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Statistics for Genomic Data Science

With genomics sparks a revolution in medical discoveries, it becomes imperative to be able to better understand the genome, and be able to leverage the data and information from genomic datasets. Genomic Data Science is the field that applies statistics and data science to the genome.This Specialization covers the concepts and tools to understand, analyze, and interpret data from next generation sequencing experiments. It teaches the most common tools used in genomic data science including how to use the command line, along with a variety of software implementation tools like Python, R, Biocon

Created by: Jeff Leek

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Overall Score : 76 / 100

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Course Description

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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Instructor Details

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Jeff Leek is an Assistant Professor of statistics at the Johns Hopkins Bloomberg School of Public Health and co-editor of the Simply Statistics Blog. He received his Ph.D. in statistics from the University of Washington and is recognized for his contributions to genomic data analysis and statistical methods for personalized medicine. His data analyses have helped us understand the molecular mechanisms behind brain development, stem cell self-renewal, and the immune response to major blunt force trauma. His work has appeared in the top scientific and medical journals Nature, Proceedings of the National Academy of Sciences, Genome logy, and PLoS Medicine. He created Data Analysis as a component of the year-long statistical methods core sequence for statistics students at Johns Hopkins. The course has won a teaching excellence award, voted on by the students at Johns Hopkins, every year Dr. Leek has taught the course.

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Reviews

3.8

33 reviews in total

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By Hylke C D on 25-Sep-19

Much of the code is broken because it is outdated. In the specialisation you learn to use Python, and here all of a sudden they switch to R. Some familiarity with R is assumed in this course. A lot of the functions and packages that are used are not discussed at all. By far the worst course I have taken on coursera so far.

By YuanL on 8-Sep-19

Thanks!

By Ariful l on 12-Aug-19

good for learning

By Chuan J on 16-Jul-19

It is really great that told me lots of basic statistical information that I didn't know.

By Tushar K on 25-Mar-19

Very good course and useful understanding statistical aspects of data.

By Dr. P R I on 1-Mar-19

good

By Stefanie M on 25-Feb-19

In the course, easy concepts are well explained, but the more complex topics are very tricky to understand. However, I appreciated the enthusiasm of the teacher a lot

By David B on 24-Feb-19

Theory part, remaining that it has to be done in pills, could be done a lot better. R part is done better, but the principal issue is that you have not a clear connection with theory.

By Nitin S on 19-Feb-19

sometimes termininology was used interchangeably, which can be confusing for a beginner but overall a good introduction to statistcs for genomic data analysis

By Hemanoel P A on 24-Jan-19

This is totally not for beginners..

By Hamzeh M T on 8-Nov-18

Great place to start learning genomics in R

By Ian P on 30-Aug-18

I did my best to work through module 1, but encountered one problem after another with installing the various required R packages, due to version issues. From the absence of recent discussion posts it seems that this is not really a current, viable course. From what I have seen of the course, I get the impression that even if package installation went smoothly, the course is more about R than statistics or genomics - which is not what I joined for.

Showing 12 of 33 reviews