Events Calendar

23 Apr
Cathedral
Event Type

Lectures, Symposia, Etc.

Topic

Research

Target Audience

Staff, Alumni, Faculty, Graduate Students, Postdocs

Tags

Public Health Grand Rounds

University Unit
Department of Human Genetics
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18th Annual CC Li Memorial Lecture - Kathryn Roeder, PhD

Designated as a Public Health Grand Rounds event, our 18th Annual CC Li Memorial Lecture will feature Dr. Kathryn Roeder. Dr. Roeder is the UPMC Professor of Statistics and Life Sciences in the Departments of Statistics and Data Science and Computational Biology.  She has developed statistical and machine learning methods in a wide spectrum of areas, including high dimensional data problems in genetics.  Her work focuses on statistical methods to reveal the genetic basis of complex disease.  She is one of the leaders of the Autism Sequencing Consortium, an international organization dedicated to discovering the genetic etiology of autism.  In 1997, she received the COPSS Presidents’ Award, as well as the COPSS Snedecor Award for outstanding work in statistical applications.  In 2019, she was elected to the National Academy of Sciences.

Statistics and Genetics Offer a Window into Autism

The largest exome sequencing study (n = 14,578 parent-child trios) to date of autism spectrum disorder (ASD) implicates 185 genes in risk (FDR < 0.05). We describe how de novo mutations and rare inherited variants were used to assess association. Applying the same approach to the cohort  entitled Deciphering Developmental Disorders (n = 31,058 trios), we to obtain 374 DD risk genes. These risk gene sets serve as a springboard for explorations into differences in the etiological of ASD and other developmental disorders.  Quantification of gene expression using single cell RNA-sequencing of brain tissues can be a critical step in such investigations.   We describe statistical challenges encountered analyzing developing brain cells, including new methods for transfer learning and hierarchical reconstruction via reconciliation of multi-resolution cluster trees. 

 

Dial-In Information

Register here

Friday, April 23 at 12:10 p.m. to 1:10 p.m.

Virtual Event

18th Annual CC Li Memorial Lecture - Kathryn Roeder, PhD

Designated as a Public Health Grand Rounds event, our 18th Annual CC Li Memorial Lecture will feature Dr. Kathryn Roeder. Dr. Roeder is the UPMC Professor of Statistics and Life Sciences in the Departments of Statistics and Data Science and Computational Biology.  She has developed statistical and machine learning methods in a wide spectrum of areas, including high dimensional data problems in genetics.  Her work focuses on statistical methods to reveal the genetic basis of complex disease.  She is one of the leaders of the Autism Sequencing Consortium, an international organization dedicated to discovering the genetic etiology of autism.  In 1997, she received the COPSS Presidents’ Award, as well as the COPSS Snedecor Award for outstanding work in statistical applications.  In 2019, she was elected to the National Academy of Sciences.

Statistics and Genetics Offer a Window into Autism

The largest exome sequencing study (n = 14,578 parent-child trios) to date of autism spectrum disorder (ASD) implicates 185 genes in risk (FDR < 0.05). We describe how de novo mutations and rare inherited variants were used to assess association. Applying the same approach to the cohort  entitled Deciphering Developmental Disorders (n = 31,058 trios), we to obtain 374 DD risk genes. These risk gene sets serve as a springboard for explorations into differences in the etiological of ASD and other developmental disorders.  Quantification of gene expression using single cell RNA-sequencing of brain tissues can be a critical step in such investigations.   We describe statistical challenges encountered analyzing developing brain cells, including new methods for transfer learning and hierarchical reconstruction via reconciliation of multi-resolution cluster trees. 

 

Dial-In Information

Register here

Friday, April 23 at 12:10 p.m. to 1:10 p.m.

Virtual Event

Topic

Research