Chris Miller, PhD

I currently work in the Genome Institute at Washington University in St. Louis, where I lead a group that develops and applies computational tools to give us insight into the origins and progression of cancer.

Before moving to WashU, I completed a PhD in Computational Biology at Baylor College of Medicine. My thesis was about using bioinformatic techniques and large-scale data integration to help understand the aetiology of cancer.

My core research interests include:

• Cancer - studying the evolutionary pressures driving tumorigenesis
• Integrative analysis - combining disparate sources of genomic data to place aberrations into a functional context
• Structural changes in the human genome and their contributions to disease
• Developing open-source software for integrating, mining, and visualizing genomic data
• Utilizing online technologies to drive science communication and collaboration

• PhD, Structural and Computational Biology
  and Molecular Biophysics program
  Baylor College of Medicine
  Mentor: Dr. Aleksandar Milosavljevic
  Thesis: Detection and Integrative Analysis of Genomic Aberrations in Cancer
  (graduated February 2011)
• BS degrees in Biology and Computer Science
  Truman State University
  (graduated May 2005)

• Designing genomic analysis pipelines using Perl, R, Bash, Ruby, and Linux
• Synthesizing data from a wide variety of genomic techniques and technologies, including:
  • massively-parallel sequencing:
      - paired-end sequencing for structural mapping
      - RNAseq for transcriptome interrogation
      - bisulfite sequencing for epigenomic assays
      - copy-number inference from read depth
      - SNP and indel detection
    
  • array comparative genomic hybridization (aCGH)
  • SNP, expression, and methylation arrays
  • functional and pathway databases
• Design of machine-learning tools for extracting patterns from genomic data
• Utilizing high-performance linux clusters to expidite analyses
• Data visualization and web design
• Facilitating interdisciplinary collaborations

• Genomic and Epigenomic Landscapes of Adult De Novo Acute Myeloid Leukemia
  The Cancer Genome Atlas Research Network. New England Journal of Medicine.
  doi:10.1056/NEJMoa1301689
• The Origin and Evolution of Mutations in Acute Myeloid Leukemia
  Welch JS, Ley TJ, Link DC, Miller CA, Larson DE, Koboldt DC, Wartman, LD, et al. Cell.
  doi:10.1016/j.cell.2012.06.023
• Whole-genome analysis informs breast cancer response to aromatase inhibition
  Ellis MJ, Ding L, Shen D, Luo J, Suman VJ, Wallis J, Van Tine BA, Hoog J, et al. Nature.
  doi:10.1038/nature11143
• Background Mutations in Parental Cells Account for Most of the Genetic Heterogeneity of Induced Pluripotent Stem Cells
  Young MA, Larson DE, Sun C, George DR, Ding L, Miller CA, Ling L, et al. Cell Stem Cell.
  doi:10.1038/nature11143
• VarScan 2: Somatic mutation and copy number alteration discovery in cancer by exome sequencing.
  Koboldt DC, Zhang Q, Larson DE, Shen D, McLellan M, Lin L, Miller CA, Mardis ER, Ding L, Wilson RK. Genome Research.
  doi:10.1101/gr.129684.111
• Clonal evolution in relapsed acute myeloid leukaemia revealed by whole-genome sequencing.
  Ding L, Ley T, Larson DE, Miller CA, Koboldt DC, Welch JS, et al. Nature.
  doi:10.1038/nature10738
• readDepth: A parallel R package for detecting copy-number alterations from short sequencing reads.
  Miller CA; Hampton OA, Coarfa C, Milosavljevic A. PLoS ONE 6(1):e16327, 2011
  doi:10.1371/journal.pone.0016327
• Discovering functional modules by identifying patterns of recurrent and mutually exclusive mutations in cancer.
  Miller CA, Settle SH, Sulman EP, Aldape KD, Milosavljevic, A. BMC Medical Genomics 4:34, 2011
  doi:10.1186/1755-8794-4-34
• BioStar: An Online Question & Answer Resource for the Bioinformatics Community.
  Parnell LD, Lindenbaum P, Shameer K, Dall'Olio GM, Swan DC, Jensen LJ, Cockell SJ, Pedersen BS, Mangan ME, Miller CA, Albert I. PLoS Comput Biol. 2011 7(10): e1002216.
  doi:10.1371/journal.pcbi.1002216
• Long-range massively parallel mate pair sequencing detects distinct mutations and similar patterns of structural mutability in two breast cancer cell lines
  Hampton OA, Miller CA, Koriabine, M, Li J, Den Hollander P, Carbone L, Nefedov M, Boudewijn, FH, Lee AV, De Jong PJ, Milosavljevic, A. Cancer Genet. 2011 Aug;204(8):447-57.
  doi:10.1016/j.cancergen.2011.07.009
• Pash 3.0: A versatile software package for read mapping and integrative analysis of genomic and epigenomic variation using massively parallel DNA sequencing.
  Coarfa C, Yu F, Miller CA, Chen Z, Harris RA, Milosavljevic A. BMC Bioinformatics 11:572, 2010
  doi:10.1186/1471-2105-11-572
• A sequence-level map of chromosomal breakpoints in the MCF-7 breast cancer cell line yields insights into the evolution of a cancer genome.
  Hampton OA, Den Hollander P, Miller CA, Delgado DA, Li J, Coarfa C, Harris RA, Richards S, Scherer SE, Muzny DM, Gibbs RA, Lee AV, Milosavljevic, A. Genome Res. Advance Online Publication, December 3, 2008.
  doi:10.1101/gr.080259.108
• Comprehensive genomic characterization defines human glioblastoma genes and core pathways.
  The Cancer Genome Atlas Research Network. Nature 455, 1061-1068 (23 October 2008)
  doi:10.1038/nature07385

• Multi-dimensional clustering of mutations from heterogeneous tumors offers insight into clonal architecture, tumor evolution, and response to therapy
  Presentation: The Cancer Genome Atlas Steering Committee Meeting (2013)
• Assessing Tumor Heterogeneity and Tracking Clonal Evolution Using Whole Genome or Exome Sequencing
  Presentation: The Cancer Genome Atlas Scientific Symposium (2012) link
• Identification of driver mutations in non-coding functional regions of cancer genomes
  Poster: Genome Informatics (2012)
• Discovering functional modules relevant for cancer progression by identifying patterns of recurrent and mutually exclusive mutations in tumor samples
  Poster: CSHL Biology of Genomes (2010)
• Integrative analysis of multi-dimensional genomic data identifies key relationships between cancer pathways
  Poster: SCBMB Retreat (2008)
• Pash: Efficient Genome-Scale Sequence Anchoring by Positional Hashing
  Poster: Rice University Computational Biology Conference (2006)
• An Image Analytic Approach to Characterizing Vasculogenic Networks
  Presentation: Truman State University Student Research Symposium (2005)

• Computer Aided Discovery Methods (2007 and 2008)
  Contributed to the development of the course and taught computational labs on:
  • Studies of genome variation
  • Transcriptional regulatory pathways
• Computational Mathematics for Biomedical Scientists (2008)
  • Teaching Assistant
• Advanced Topics: Quantitative Biology (2005)
  • Teaching Assistant

• Classification and analysis of Alu SINEs in Human and Chimpanzee Chromosomes 3 and 12
  Mentor: Dr. Aleksandar Milosavljevic (BCM)
  Rotation project - Fall 2005
• Development of an open-source image analysis toolset for describing the structure and dynamics of biological tissue.
  Mentors: Dr Jason Miller (Truman State University) and Dr Robert Baer (Kirksville College of Osteopathic Medicine)
  Summer 2004 - Spring 2005