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Statistics for Genomic Data Science
  • Level Foundation
  • المدة 9 ساعات hours
  • الطبع بواسطة Johns Hopkins University
  • Offered by

عن

An introduction to the statistics behind the most popular genomic data science projects. This is the sixth course in the Genomic Big Data Science Specialization from Johns Hopkins University.

الوحدات

Introduction

    • 6 Videos
    • 3 Readings
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6 Videos

  • Welcome to Statistics for Genomic Data Science
  • What is Statistics?
  • Finding Statistics You Can Trust (4:44)
  • Getting Help (3:44)
  • What is Data? (4:28)
  • Representing Data (5:23)

3 Readings

  • Syllabus
  • Pre Course Survey
  • Introduction and Materials

Module 1

    • 15 Videos
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15 Videos

  • Module 1 Overview (1:07)
  • Reproducible Research (3:42)
  • Achieving Reproducible Research (5:02)
  • R Markdown (6:26)
  • The Three Tables in Genomics (2:10)
  • The Three Tables in Genomics (in R) (3:46)
  • Experimental Design: Variability, Replication, and Power (14:17)
  • Experimental Design: Confounding and Randomization (9:26)
  • Exploratory Analysis (9:21)
  • Exploratory Analysis in R Part I (7:22)
  • Exploratory Analysis in R Part II (10:07)
  • Exploratory Analysis in R Part III (7:26)
  • Data Transforms (7:31)
  • Clustering (8:43)
  • Clustering in R (9:09)

Quiz

    • 1 Assignment
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1 Assignment

  • Module 1 Quiz

Module 2

    • 14 Videos
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14 Videos

  • Module 2 Overview (1:12)
  • Dimension Reduction (12:13)
  • Dimension Reduction (in R) (8:48)
  • Pre-processing and Normalization (11:26)
  • Quantile Normalization (in R) (4:49)
  • The Linear Model (6:50)
  • Linear Models with Categorical Covariates (4:08)
  • Adjusting for Covariates (4:16)
  • Linear Regression in R (13:03)
  • Many Regressions at Once (3:50)
  • Many Regressions in R (7:21)
  • Batch Effects and Confounders (7:11)
  • Batch Effects in R: Part A (8:18)
  • Batch Effects in R: Part B (3:50)

Quiz

    • 1 Assignment
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1 Assignment

  • Module 2 Quiz

Module 3

    • 15 Videos
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15 Videos

  • Module 3 Overview (1:07)
  • Logistic Regression (7:03)
  • Regression for Counts (5:02)
  • GLMs in R (9:28)
  • Inference (4:18)
  • Null and Alternative Hypotheses (4:45)
  • Calculating Statistics (5:11)
  • Comparing Models (7:08)
  • Calculating Statistics in R
  • Permutation (3:26)
  • Permutation in R (3:33)
  • P-values (6:04)
  • Multiple Testing (8:25)
  • P-values and Multiple Testing in R: Part A (5:58)
  • P-values and Multiple Testing in R: Part B (4:23)

Quiz

    • 1 Assignment
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1 Assignment

  • Module 3 Quiz

Module 4

    • 14 Videos
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14 Videos

  • Module 4 Overview (1:21)
  • Gene Set Enrichment (4:19)
  • More Enrichment (3:59)
  • Gene Set Analysis in R (7:43)
  • The Process for RNA-seq (3:59)
  • The Process for Chip-Seq (5:25)
  • The Process for DNA Methylation (5:03)
  • The Process for GWAS/WGS (6:12)
  • Combining Data Types (eQTL) (6:04)
  • eQTL in R (10:36)
  • Researcher Degrees of Freedom (5:49)
  • Inference vs. Prediction (8:52)
  • Knowing When to Get Help (2:31)
  • Statistics for Genomic Data Science Wrap-Up (1:53)

Quiz

    • 1 Assignment
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1 Assignment

  • Module 4 Quiz

Post Course Survey

    • 1 Readings
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1 Readings

  • Post Course Survey
Jeff Leek, PhD
Instructor

Jeff Leek, PhD