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Introduction to Bioconductor in R
4.8(119)18k studentsINTERMEDIATEEnglish
Korshub's take
The Korshub Take
This intermediate R course introduces Bioconductor, the leading open-source platform for genomic data analysis and bioinformatics. It provides essential hands-on experience navigating genomic ranges, biological sequences, and specialized R packages designed for targeted and whole-genome datasets.
Who It's For
Bioinformaticians, life science researchers, and R programmers working with genomic sequence data and biological big data.
Key Takeaways
- Bioconductor Infrastructure: Understand the core architecture, built-in datasets, and package ecosystem powering computational biology in R.
- Genomic Intervals & Ranges: Work with interval data and range operations using IRanges and GenomicRanges.
- Biological Sequence Analysis: Process biological sequence data using BSgenome, Biostrings, and TxDB packages.
- Quality Control & Short Reads: Inspect raw sequencing data and evaluate sequence quality using ShortRead and Rqc.
About this course
Much of the biological research, from medicine to biotech, is moving toward sequence analysis. We are now generating targeted and whole genome big data, which needs to be analyzed to answer biological questions. To help you get started, you will be introduced to The Bioconductor project. Bioconductor is and builds the infrastructure to share software tools (packages), workflows and datasets for the analysis and comprehension of genomic data. Bioconductor is a great platform accessible to you, and it is a community developed open software resource. By the end of this course, you will be able to use essential Bioconductor packages and get a grasp of its infrastructure and some built-in datasets. Using BSgenome, Biostrings, IRanges, GenomicRanges, TxDB, ShortRead and Rqc with real datasets from different species is going to be an exceptional experience!
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