Robyn Ball, Ph.D.
Senior Biostatistician

Dr. Robyn L. Ball received her Ph.D. in Statistics from Texas A&M University in 2013 and is Senior Biostatistician in the Quantitative Sciences Unit (QSU) of the Department of Medicine (Biomedical Informatics) at Stanford University. Prior to her appointment at Stanford, she was a postdoctoral associate and statistical analyst at The Jackson Laboratory from 2013—2015, where she developed novel methodology, applied statistical models to genetic and genomic data, analyzed non-standard Next Generation Sequencing (NGS) data, and mentored students. During 2011—2012, she was awarded a fellowship at NASA where she developed a statistical model that predicts a subject’s heart age from the his/her electrocardiogram, winning an award from the NASA Inventions and Contributions Board. Also in 2011—2012, she completed two internships at UT MD Anderson Cancer Center where she applied machine learning methods to 1) identify distinct classes of breakpoint hotspots by comparing somatic copy number alterations (SCNAs) across eight human cancer types and 2) predict the lethality of knock-out mice using genomic data. In her current position at Stanford, she takes the statistical lead on a number of medical studies that pose methodological challenges. The areas of her statistical expertise include developing robust statistical methods to analyze high dimensional biomedical data, nonparametric statistics, statistical genetics, genomics and proteomics, machine learning methods, and pattern recognition.

Methodology Area of Interest:  nonparametric methods for high dimensional biomedical data, integrating multimodal data, interactive visualization, big data, statistical pattern identification, machine learning, Bayesian methodology, imaging, statistical genetics, genomics, and proteomics.

Clinical Area of Interest: neurology, Alzheimer's disease, cardiology, lupus, cancer

Selected Publications: 

Haque F, Ball RL (co first-author), Khatun S, Ahmed M, Kache S, Chisti MJ, Sarker SA, Maples SD, Pieri D, Korrapati TV, Sarnquist C. Evaluation of a Smartphone Decision-Support Tool for Diarrheal Disease Management in a Resource-Limited Setting. PLOS Neglected Tropical Diseases. 2017 Jan 19;11(1):e0005290.

Ball RL, Fujuwara Y, Sun F, Hu J, H MA, Carter GW. Regulatory complexity revealed by integrated cytological and RNA-seq analyses of meiotic substages in mouse spermatocytes. BMC Genomics August 12, 2016. 

Ball RL, Feiveson AH, Schlegel TT, Starc V, Dabney AR. Predicting “Heart Age” using Electrocardiography. J. Pers. Med. 2014 Mar 7; 4(1), 65-78. 

Ball RL, Feiveson AH, Schlegel TT, Dabney AR. Predicting “Heart Age” using Electrocardiography. NASA Tech Briefs. November 1, 2014.

Yuan Y, Xu Y, Xu J, Ball RL, Liang H. Predicting the lethal phenotype of the knockout mouse by integrating comprehensive genomic data. Bioinformatics. 2012 May1;28(9):1246-52. 

Li Y, Zhang L, Ball RL, Liang X, Lin J, Lin Z, Liang H. Comparative analysis of somatic copy-number alterations across different human cancer types reveals two distinct classes of breakpoint hotspots. Hum. Mol. Genet. 2012 Nov 15; 21(22):4957-65.

 

For a comprehensive list of her publications, please see http://www.ncbi.nlm.nih.gov/sites/myncbi/1BU6vLapNVSQA/bibliography/49431505/public/?sort=date&direction=ascendin