Course website: https://bu-bioinfo.github.io/bf528/index.html
- Learn the molecular mechanisms and basic data analysis steps underlying common NGS techniques used to study genomics and transcriptomics.
- Develop proficiency in creating bioinformatics workflows emphasizing reproducibility and portability.
- Gain experience generating and interpreting bioinformatics analyses in a biological context.
Below are some prominent biological and computational topics that will be addressed during the course:
- High Throughput Sequencing Technologies
- RNAseq, ChIPseq, scRNAseq, ATACseq
- Proteomics, Metabolomics, and other omics technologies
- Computational Workflow Tools: Snakemake, Nextflow
- Reproducibility and Replicability Tools: Git, Docker, Conda
- Bioinformatics Databases and File Formats
This course introduces students to modern bioinformatics studies with a specific focus on next-generation sequencing (NGS) data analysis.
- Lectures will blend biological and computational topics essential for understanding high-throughput genomics techniques.
- Practical lab sessions will provide hands-on experience with developing computational workflows for NGS data, including RNAseq, ChIPseq, and scRNAseq.
Key Features:
- Emphasis on reproducibility, portability, and replicability.
- Weekly tasks lead to a final project report for evaluation.
- Basic understanding of biology and genomics (e.g., BF527, BE505/BE605).
- Programming experience in modern languages (e.g., R, Python, Java, etc.).
Joey Orofino & Adam Labadorf
- Weekly Progress: Each project is split into four weekly parts.
- Pipeline Development: Learn to process NGS data end-to-end using Nextflow, Git, Conda, Docker, and HPC.
- Final Evaluation: Compare your analysis results to published papers and discuss any differences.
- Project 0: Not graded (Introductory).
- Project 1: 25%
- Project 2: 25%
- Project 3: 50%