2023 WORKSHOPS and BOOTCAMPS

(2) Statistics Bootcamp for Neuroscience and Single-Cell Omics Data Analysis

This bootcamp will be free and open to all conference registrants. Professor Zhaoxia Yu and Professor Wei Li will be the instructors for this bootcamp, which includes lectures and hands-on components (data visualization, processing, and statistical testing using statistical packages). Dr. Yu’s research is focused on developing statistical methods to address the challenges confronting scientists when analyzing multivariate and high dimensional data. Dr. Yu has recently published a well-cited article in Neuron. She will teach attendees how to use the methods described in this paper and other related publications. She will also provide statistical consulting through the UCI CNCM.

Dr. Li is an Endowed Chair and Professor of Bioinformatics in the Department of Biological Chemistry at UCI School of Medicine. He has developed a series of widely used bioinformatics algorithms to harness the full power of population-scale genomics and epigenomics data. He will present two recent projects that leverage bioinformatics and all-in-human large-scale data analysis to facilitate scientific discoveries. He will also discuss the importance of statistical rigor in data analysis, and the solution to deal with the exaggerated false positives by popular differential expression methods when analyzing human population samples.

Agenda:
8:30 am – 9:50 am: Analyzing Clustered / Dependent Data in Neuroscience Research
8:30 am – 9:00 am (30 minutes): A review of linear models and their limitations
9:00 am – 9:50 am (50 minutes): Introduction to mixed-effects models
9:50 am – 10:10 am: coffee break
10:10 am – 11:30 am:
10:10 am – 10:30 am (20 minutes): exaggerated false positives in popular differential expression methods
10:30 am – 11:00 am (30 minutes): epigenetic liquid biopsy for cancer and brain disorders
11:00 am – 11:30 am: RNA therapy targeting Alternative Polyadenylation
11:30 am – 1:00 pm: Lunch break
1:00 pm – 3:00 pm: Hands-on demos (a laptop is required)
1:00 pm – 1:30 pm (30 minutes): Install R and R Studio
1:30 pm – 3:30 pm (120 minutes): Use R to visualize and model clustered data

References:

1. Yu, Z., Guindani, M., Grieco, S.F., Chen, L., Holmes, T.C. and Xu, X., 2022. Beyond t-test and ANOVA: Applications of mixed-effects models for more rigorous statistical analysis in neuroscience research. Neuron, 110(1), pp.21-35.
2. Cui Y, Arnold FJ, Peng F, Wang D, Li JS, Michels S, Wagner EJ, La Spada AR, Li W: Alternative polyadenylation transcriptome-wide association study identifies APA-linked susceptibility genes in brain disorders. Nature Communications 14 (2023) 583.
3. Lin N, Lin Y, Xu J, Liu D, Li D, Meng H, Gallant MA, Kubota N, Roy D, Li JS, Gorospe EC, Sherman M, Gish RG, Abou Alfa GK, Nguyen MH, Taggart DJ, Van Etten RA, Hoshida Y, Li W: A multi-analyte cell-free DNA-based blood test for early detection of hepatocellular carcinoma. Hepatology Communications 6 (2022) 1753-1763. P
4. Li L, Huang KL, Gao Y, Cui Y, Elrod ND, Wang G, Ji P, Peng F, Russell WK, Wanger EJ, Li W: An atlas of alternative polyadenylation quantitative trait loci contributing to complex trait and disease heritability. Nature Genetics 53 (2021) 994
5. Xu J, Shi J, Cui X, Cui Y, Li JJ, Goel A, Chen X, Issa JP, Su J, Li W: Cellular Heterogeneity-Adjusted cLonal Methylation (CHALM) improves prediction of gene expression. Nature Communications 12 (2021) 400.
6. Kandimalla R^, Xu J^, Link A, Matsuyama T, Yamamura K, Parker MI, Uetake H, Balaguer F, Borazanci E, Tsai S, Evans D, Meltzer SJ, Baba H, Brand R, Von Hoff D, Li W, Goel A: EpiPanGI Dx: A cell-free DNA methylation fingerprint for the early detection of gastrointestinal cancers. Clinical Cancer Research 27 (2021) 6135-6144.