2019 Spring ASA Chapter Meeting
Dear Members of Kansas-Western Missouri Chapter of ASA,
Please join us for our spring Chapter meeting on Friday, April 5th, 2019 at Kansas State University. The meeting will be held in the Holiday Inn Manhattan at the Campus (1641 Anderson Ave, Manhattan, KS 66502).
Professor Susmita Datta from the Department of Biostatistics, University of Florida will be presenting the Keynote Address "Advances and Challenges in Single Cell RNA-Seq Analysis".
Please contact the Chapter secretary Dr. Pallavi Sawant (email@example.com) if you have any questions.
We look forward to seeing you in Manhattan!
The cost to attend the chapter meeting is $30.00 ($20.00 for students), which includes dinner.
After April 1st, 2019 prices subject to increase.
(Apr 2 - Apr 4, 2019)
|Non-Student||US$ 30.00||US$ 35.00|
|Student||US$ 20.00||US$ 25.00|
Registration for this event can be done online at: www.123signup.com/register?id=rgpzm
More information about this event: www.123signup.com/event?id=rgpzm
6:00 – 6:15 p.m. Social time
6:15 – 6:30 p.m. The induction ceremony for Mu Sigma Rho Honor Society
6:30 – 7:15 p.m. Dinner
7:15 – 7:30 p.m. Chapter business
7:30 – 8:30 p.m. Keynote Address
Chapter Meeting Keynote Address
Title: Advances and Challenges in Single Cell RNA-Seq Analysis
Abstract: Traditionally, transcriptomic studies have examined transcript abundance measurements averaged over bulk populations of thousands (or even millions) of cells. While these bulk RNA-sequencing (RNA-Seq) measurements have been valuable in countless studies, they often conceal cell-specific heterogeneity in expression signals that may be paramount to new biological findings. Fortunately, with single cell RNA-sequencing (scRNA-Seq), transcriptome data from individual cells are now accessible, providing opportunities to investigate functional states of cells, identify rare cell populations and uncover diverse gene expression patterns in cell populations that seem homogeneous. However, there are challenges in analyzing such scRNA-Seq data. Amongst many challenges the most significant are the bimodal or multimodal distribution, sparsity and tremendous heterogeneity in the data. Consequently, we will describe potential ways of statistical modeling of such data, finding differentially expressed genes and possible ways of constructing gene-gene interaction network using this data. Moreover, we will compare the performance of our modeling and differential analysis with respect to some other existing methods.
Biographical sketch of Professor Susmita Datta:
Susmita Datta, PhD
Co-Director of Biostatistics and Epidemiology Research Design (CTSI)
Dr. Susmita Datta is a Professor at University of Florida (UF), Department of Biostatistics. She was hired as a part of the university's Preeminence initiative. She is the Co-Director of the Biostatistics, Epidemiology and Research Design Program (BERD) of UF Clinical and Translational Science Institute. Before joining UF, Dr. Datta was at the University of Louisville, Department of Bioinformatics and Biostatistics, where she was a University Distinguished Scholar and Graduate Director of the master's and Ph.D. programs. She is a fellow of the American Statistical Association (ASA), an elected member of the International Statistical Institute (ISI), and fellow of the American Association for the Advancement of Science (AAAS). Her research area includes bioinformatics, genomics, proteomics, metabolomics, lipidomics, clustering and classification techniques, infectious disease modeling, statistical issues in population biology, systems biology, survival analysis, multi-state models and big data analytics. Dr. Datta has widely (>100) published in peer reviewed journals. She has recently published a book on "Statistical Analysis of Proteomics, Metabolomics, and Lipidomics Data Using Mass Spectrometry" by Springer.
Dr. Datta is enthusiastic in promoting women in STEM fields and has served as President of Caucus for Women in Statistics (CWS) and is presently appointed to the Committee of Women in Statistics of ASA (COWIS). She is the founding executive committee member of the Women in Statistics and Data Science conference (WSDS).