![]() ![]() But as popular as these were with the kids were almost as unpopular as they were for parents. Sold as both Lick-m-Aid, a precursor to Fun-Dip, and the straw shapes we know, Pixy Stix established a firm hold on young sweet toots everywhere. Pix y Stix as we know them didn’t come into their own until 1952, thanks to the clever people at Sunline Inc. Talk about convenience! Why Smith swapped out a ‘t’ for a ‘z’ is a mystery, but since kids loved it, no one ever bothered to ask. That way kids had much easier access to the powdery candy they were already enjoying by the spoonful. Fish Smith realized that kids craved this sweet-tart powder straight from the package, he added a spoon and changed the name to Fruzola. Making water more exciting seemed like a great idea in itself. The original intention was that the powder be mixed into water to make a fun, kool-aid-esque drink. The history of the Stix stretches all the way back to the 1930’s to a drink mix called Frutola. But while you may know this candy on sight, do you know its sweet past? If not, read on to find out more! That distinctive straw-shaped packet of sweetness could be none other than Pixy Stix. Ggsave(paste("dxyplot_", combo$pop1], "_", combo$pop2],".You would know this sugar-bomb as soon as you saw it. Labs(x="Position of window start", y="Dxy")+ PopPlot <- ggplot(thisPop, aes(window_pos_1, avg_dxy, color=chrOrder)) + ThisPop <- subset(inp, pop1 = combo$pop1] & pop2 = combo$pop2]) # Get each unique combination of populations # Plot Dxy for each combination of populations found in the input file Scale_color_manual(values=rep(c("black","gray"),ceiling((length(chrOrder)/2))))+ Labs(x="Position of window start", y="Pi")+ Labs(title=paste("Pi for population", p))+ PopPlot <- ggplot(thisPop, aes(window_pos_1, avg_pi, color=chrOrder)) + # Saves a copy of each plot in the working directory # Plot pi for each population found in the input file Inp$chrOrder <- factor(inp$chromosome,levels=chrOrder) # Find the chromosome names and order them: first numerical order, then any non-numerical chromosomes # NOTE: this is the only line you should have to edit to run this code: # Here, we use pi and dxy output files directly from pixy. # Example R Script for simple output plots This statistic is included for the user, and not directly used in any calculations. ![]() cases where two genotypes were compared and at least one was missing). This is the denominator of avg_dxy.Ĭount_missing - The raw number of missing pairwise cross-population comparisons between all genotypes in the window (i.e. cases where two genotypes were compared and both were valid). This is the numerator of avg_dxy.Ĭount_comparisons - The raw number of non-missing pairwise cross-population comparisons between all genotypes in the window (i.e. This statistic is included for the user, and not directly used in any calculations.Ĭount_diffs - The raw number of pairwise, cross-population differences between all genotypes. No_sites - The total number of sites in the window that have at least one valid genotype in both populations. Window_pos_2 - The last position of the genomic window.Īvg_dxy - Average per site nucleotide divergence for the window. Window_pos_1 - The first position of the genomic window. Pop2 - The ID of the second population from the population file. Pop1 - The ID of the first population from the population file. cases where two genotypes were compared and at least one was missing).īetween population nucleotide divergence (dxy) ¶ This is the denominator of avg_pi.Ĭount_missing - The raw number of missing pairwise comparisons between all genotypes in the window (i.e. This is the numerator of avg_pi.Ĭount_comparisons - The raw number of non-missing pairwise comparisons between all genotypes in the window (i.e. This statistic is included for the user, and not directly used in any calculations.Ĭount_diffs - The raw number of pairwise differences between all genotypes in the window. No_sites - The total number of sites in the window that have at least one valid genotype. More specifically, pixy computes the weighted average nucleotide diversity per site for all sites in the window, where the weights are determined by the number of genotyped samples at each site. Window_pos_2 - The last position of the genomic windowĪvg_pi - Average per site nucleotide diversity for the window. Window_pos_1 - The first position of the genomic window Pop - The ID of the population from the population file Within population nucleotide diversity (pi) ¶ ![]()
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