coleoguy

library(shiny)
# I like this color pallete much more than the base options
library(viridis)
shinyServer(function(input, output) {
  # this is the actual brownian motion simulation
  x <- reactive({
    # insure reproducability
    set.seed <- input$seed.val
    replicate(input$reps, cumsum(rnorm(input$gens)))
  })

coleoguy

## plotting simulated data
require("vcd")
colnames(simresult) <- c("Root", "XY", "XO", "Xyp")
simresult <- as.data.frame(simresult)
colors <- c("black","red","green", "orange")    #This sets up a vector of colors
ternaryplot(                                    #This is the actual plotting of our data
  simresult[,2:4],                              #Here I provide the file and columns to plot
  pch = 20,                                     #This is choosing the shape of data points (simple circle here)
  cex = .5,                                     #This is the size of the data points
  col = colors[as.numeric(simresult$Root)],     #Telling it to color the points

coleoguy

## non-phylogenetic approach to simulating data
simresult <- matrix(1,200,4)
set.seed(4)
simresult[,2] <- sample(1:498, size=200)
for(i in 1:200){
  simresult[i,3] <- sample(1:(499 - simresult[i,2]), size=1)
  simresult[i,4] <- sample(1:(500 - (simresult[i,2] + simresult[i,3])), size=1)
  simresult[i,1] <- sample(2:4, size=1, prob = c(simresult[i,2], 
                                                 simresult[i,3], 

coleoguy

## phylogenetic approach to simulating data
library(geiger)
tree <- sim.bdtree(b=1, d=.4, stop=c("taxa", "time"), n=200, seed=0, extinct=T)
tree <- drop.extinct(tree)
q <- list(rbind(c(-.06, .05, .01), c(.09, -.1, .01), c(.01, .01, -.02)))
simresult <- matrix(1,200,4)
for(i in 1:200){
  sim.root <- sample(1:3, prob=c(.55,.35,.1), size=1)
  phylosim <- sim.char(phy=tree, model="discrete", par=q, 
                       root=sim.root)

coleoguy

## simple function to take a line of text and return a version of 
## this text that has been encoded into DNA.  This function makes
## use of a couple of codons that are normally stop codons but in
## certain organisms have been coopted to code for unusual amino
## acids.  This is how we are able to expand the alphabet to include
## O and U


wordTOcodons <- function(x){
  table <- matrix(c("START", 'A', 'R', 'N', 'D', 'C', 'Q', 'E', 'G', 'H', 'I',

coleoguy

slideFunct <- function(data, window, step){
  total <- length(data)
  spots <- seq(from = 1, to = (total - window + 1), by = step)
  result <- vector(length = length(spots))
  for(i in 1:length(spots)){
    result[i] <- mean(data[spots[i]:(spots[i] + window - 1)])
  }
  return(result)
}

coleoguy

data <- c(runif(100000, min=0, max=.1),runif(100000, min=.05, max=.1),runif(10000, min=.05, max=1), runif(100000, min=0, max=.2))

coleoguy

# to construct database from an assembly in the file
# conf.scaf.fa run this in the terminal
# it will create a blast database call confscaf

makeblastdb -in conf.scaf.fa -dbtype nucl -out confscaf

# next we want to blast our large exons against this db
blastn -query=/outputs/300+bpExons.fa -db=/blastDB/confscaf -outfmt='6 qseqid qstart sseqid sstart qlen length pident' -max_target_seqs=2 -out=info

# this produces the lookup table that we can then use to analyze the degree of synteny conservation

coleoguy

setwd("~/Desktop/retrogenes/data/")
gff <- read.csv("exons.csv", header = F, as.is=T) #This is a parsed GFF3 file that contains the lines for exons

# lets get big ones >300 bp

gff <- gff[gff[, 3] - gff[, 2] > 300, ]
setwd("~/Desktop/retrogenes/data/chromosomes") #This is the directory that contains the chromosomes of the genome

library(ape)
seq <- name <- list()

coleoguy

from Bio import SeqIO  # to deal with the fast files

# lets pull in our exon table
datafile = open('exons.csv', 'r')
data = []
for row in datafile:
    data.append(row.strip().split(','))

# now lets start the process of creating all of our exon-exon sequences
# by first creating a list that has the name we want to assign and the LG and