BIOS 221/STATS 366: Modern Statistics for Modern Biology

Summer Quarter 2015

Manhattan Plot for Type 2 Diabetes 

Manhattan Plot from the Wellcome Trust Case Control Consortium, Nature 2007.

This type of plot is used to show which genomic loci are significantly associated with a phenotype such as Type 2 Diabetes.

Announcements

  • In preparation for the course, please follow the download instructions.

  • For those taking the course for a letter grade, the final 10 page paper showing and interpreting your results (from your proposal) is due August 7th.

Schedule and Location

  • Lecture: 06/22/2014 - 07/10/2015 MTWThF, 10:00 AM - 11:50 AM

    • Location: LKSC 120

  • Labs: Week 1: TWThF, Week2: MTWTh, Week 3: MTWTh

    • Location and Times: LKSC 120, 2:00 - 3:30 PM

Instructors & TAs

Instructors

Susan Holmes

  • Office: Sequoia Hall 102

  • E-Mail: susan [at] stat [dot] stanford [dot] edu

  • Phone: (650) 725 [hyphen] 1925

Trevor Martin

  • Office: Herrin Hall 309

  • E-Mail: trevorm [at] stanford [dot] edu

  • Phone: (650) 723 [hyphen] 1849

TAs

Haben Michael

  • Office: Sequoia Hall

  • E-Mail: haben.michael [at] stanford [dot] edu

Lan Huong Nguyen

  • Office: Sequoia Hall

  • E-Mail: lanhuong [at] stanford [dot] edu

Course Overview and Prerequisites

Course Overview
  • Introductory Examples: Poisson, Multinomial, Probability Statistics

  • High Graphics (real examples of Biological Data)

  • Sequence Data, Variants, Mixture Simulation

  • Flow Cytometry

  • Clustering and Distances

  • RNA Seq : (without PCA)

  • PCA intro to SVD, PCA for RNAseq

  • Multiple Testing

  • MDS and Chisquare CA

  • Trees and Graphs

  • Microbial Ecology

  • ChIP Seq

  • Image Analysis and Spatial Stats

  • Experimental Design

Grading
  • Seven Labs to Complete (6 Best Used): 20%

  • Participation in Class: 20%

  • Lecture scribing : 10% (Due July 11th)

  • Project Proposal (Due July 10th; Required for Letter Grade): 15%

  • Final Project (Due August 6th; Required for Letter Grade) 35%

Prerequisites
  • Permission of instructors

  • Basic knowledge of R programming

    • Alternatively, willingness to learn R prior to the course (See BIOS205)