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# analyze redrawn allele ages
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redraw_frames <- list()
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for(i in 25:34) {
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redraw <- read.table(paste("Mutations/spectral/manuscript/submit/revisions/family_redraw/TGP_10kgacounts.redraw", i, sep = ""))
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names(redraw) <- count_header
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redraw <- cbind(redraw[,mut_classes] + redraw[,complementary_classes],
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CpG = redraw$CpG, bin_age = redraw$bin_age)
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redraw_frames[[i-24]] <- make_plotframes(phasedstrictCT_model, redraw, TGPphased_boot10kga_ests)[[2]]
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}
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redraw_sexaves <- lapply(redraw_frames, "[", c("sexave"))
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redraw_sexaves <- mapply(cbind, redraw_sexaves,
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data.frame(bin_age = tgp_phased10kgaplots[[2]]$bin_age),
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SIMPLIFY = FALSE)
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redraw_ggframe <- do.call(rbind, mapply(cbind, redraw_sexaves,
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lapply(1:10, function(i) {
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data.frame(redraw_idx = rep(i, 100)) }),
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SIMPLIFY = FALSE))
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names(redraw_ggframe)[2] <- "bin_age"
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ggplot(redraw_ggframe, aes(y = sexave, x = bin_age, col = factor(redraw_idx))) +
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geom_smooth(method = "loess", se = FALSE, span = 0.65) +
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geom_smooth(data = tgp_phased10kgaplots[[2]], aes(y = sexave, x = bin_age, col = 'mean'), lwd = 1, lty = 3,
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formula = y ~ x, method = "loess", span = 0.65, se = FALSE, color = 'black') +
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geom_ribbon(data = tgp_phased10kgaplots[[2]], aes(x = bin_age, y = sexave, col = 'mean',
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ymin = sexave_lower, ymax = sexave_upper),
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alpha = 0.15, color = NA) +
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coord_cartesian(ylim = c(13.5,38.5)) + #scale_color_manual(values = rev(pal_aaas("default")(2))) +
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axis_formatting + annotation_logticks(sides = "b") +
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scale_x_log10(minor_breaks = c(1:9 * 100, 1:9 * 1000)) +
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labs(y = "generation interval (years)", x = "allele age (generations ago)") +
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theme(legend.position = "none")

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