Statistics for Genomic Data Science

开始时间: 04/22/2022 持续时间: 4 weeks

所在平台: CourseraArchive

课程类别: 其他类别

大学或机构: Johns Hopkins University(约翰•霍普金斯大学)

课程主页: https://www.coursera.org/course/genstats

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课程详情

It isn't enough to just know how to use the tools. Doing genomic data science well means understanding the statistical principles at work. This class will provide an introduction to the statistics behind the most popular genomic data science projects. This will help you ask better questions, plan better research, and interpret the results more accurately.

课程大纲

1. Experimental desgin

  • Types of data
  • Populations and samples
  • Bias and variance
  • Sample sizes 

2. Exploratory analysis/data processing

  • Plots (scatter, box, MA, funnel, loess)
  • Plots to avoid
  • Tables

3. Statistical inference

  • Normalization
  • Basic linear modeling
  • Batch effects
  • Multiple testing
  • Gene set analysis
4. Common mistakes to avoid
  • Overfitting
  • Normalization errors
  • Confounders
  • Irreproducibility
  • Significance chasing

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课程简介

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.

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