New year, new site

..go

Nicholas Owen

Jan 31, 2022 2 min read code

With my recent involvement with the UK Reproducibility Network, and continued use of GitHub for code sharing, I thought it was long past due that I create a quick site to provide access to the code, analysis and associated data for the projects I am working with. The Wellcome Trust funds my position at the Institute of Ophthalmology (UCL) in the Ocular Genomics and Therapeutics lab of Professor Mariya Mosajee, and with the Trust’s supportive attitude to open research I will document some of the projects and code that we are currently involved with.

# Welcome
return("Hello World")

require(stats)

#' Compute different averages
#'
#' @param x \code{numeric} vector of sample data
#' @param type \code{character} vector of length 1 specifying the average type
#' @return \code{centre} returns the sample average according to the chosen method.
#' @examples
#' centre(rcauchy(10), "mean")
#' @export
centre <- function(x, type) {
  switch(type,
         mean = mean(x),
         median = median(x),
         trimmed = mean(x, trim = .1))
}
x <- rcauchy(10)
centre(x, "mean")

library(ggplot2)

models <- tibble::tribble(
  ~model_name,    ~ formula,
  "length-width", Sepal.Length ~ Petal.Width + Petal.Length,
  "interaction",  Sepal.Length ~ Petal.Width * Petal.Length
)

iris %>% 
  nest_by(Species) %>% 
  left_join(models, by = character()) %>% 
  rowwise(Species, model_name) %>% 
  mutate(model = list(lm(formula, data = data))) %>% 
  summarise(broom::glance(model))
#> `summarise()` regrouping output by 'Species', 'model_name' (override with `.groups` argument)
#> # A tibble: 6 x 13
#> # Groups:   Species, model_name [6]
#>   Species model_name r.squared adj.r.squared sigma statistic  p.value    df
#>   <fct>   <chr>          <dbl>         <dbl> <dbl>     <dbl>    <dbl> <int>
#> 1 setosa  length-wi…     0.112        0.0739 0.339      2.96 6.18e- 2     3
#> 2 setosa  interacti…     0.133        0.0760 0.339      2.34 8.54e- 2     4
#> 3 versic… length-wi…     0.574        0.556  0.344     31.7  1.92e- 9     3
#> 4 versic… interacti…     0.577        0.549  0.347     20.9  1.11e- 8     4
#> 5 virgin… length-wi…     0.747        0.736  0.327     69.3  9.50e-15     3
#> 6 virgin… interacti…     0.757        0.741  0.323     47.8  3.54e-14     4
#> # … with 5 more variables: logLik <dbl>, AIC <dbl>, BIC <dbl>, deviance <dbl>,
#> #   df.residual <int>

reproducibility R open code bioinformatics

Nicholas Owen

Research Fellow and Bioinformatician

My interests include rare disease translational research using ‘omics analysis.