22100 c22100 https://teaching.healthtech.dtu.dk/22100/index.php/22100_-_R_for_Bio_Data_Science MediaWiki 1.41.0 first-letter Media Special Talk User User talk 22100 22100 talk File File talk MediaWiki MediaWiki talk Template Template talk Help Help talk Category Category talk 0 7 12 11 2024-03-06T12:09:48Z WikiSysop 1 /* Previous Versions of the Course */ 12 wikitext text/x-wiki [[File:R_for_bio_data_Science_text_logo_w_dna.png|right|250px]] [[File:R_for_bio_data_science_hex_logo_quadratic_small.png|right|250px]] This is the course website for the [https://kurser.dtu.dk/course/22100 ''R for Bio Data Science''] course at [https://www.healthtech.dtu.dk/english/research/digital-health-and-biological-modelling/section-bioinformatics section for Bioinformatics], Technical University of Denmark. If you wish to take the course without being enrolled at DTU, [https://www.dtu.dk/uddannelse/efteruddannelse/kurser/enkeltfagskurser please click here for more information]. = Course Programme = * [https://learn.inside.dtu.dk/d2l/home/60275 Spring 2021] = About = * '''Course responsible''': [https://www.dtu.dk/english/service/phonebook/person?id=22554&cpid=257113&tab=2&qt=dtupublicationquery Leon Eyrich Jessen] * '''Schedule''': [https://kurser.dtu.dk/schedule/22100 Spring F1A], i.e. on Mondays 8 - 12 * '''Location''': Lyngby Campus, see course version above * '''Exam''': [https://www.dtu.dk/english/education/examination-timetable See DTU Examination timetable] * '''Text book''': [http://r4ds.had.co.nz/ R for Data Science by Garrett Grolemund and Hadley Wickham] * '''Course Description''': For full course description, please see the [https://kurser.dtu.dk/course/22100 DTU Course Base] * '''Official GitHub site''': [https://github.com/rforbiodatascience https://github.com/rforbiodatascience] = Collection of Additional Ressources = ''Open source books'' Please, feel free to explore the following books: * [https://rstudio-education.github.io/hopr/ Hands-On Programming with R by Garrett Grolemund] * [https://moderndive.com/ Statistical Inference via Data Science - A moderndive into R and the tidyverse by Chester Ismay and Albert Y. Kim] * [https://rafalab.github.io/dsbook/ Introduction to Data Science, Data Analysis and Prediction Algorithms with R by Rafael A. Irizarry] * [https://mastering-shiny.org/ Mastering Shiny by Hadley Wickham] * [http://faculty.marshall.usc.edu/gareth-james/ISL/ An Introduction to Statistical Learning with Applications in R by Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani] * [https://stat545.com/ STAT 545 - Data wrangling, exploration, and analysis with R by Jenny Bryan] ''Software Links'' * [https://www.r-project.org/ The R Project for Statistical Computing] * [https://rstudio.com/products/rstudio/download/?utm_source=downloadrstudio RStudio - Open Source and Enterprise-ready professional software for R] * [https://www.tidyverse.org/ Tidyverse website] ''Some Useful Links'' * [http://www.stat.columbia.edu/~tzheng/files/Rcolor.pdf R colour guide by Tian Zheng] * [https://style.tidyverse.org/ The tidyverse style guide - By Hadley Wickham] * [https://rstudio.cloud/learn/primers RStudio Primers - Learn data science basics with the interactive tutorials] * [https://style.tidyverse.org/documentation.html The tidyverse style guide] * [http://swirlstats.com/ swirl - Learn R, in R] * [https://www.rstudio.com/resources/cheatsheets/ RStudio Cheat Sheets] * [https://community.rstudio.com/ RStudio Community - Stuck? Ask a question and get help moving on] * [https://garrettgman.github.io/rmarkdown/ioslides_presentation_format.html Presentations with ioslides] * [https://rafalab.github.io/pages/harvardx.html HarvardX Biomedical Data Science Open Online Training] * [https://www.youtube.com/playlist?list=PLzH6n4zXuckpfMu_4Ff8E7Z1behQks5ba Data Analysis Playlist] ''On Data Science'' * [https://hdsr.mitpress.mit.edu/pub/gg6swfqh/ The Role of Academia in Data Science Education] ''Guides on Good Data Practices'' * [https://www.britishecologicalsociety.org/wp-content/uploads/2017/12/guide-to-reproducible-code.pdf A Guide to Reproducible Code by the British Ecology Society] * [https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1000424 A Quick Guide to Organizing Computational Biology Projects] * [https://blog.datawrapper.de/beautifulcolors/ How to pick more beautiful colors for your data visualizations] ''Suggested Data Sources'' * [https://github.com/ramhiser/datamicroarray datamicroarray: Small-sample, high-dimensional microarray data] * [http://userweb.eng.gla.ac.uk/umer.ijaz/bioinformatics/ecological.html Assessment of the influence of intrinsic environmental and geographical factors on the bacterial ecology of pit latrines] * [https://support.10xgenomics.com/single-cell-vdj/datasets A New Way of Exploring Immunity - Linking Highly Multiplexed Antigen Recognition to Immune Repertoire and Phenotype] * [https://datasetsearch.research.google.com/ Google Dataset Search] * [http://biostat.mc.vanderbilt.edu/wiki/Main/DataSets Vanderbilt Biostatistics DataSets] * [https://github.com/CSSEGISandData/COVID-19 2019 Novel Coronavirus COVID-19 (2019-nCoV) Data Repository by Johns Hopkins CSSE] * [http://covid19.bigomics.ch/ BigOmics Analytics - Let's fight coronavirus infections together!] = Previous Versions of the Course = * [[22100_-_Course_Programme_Spring_2020 Spring 2020]] olh8fkgzgrnosls858modhlvjjquk38