[Forum SIS] Biostatistics seminars @Sapienza

[Marco Alfo']

We are glad to announce the seminar:

 thursday, November 14, 12.00 am

 Room XIV, Palazzina ex Tumminelli, Sapienza Universita' di Roma

Multi-study factor analysis for biological data

Roberta De Vito (Department of Biostatistics, Brown University)

We introduce a novel class of factor analysis methodologies for the joint
analysis of multiple studies. The goal is to separately identify and
estimate 1) common factors shared across multiple studies, and 2)
study-specific factors.  We develop a fast Expectation
Conditional-Maximization algorithm for parameter estimates and we provide a
procedure for choosing the common and specific factors.



We present simulations evaluating the performance of the method and we
illustrate it by applying it to gene expression data in ovarian cancer and
to nutrient-based dietary patterns and the risk of head and neck cancer. In
both cases, we clarify the benefits of a joint analysis compared to the
standard factor analysis.



Moreover, we generalize the model in a Bayesian framework. We implement it
using sparse modeling of high-dimensional factor loadings matrices, both
common

and specific, using the infinite gamma shrinkage prior. We propose a
computationally efficient algorithm, based on a traditional Gibbs sampler,
to produce the Bayes estimates of the parameters and to select the number
of relevant common factors.

We assess the operating characteristics of our method by means of
simulation studies, and we present an application to the prediction of the
biological signal from four gene expression studies on ovarian cancer.
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