Analyzing Genomic Data in R

अद्यतन 03/2026

Start exploring the world of computational biology with essential Bioconductor packages and workflows for next-generation sequencing data analysis.

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या

जारी रखने पर, आप हमारी उपयोग की शर्तें, हमारी गोपनीयता नीति को स्वीकार करते हैं और यह भी कि आपका डेटा संयुक्त राज्य अमेरिका में संग्रहीत किया जाता है।

ट्रैक विवरण

Analyzing Genomic Data in R

Are you interested in analyzing next-generation sequencing data but lacking in strong computational skills? In this skills track, geared towards non-computational biologists, you will learn to use Bioconductor, the specialized repository for bioinformatics software, along with essential Bioconductor packages. Then, you'll learn about current best-practice workflows for RNA sequencing differential expression analysis, as well as Chip-sequencing data.

आवश्यक शर्तें

इस ट्रैक के लिए कोई पूर्व शर्त नहीं है।

Course
1
Introduction to Bioconductor in R
Learn to use essential Bioconductor packages for bioinformatics using datasets from viruses, fungi, humans, and plants!
Course
2
RNA-Seq with Bioconductor in R
Use RNA-Seq differential expression analysis to identify genes likely to be important for different diseases or conditions.
Course
3
Differential Expression Analysis with limma in R
Learn to use the Bioconductor package limma for differential gene expression analysis.
Course
5
ChIP-seq with Bioconductor in R
Learn how to analyse and interpret ChIP-seq data with the help of Bioconductor using a human cancer dataset.