More info on my Google Scholar profile


  • Fitzerald et al. Driving Under the Influence of Cannabis: Impact of Combining Toxicology Testing with Field Sobriety Tests. Clinical Chemistry. [link]
  • Leas et al. E-commerce licensing loopholes: a case study of online shopping for tobacco products following a statewide sales restriction on flavoured tobacco in California. Tobacco Control. [link]


  • Donoghue T, Voytek B, and Ellis SE. Course Materials for Data Science in Practice. The Journal of Open Source Education. [link]
  • Lau S, Eldridge J, Ellis SE, Fraenkel A, Langlois M, Rampure S, Tiefenbruck J, and Guo P. The Challenges of Evolving Technical Courses at Scale: Four Case Studies of Updating Large Data Science Courses. ACM Conference on Learning @ Scale (L@S). [link]


  • Hubbard JA, Hoffman MA, Ellis SE, Sobolesky PM, Smith BE, Suhandynata RT, Sones EG, Sanford SK, Umlauf A, Huestis MA, Grelotti DJ, Grant I, Marcotte RD, and Fitzgerald RL (2021). Biomarkers of Recent Cannabis Use in Blood, Oral Fluid and Breath. Journal of Analytical Toxicology. [link]
  • Hoffman MA, Hubbard JA, Sobolesky PM, Smith BE, Suhandynata RT, Sanford S, Sones EG, Ellis SE, Umlauf A, Huestis MA, Grelotti DJ, Grant I, Marcotte TD, and Fitzgerald RL (2021). Blood and Oral Fluid Cannabinoid Profiles of Frequent and Occasional Cannabis Smokers. Journal of Analytical Toxicology. [link]


  • Donoghue T, Voytek B, and Ellis SE (2020). Teaching Creative and Practical Data Science at Scale. Journal of Statistics Education and Data Science. [link]


  • Madugundu AK, Hyun Na C, Nirujogi RS, Reunuse S, Kim KP, Burns KH, Langmead B, Ellis SE, Collado-Torres L, Halushka MK, Kim M, Pandey A (2019) Integrated Transcriptomic and Proteomic Analysis of Primary Human Umbilical Vein Endothelial cells. Proteomics. [link]

  • Moriah E. Katt, Lakyn N. Mayo, Shannon E. Ellis, Vasiliki Mahairaki, Jeffrey D. Rothstein, Linzhao Cheng & Peter C. Searson (2019) The role of mutations associated with familial neurodegenerative disorders on blood–brain barrier function in an iPSC model. Fluids and Barriers of the CNS. [link]


  • Ellis SE, Collado-Torres L, Jaffe AE, Leek JT (2018) Improving the value of public RNA-seq expression data by phenotype prediction. Nucleic Acids Research. [link]


  • Andrews SV, Ellis SE, Bakulski KM, Sheppard B, Croen LA, Hertz-Picciotto I, Newschaffer CJ, Feinberg AP, Arking DE, Ladd-Acosta C, Fallin MD (2017) Cross-tissue integration of genetic and epigenetic data offers insight into autism spectrum disorder. Nature Communications. [link]

  • Ellis SE and Leek JT (2017) How to share data for collaboration. The American Statistician. [link]

  • Collado-Torres L, Nellore A, Kammers K, Ellis SE, Taub MA Hansen KD, Jaffe AE, Langmead B, Leek JT (2017) Reproducible RNA-seq analysis using recount2. Nature Biotechnology doi: 10.1038/nbt.3838 [link] [database] [reproducible analysis] [software]

  • Ellis SE, Gupta S, Moes A, West AB, Arking DE (2017) Exaggerated CpH Methylation in the Autism-Affected Brain. Molecular Autism doi: 10.1186/s13229-017-0119-y [link]


  • Ellis SE, Panitch R, West AB, Arking DE (2016) Transcriptome analysis of cortical tissue reveals shared sets of downregulated genes in autism and schizophrenia. Translational Psychiatry doi: 10.1038/tp.2016.87 [link]


  • Huang, Haritunas, Okou, et al. (2015) Characterization of genetic loci that affect susceptibility to inflammatory bowel diseases in African Americans. Gastroenterolgy doi: 10.1053/j.gastro.2015.07.065 [link]


  • Gupta S, Ellis SE, Ashar FN, Moes A, Baser JS, Zhan J, West AB, Arking DE (2014) Transcriptome analysis reveals dysregulation of innate immune response genes and neuronal activity-dependent genes in autism. Nature Communications doi: doi:10.1038/ncomms6748 [link]


  • Ellis SE, Gupta S, Ashar FN, Bader JS, West AB, Arking DE. (2013) RNA-Seq optimization with eQTL gold standards. BMC Genomics doi: 10.1186/1471-2164-14-892 [link]