References and Resources

References

Geistlinger, Ludwig, Gergely Csaba, Mara Santarelli, Marcel Ramos, Lucas Schiffer, Nitesh Turaga, Charity Law, et al. 2020. “Toward a Gold Standard for Benchmarking Gene Set Enrichment Analysis.” Briefings in Bioinformatics, February. https://doi.org/10.1093/bib/bbz158.

Huber, Wolfgang, Vincent J Carey, Robert Gentleman, Simon Anders, Marc Carlson, Benilton S Carvalho, Hector Corrada Bravo, et al. 2015. “Orchestrating High-Throughput Genomic Analysis with Bioconductor.” Nature Methods 12 (2): 115–21. https://doi.org/10.1038/nmeth.3252.

Yan, Feng, David R Powell, David J Curtis, and Nicholas C Wong. 2020. “From Reads to Insight: A Hitchhiker’s Guide to ATAC-seq Data Analysis.” Genome Biology 21 (1): 22. https://doi.org/10.1186/s13059-020-1929-3.

Resources

R programming

• R for Data Science

  An online book and comprehensive guide to data science with R by Hadley Wickham and Garrett Grolemund.

Bioconductor

• Orchestrating Single-Cell Analysis with Bioconductor

  An online book and comprehensive guide to single-cell analysis with Bioconductor.

• Orchestrating Spatially-Resolved Transcriptomics Analysis with Bioconductor

  Ths online book is a bit more of a work-in-progress and presents a guide to spatially-resolved transcriptomics analysis with Bioconductor.

Machine learning

• Workshop on Machine Learning in Genetics and Genomics

  A series of five talks on machine learning in genetics and genomics from the National Human Genome Research Institute (2021).