Introduction to the main workflow used in genomic data analysis by recreating published research. Create a free account to see full content.
Paper used in pipeliner: Identification of and enriched pathways in lung cancer using bioinformatics analysis Data: GSE19804
Recommended Prerequisites
- AP Biology or higher (specifically genetics)
- Beginner experience with R, Python, or an equivalent statistical language
Technical Objectives
- Introduction to bioinformatics and the different types of -omics data
- Application of the basic pipeline used in large-scale data analysis: data collection, QC, statistical analysis, and functional interpretation of results
- Learning how to work through a coherent workflow and interpret output results and relate them to biological problems
- Learning the basics of RStudio and R programming
- Introduction to Bioconductor and packages used in transcriptomics data analysis relevant to the above-mentioned pipeline
- Learning how to troubleshoot in R and read R documentation
- Using free, public bioinformatics tools used for functional analysis of transcriptomics results
Soft Skills Objectives
- Reading and understanding scientific papers
- Project management
- Virtual collaboration and teamwork
- Technical presentation
- Time management and much more
- Leadership & mentoring (student leads)