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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課程信息
您將獲得的技能
- Statistics
- Data Analysis
- R Programming
- Biostatistics
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约翰霍普金斯大学
The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.
授課大綱 - 您將從這門課程中學到什麼
Module 1
This course is structured to hit the key conceptual ideas of normalization, exploratory analysis, linear modeling, testing, and multiple testing that arise over and over in genomic studies.
Module 2
This week we will cover preprocessing, linear modeling, and batch effects.
Module 3
This week we will cover modeling non-continuous outcomes (like binary or count data), hypothesis testing, and multiple hypothesis testing.
Module 4
In this week we will cover a lot of the general pipelines people use to analyze specific data types like RNA-seq, GWAS, ChIP-Seq, and DNA Methylation studies.
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- 5 stars54.88%
- 4 stars26.81%
- 3 stars11.04%
- 2 stars2.52%
- 1 star4.73%
來自基因组数据科学所需的统计学的熱門評論
Great course as a starting point for statistical genomics!
This is the best. It opens my eye for genomic data analysis.
Very good course and useful understanding statistical aspects of data.
It is really great that told me lots of basic statistical information that I didn't know.
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