Goal Get started Data Add geographical coordinates Create leaflet Save the map Reason for deviation from the original This post provides the R-Code to map the 26 populations of the 1000 Genomes project.
Goal Create a map similar to the one1 on the front page of http://www.internationalgenome.org/ in a reproducible manner.
Version on internationalgenome.org
Get started Packages needed:
## accessed via :: # library(mapview) # library(readxl) # library(readr) # library(purrr) # library(tidyr) # library(forcats) library(leaflet) library(dplyr) library(ggmap) ## for geocode, devtools::install_github("dkahle/ggmap") ggmap requires a google map api key2:
What is a “project folder”? Why now? Why we tidy up: authority and incentive Challenges What I want The options Drake Getting started More Examples Resources But wait: drake does not care about messy folders What is next? When is the right time to tidy Is it worth it? Recently, I started to seriously1 think about the tidiness of data analysis project folders and the implications of tidying up.
Goal Getting it done 1. Get summary statistics Visualising associations Identify genomic region with lowest P-value 2. Extracting annotation biomaRt Learning resources Using biomaRt Quick d-tour: assembly GRCh37 or GRCh38? Extracting gene name for one SNP Extracting gene names for genomic region 3. Combining summary statistics and annotation Wouldn’t it be nice… Source In the world of genome-wide association studies (GWAS), we often get a list of genetic markers (SNPs) that seem for some reason relevant for a particular outcome.
This is a brief write-up of my satRdays Cardiff experience.
First - what is a satRday?
It is an awesome concept: attending an R conference organised by a local RUG on a Saturday.
The programme in Cardiff had parallel sessions - tough decision-making to pick between promising talks!
dplyr workshop Kathrine Tansey kept us busy with a workshop on dplyr in the morning.
💻 rstudio-cloud project
Packaging workshop Heather Turner upgraded us on packaging.