Science at the Edge Seminar
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Speaker: Sunduz Keles, Department of Biostatistics & Medical Informatics and Department of Statistics, University of Wisconsin, Madison
Title: Statistical data integration for genomic and epigenomic data
Refreshments at 11:15 am.
Date: Fri, 06 Oct 2017, 11:30 am – 12:30 pm
Location: 1400 BPS Bldg.
My group works on high dimensional statistical genomics and epigenomics with a specific emphasis on data integration problems. In this seminar, I will present our statistical approaches for NGS read-level data integration for studying repetitive regions of the genome and data integration for genomewide-association studies.
- X. Zeng, B. Li, R. Welch, C. Rojo-Alfaro, Y. Zheng, C. Dewey, and S. Keles. Perm-seq: Mapping protein-DNA interactions in segmental duplication and highly repetitive regions of genomes with prior-enhanced read mapping. PLoS Computational Biology, 11(10):e1004491, 2015.
- C. Zuo, S. Shin, and S. Keles. atSNP: transcription factor binding affinity testing for regulatory SNP detection. Bioinformatics, 31(20):3353-5, 2015.
- P. Liu, R. Sanalkumar, E. H. Bresnick, S. Keles*, and C. N. Dewey*. Integrative analysis with ChIP-seq advances the limits of transcript quantification from RNA-seq, Genome Research, 26(8): 1124–1133, 2016.
- S. Shin and S. Keles. Annotation regression for genome-wide association studies with an application to psychiatric genomic consortium data. Statistics in Biosciences, 9(1):50-72, 2017.