The Pan Omics & Data Science (PODS) Core

provides omic study support for members of the Michigan Center on Lifestage Environmental Exposures and Disease.

Contacts

Kai Wang
734-763-8013
wangdaha@umich.edu

Katie Zarins
734-763-6532
kmrents@umich.edu

Laura Rozek
734-615-9816
rozekl@umich.edu

Maureen Sartor, PhD
734-763-8013
sartorma@umich.edu

Location

School of Public Health
1415 Washington Heights, Ann Arbor, MI

Affiliations
Public Health

Who We Serve

Members of M-LEEaD Center, M-LEEaD Center grant recipients, and researchers associated with all Center-related projects

Core Summary

The Pan Omics & Data Science (PODS) Core provides comprehensive and innovative support for members of the Michigan Center on Lifestage Environmental Exposures and Disease (M-LEEaD). We also support M-LEEaD pilot grant recipients. The PODS Facility Core services include assistance with study design, sample collection and preparation, data analyses, results integration and interpretation, advanced visualizations, and dissemination for a broad range of omics-based studies, including integration with clinical/ translational data. Specific omics approaches supported by the PODS Core include genomic assays (WGS, SNP arrays), RNA-seq (bulk and single-cell), microRNA expression, DNA methylation assays (BeadChip, ERRBS, WGBS, meDIP-seq), DNA hydroxymethylation, ATAC-seq (bulk and single-cell), ChIP-seq, adductomics, and microbiome profiling. We also provide support for downstream analyses such as pathway analyses, multi-omics data integration, and predictions using machine learning.

Service Categories: Data Tools and Analysis Service Categories: Gene Sequencing, Expression and Analysis Service Categories: Informatics, Statistics and Computation Service Categories: Molecular Biology

Services

Bioinformatics analysis
DNA methylation (EPIC BeadChip, bisulfite sequencing), Integrative omics analyses, Pathway and interaction network analyses,

Consultations for omics experiments
DNA/RNA extractions, Facilitate interactions with other Cores (e.g. Metabolomics), Sample preparation, Study design, Targeted validations,


Equipment

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