Talks focused on translating recent advances in biostatistics into practice. Biostatistics Continuing Education
At a glance
Opportunity for
  • Continuing education on recent advances in biostatistics
  • All members of the Harvard Catalyst community, but primarily geared toward biostatisticians
Session Dates
  • Varies; see below for details

The Harvard Catalyst Biostatistics Program presents seminars on current applied topics in biostatistics. These include monthly journal club and work in progress sessions, seminar series, symposia, and short courses.

Journal Club/Work in Progress

Seminar Series

Applications of Independent Component Analysis for MRI Data: Denoising, Brain Functional Connectivity, and Multi-Modal Data Fusion
November 13, 2018

Lisa Nickerson, PhD; Assistant Professor of Psychiatry, HMS; Director of Applied Neuroimaging Statistics Laboratory, McLean Hospital

FXB, Room G13
Harvard T.H. Chan School of Public Health

Abstract: Independent component analysis (ICA) is a purely data-driven multivariate statistical method that has found numerous applications in MRI data analysis. The ability of ICA to separate meaningful signals of interest from confounding noise signals in a data-driven fashion make it a powerful dual purpose technique for both addressing noise problems in MRI data and for investigating brain function. Dr. Nickerson will present several such applications of ICA techniques, including the application of single-subject ICA for denoising fMRI data and group ICA for investigating functional connectivity of brain networks, highlighting the work on dual regression and findings on brain network connectivity in individuals with alcohol use disorder. Also, a new analytic method will be discussed that uses linked ICA to denoise scanner effects from multi-study MRI data, and the findings using linked ICA for multi-modal data fusion to investigate brain structure and function in heavy chronic cannabis users.

Registration not required.


Short Courses

Methods for Human Microbiome Research

November 20, 10:00am-6:00pm
FXB G12, Harvard T.H. Chan School of Public Health

This course will provide an introduction to study designs and methods for human microbiome population studies, including typical sampling and data generation considerations and approaches for microbial community data analysis (metagenomics, metatranscriptomics, and other culture-independent molecular data). It will incorporate both lecture and hands-on lab sessions. Course participants will learn about typical approaches to human microbiome studies - in the gut and across the body - and how to process data from raw meta'omic sequencing files through appropriate bioinformatic methods and approaches for subsequent integrative statistical analyses. Participants are encouraged to bring their own data, otherwise in-class examples will focus on publicly available data from the Integrative Human Microbiome Project (HMP2).

Curtis Huttenhower, PhD
Associate Professor of Computational Biology and Bioinformatics
Department of Biostatistics
Department of Immunology and Infectious Diseases
Harvard T.H. Chan School of Public Health

Please register.