POPdemog-package: Plot Population Demographic History
In POPdemog: Plot Population Demographic History

Description Details Author(s) References Examples

Plot demographic graphs for single/multiple populations from coalescent simulation program input. This package does not check the simulation program input for correctness, but assumes the simulation program input has been validated by the simulation program. More features will be added to this package in the future, please check the 'GitHub' page for the latest updates: <https://github.com/YingZhou001/POPdemog>.

This package contains functions to visualize the population demographic history from coalescent simulation program input. This package supports the ms, msHot, MaCS, msprime, cosi, and SCRM simulation programs. Please check the online tutorial file for the current list of supported programs.

The input of the program is a file or string containing the simulation program commands(for ms, msa, msHot, and MaCS), or the parameter file (for Cosi), or a conversion of the program commands into ms format(for msprime). The input file or string should only contain one demographic model.

Once the input file or string is prepared, the PlotMS function can be used to generate a plot of the demographic model or to generate parameters to pass to the PlotMMig function for displaying migrations. The visualization of migrations can be customized using the PlotMig function.

Ying Zhou <yz001@uw.edu>

ms: Hudson, R. R. "Generating Samples under a Wright-Fisher Neutral Model of Genetic Variation." Bioinformatics 18.2 (2002): 337-38.

msHot: Hellenthal, G., and M. Stephens. "MsHOT: Modifying Hudson's Ms Simulator to Incorporate Crossover and Gene Conversion Hotspots." Bioinformatics 23.4 (2006): 520-21.

MaCS: Chen, G. K., P. Marjoram, and J. D. Wall. "Fast and Flexible Simulation of DNA Sequence Data." Genome Research 19.1 (2008): 136-42.

Cosi: Shlyakhter, Ilya, Pardis C. Sabeti, and Stephen F. Schaffner. "Cosi2: An Efficient Simulator of Exact and Approximate Coalescent with Selection | Bioinformatics | Oxford Academic." OUP Academic. Oxford University Press, 22 Aug. 2014.

msprime: Jerome Kelleher, Alison M Etheridge and Gilean McVean, "Efficient Coalescent Simulation and Genealogical Analysis for Large Sample Sizes", PLoS Comput Biol 12(5): e1004842. doi: 10.1371/journal.pcbi.1004842. 2016.

SCRM: Paul R. Staab, Sha Zhu, Dirk Metzler and Gerton Lunter. "scrm: efficiently simulating long sequences using the approximated coalescent with recombination." Bioinformatics (2015) 31 (10): 1680-1682.

###Tennessen's standard model
"macs 2025 15000000 -i 10 -r 3.0e-04 -t 0.00069 -T -I 4 10 1006 1008 1 0 
-n 4 0.205 -n 1 58.00274 -n 2 70.041 -n 3 187.55 -eg 0.9e-10 1 482.46 
-eg 1.0e-10 2 570.18 -eg 1.1e-10 3 720.23 -em 1.2e-10 1 2 0.731 
-em 1.3e-10 2 1 0.731 -em 1.4e-10 3 1 0.2281 -em 1.5e-10 1 3 0.2281 
-em 1.6e-10 2 3 0.9094 -em 1.7e-10 3 2 0.9094 -eg 0.007 1 0 
-en 0.007001 1 1.98 -eg 0.007002 2 89.7668 -eg 0.007003 3 113.3896
-eG 0.031456 0 -en 0.031457 2 0.1412 -en 0.031458 3 0.07579
-eM 0.031459 0 -ej 0.03146 3 2 -en 0.0314601 2 0.2546
-em 0.0314602 2 1 4.386 -em 0.0314603 1 2 4.386 -eM 0.0697669 0
-ej 0.069767 2 1 -en 0.0697671 1 1.98 -en 0.2025 1 1 -ej 0.9575923 4 1
-em 0.06765 2 4 32 -em 0.06840 2 4 0" -> std_model_Tennessen.cmd
#plot the demographic graph
par(mfrow = c(1,2))
PlotMS(input.cmd = std_model_Tennessen.cmd, type = "macs", N4 = 10000, size.scale = "log", 
log.base = 50, inpos = c(1,4,7,9), time.scale = "log10year", 
col.pop = c("brown", "blue", "gold3", "forestgreen"), 
pops = c("AFR", "EUR", "ASIA", "ARC"), 
cex.lab = 1, cex.axis = 1, xlab = "", length.arrowtip = 0.1)
title("Demographic histoy")
PlotMS(input.cmd = std_model_Tennessen.cmd, type = "macs", N4 = 10000,
time.scale = "log10year", plot.out = FALSE, demo.out = TRUE)->out;
PlotMig(time_pt = 2, demograph_out = out$demograph_out,mig_par = out$mig_par, 
col.pop = c("brown", "blue", "gold3", "forestgreen"), size.scale = "topology");
legend("topleft", legend = c("AFR", "EUR", "ASIA", "ARC"), 
col = c("brown", "blue", "gold3", "forestgreen"), pch = 20, bty = "n")
title("Migrations at 200 years ago");


###Archaic introgrssion model
"./ms 44 1 -r 20000 50000000 -t 30000 -I 6 20 20 1 1 1 1 -en 0 1 1
-en 0 2 1 -en 0 3 1e-10 -en 0 4 1e-10 -en 0 5 1e-10 -en 0 6 1e-10
-es 0.0125 2 0.97 -en 0.02500025 7 0.25 -en 0.02500025 2 1 -ej 0.05 4 3
-ej 0.05 6 5 -en 0.05000025 3 0.25 -en 0.05000025 5 0.25 -ej 0.0500025 5 3
-en 0.050005 3 0.25 -ej 0.075 2 1 -en 0.0750025 1 1 -ej 0.1 7 3
-en 0.1000025 3 0.25 -ej 0.3 3 1 -en 0.3000025 1 1" -> test.1.ms.cmd
PlotMS(input.cmd = test.1.ms.cmd, type = "ms", N4 = 10000,
time.scale = "kyear", length.arrowtip = 0.1, inpos = c(1,2,5,4.5,5.5,6,3),
col.pop = c("brown", "blue", "forestgreen", rainbow(10)[6:9]));


###Migration model from ms.
"./ms 15 100 -t 3.0 -I 6 0 7 0 0 8 0 -m 1 2 2.5 -m 2 1 2.5 -m 2 3 2.5
-m 3 2 2.5 -m 4 5 2.5 -m 5 4 2.5 -m 5 6 2.5 -m 6 5 2.5 -em 2.0 3 4 2.5
-em 2.0 4 3 2.5" -> test.2.ms.cmd
PlotMS(input.cmd = test.2.ms.cmd, type = "ms", N4 = 10000, col.pop = "gray",
col.arrow = "black", length.arrowtip = 0.1, lwd.arrow = 2);

Read 148 items
There are  29 time events for  4  populations
read N and g, done!
read m, done!
read pos and update, done!
demographic initiation, done!
plot initiation, done!
Read 148 items
There are  29 time events for  4  populations
read N and g, done!
read m, done!
read pos and update, done!
demographic initiation, done!
plot initiation, done!
Read 100 items
There are  13 time events for  7  populations
read N and g, done!
read m, done!
read pos and update, done!
demographic initiation, done!
plot initiation, done!
Read 55 items
There are  2 time events for  6  populations
read N and g, done!
read m, done!
read pos and update, done!
demographic initiation, done!
plot initiation, done!