Learn to use tools from the Bioconductor project to perform analysis of genomic data. This is the fifth course in the Genomic Big Data Specialization from Johns Hopkins University.
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Informações sobre o curso
Habilidades que você terá
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Universidade Johns Hopkins
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.
Programa - O que você aprenderá com este curso
Week One
The class will cover how to install and use Bioconductor software. We will discuss common data structures, including ExpressionSets, SummarizedExperiment and GRanges used across several types of analyses.
Week Two
In this week we will learn how to represent and compute on biological sequences, both at the whole-genome level and at the level of millions of short reads.
Week Three
In this week we will cover Basic Data Types, ExpressionSet, biomaRt, and R S4.
Week Four
In this week, we will cover Getting data in Bioconductor, Rsamtools, oligo, limma, and minfi
Avaliações
Principais avaliações do BIOCONDUTOR PARA CIÊNCIA DE DADOS GENÔMICOS
I think it is a good class overall but the pace is fast and the resources that can help you is lacking. This will be good for someone who already kind of understands bioconductor.
Before you can run, you must learn to walk. Kasper's well paced tutorials will give you confidence using the tools you need for genomic study.
Excellent introduction to Bioconductor. Thanks to the team. However, absence of inputs from TA or Instructor was felt in the discussion.
Amazing course, motivated me to use bio conductor for descriptive seq studies of DNA.
Sobre Programa de cursos integrados Análise de Dados GenômicosAnálise Genômica
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.

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