell Park Comprehensive Cancer Center, NCI Cancer Moonshot IOTN & DRSN
Big Data and Data Sharing Committee, Immediate Past Chair
Carsten Krieg, PhD – Medical University of South Carolina
Big Data and Data Sharing Committee, Member