kgturner

#Extract climate data from WorldClim.org tiles for several locations and make data table
#Kathryn Turner Sept 16, 2013
 
#download and unzip all relevant WorldClim geoTIFF files into a single directory.
#I used the highest resolution (~1km2), but should work for other resolutions too.

#load packages: raster, rgdal, foreach
library(rgdal)
library(raster)
library(foreach)

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#Download occurence data from GBIF - for few to many spp.
#3/25/2019 KG Turner with assistance from S. Chamberlain, rOpenSci.org

#Register at gbif.org. You will need to use this email address, user name, and password in the following script.
#NB: DON'T COMMIT YOUR PASSWORDS.

# R version 3.5.3 (2019-03-11)

library(rgbif) #1.2.0

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#generate random number sets with limited overlap
#3/28/2018
#with em-bellis

####generate random integers from a pool####
#from 1-60, sample 10
sample.int(60, 10) 
#[1] 34 42 45 54  3  5 20 25 53 40
#such as IDs of populations or individuals from a list

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#Functions to squish groups of columns together
#Kathryn Turner Sept 20, 2013
#With help from Andrew MacDonald @polesasunder

#given data that have many NAs and non-overlapping values
#across several columns, with similarly named columns within a group
> head(clim)
      alt_07.tif alt_11.tif alt_12.tif alt_15.tif alt_16.tif alt_17.tif bio1_07.tif bio1_11.tif bio1_12.tif bio1_15.tif bio1_16.tif bio1_17.tif bio10_07.tif
BG001         NA         NA         NA         NA         61         NA          NA          NA          NA          NA         121          NA           NA
CA001         NA         24         NA         NA         NA         NA          NA         100          NA          NA          NA          NA           NA

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#####Minima.mer.func.R#####
#Kathryn Turner June 21, 2013

#Given an output kmer counting histogram table from jellyfish,
#find two minima around a peak

#input table from jellyfish
dat <- read.table("data.from.jellyfish.hist", head=T)
head(dat)
frequency multiplicity

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#ModernMapEurasia.r
#Kathryn Turner, June 17, 2013
#With extensive help from Andy South

#to create a reprojected map of the Northern Hemisphere
#color code countries for range
#and add collection sites
#in a Lambert azimuthal equal area projection, with the North Pole in the center 

library(rgdal) # Commands for reprojecting the vector data.

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#latitude and longitude
#convert types and add to design files

popgps<- read.table(file.choose(), header=T, sep=",",quote='"', row.names=1) #csv of pop, lat, long
popgps<-popgps[,1:3]
popgps$Longitude<-as.character(popgps$Longitude)
popgps$Latitude<-as.character(popgps$Latitude)

#add two pops to df
popgps["SAND",1]<-"48:12.055"

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