[ABE-L] Seminario Depto Estatistica-UNICAMP

[Ronaldo Dias]

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Nesta   sexta   feira  26/10/2018, as  14:00   Sala 221,
vamos  ter  seminário  no  nosso  departamento. Contamos  com   sua
presença!.

Nesta  oportunidade,   vamos  contar  com  a  conferencia da

Profa.  Mariza de Andrade,
Department of Health Sciences Research,
Division of Biomedical Statistics and Informatics,
Mayo Clinic, Rochester, MN


Tittle: Back to the Future:  Statistical Methods and Genomics

In this talk I will provide an evolution of the statistical methods
developed in the beginning and throughout the 20th century as used today
in the genomics era.  The availability of fast computers makes the
statistical methods easy to program and to analyze the data using non-open
source software such as SAS, STATA, and SPSS among others, and open source
software such as R available in CRAN.
I will start with R.A. Fisher’s 1918 seminal paper about the small
contribution of a gene in traits or phenotypes to the current polygenic
risk model, C.R. Henderson’s 1975 paper in best linear unbiased estimation
(BLUE) and best linear unbiased predictor (BLUP) and their use in animal
and human models, N.E. Breslow and D.G. Clayton’s 1993 paper in
generalized linear mixed models (GLMM) and its current application to
identify variants or gene in sequencing data, D.R. Cox’s 1972 seminal
paper about regression models and life tables  and its current application
in time to event model to identify association between genetic variants
and risk factors-related outcomes or diseases during treatment as well as
its application using family data, T. Haavelmo’s 1943 paper in system of
simultaneous  equations turned to structural equation models (SEM) applied
in social sciences and recently for multiple ‘omics outcomes. Finally I
will present machine learning techniques and their application in
statistics and genomics.  I will also provide applications using simulated
and real data sets for the majority of topics described above.

-- 
Ronaldo Dias
Professor
Dept. of Statistics-IMECC, UNICAMP
www.ime.unicamp.br/~dias
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