introduction to R

Monday

10.30-11.30Introduction to ROliver Davisslidesscript
11.30-12.30Vectors, arithmetic, recyclingLeo Schalkwykslidesscript
12.30-13.30Lunch
13.30-14.30Practical: Vectors, arithmetic, recyclingLeo Schalkwyk scriptsolutions
14.30-15.30Data structuresOliver Davisslidesscript
15.30-16.00Afternoon tea
16.00-17.00Practical: Data structuresLeo Schalkwyk scriptsolutions

Tuesday

10.30-11.30Reading in dataMatt Daviesslidesscript
11.30-12.30Practical: Reading in dataLeo Schalkwyk scriptsolutions
12.30-13.30Lunch
13.30-14.30GraphicsOliver Davisslidesscript
14.30-15.30Practical: GraphicsOliver Davis scriptsolutions
15.30-16.00Afternoon tea
16.00-17.00Making your own functions ILeo Schalkwykslidesscript

Wednesday

10.30-11.30Applications I: Genetic analysis using R/QTLLeo Schalkwykslidesscript
11.30-12.30Practical: Genetic analysis using R/QTLLeo Schalkwyk scriptsolutions
12.30-13.30Lunch
13.30-14.30Making your own functions IIOliver Davisslidesscript
14.30-15.30Practical: Making your own functionsOliver Davis scriptsolutions
15.30-16.00Afternoon tea
16.00-17.00Linear modellingTom Priceslidesscript

Thursday

10.30-11.30Practical: Linear modellingTom Priceslidesscriptsolutions
11.30-12.30Principal components analysisMatt Daviesslidesscript
12.30-13.30Lunch
13.30-14.30Practical: Principal components analysisMatt Davies scriptsolutions
14.30-15.30Applications II: sRNA-seq with R/BioconductorMat Davisscript
15.30-16.00Afternoon tea
16.00-17.00Practical: sRNA-seq with R/BioconductorMat Davis datasolutions

Friday

10.30-11.30Object-oriented programmingOliver Davisslidesscript
11.30-12.30Practical: Object-oriented programmingOliver Davis scriptsolutions
12.30-13.30Lunch
13.30-14.30Applications III: Machine learning using CMAMatt Daviesslidesscript
14.30-15.30Practical: Machine learning using CMAKarim Malkislidesscriptsolutions
15.30-16.00Afternoon tea
16.00-17.00DiscussionMatt Davies

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