The software panicmage simulates distributed genomes according to the Infinitely Many Genes Model and can estimate model parameters from observed data. Moreover panicmage computes a p-value for the observed gene frequency spectrum and a given genealogy in the Infinitely Many Genes Model. So far p-values for neutral evolution can be computed. In addition panicmage can account for sampling bias under neutral evolution. Given
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a proxy for the true clonal genealogy of the sample
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the gene frequency spectrum of the sample
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the sample size n
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the number of generations to the most recent common ancestor (MRCA) of the sample in millions (optional)
panicmage estimates gene gain and gene loss rates and the number of core genes according to the Infinitely Many Genes Model. In addition panicmage computes the p-value of the observed gene frequency spectrum under neutral evolution. Small p-values hint at global selective forces or population growth while very high p-values may appear if gene transfer and/or recombination occur frequently. Finally panicmage provides estimates for the following statistics in a neutral evolving population:
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the average number of genes per individual
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the average total number of genes present in 2, n, 1000 and 10000 individuals for a random clonal genealogy, resp.
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the average total number of genes present in 2 or n individuals for the given clonal genealogy, resp.
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the average number of new genes to be found in the next (n+1-th) sequenced individual
If in addition the number of generations to the MRCA is given panicmage can also estimate:
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The size of the pangenome, that is the total number of different genes present in the whole population.
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The size of the persistant pangenome, that is the total number of different genes present in at least 1% of the whole population.
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The per individual per generation gene gain rate
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The per individual per gene per generation loss rate
panicmage can be used to estimate the insertion and deletion rates of
CRISPR spacers, as outlined in @Baumdicker2018. If you intend to do so
use the spacer frequency spectrum instead of the gene frequency spectrum
and use the -z option.
panicmage is written in C and C++ and designed for Linux. Currently there is no manual for Windows or Mac.
For panicmage the GNU Scientific Library (GSL) – development package (libgsl0-dev) is needed, please install it, e.g. by typing
sudo apt-get install libgsl0-dev
In order to install panicmage extract panicmage.zip to any directory, e.g. by typing
unzip panicmage.zip
there is a binary file panicmage which might already work for your system. Otherwise compile it again with:
g++ panicmage.c -lm -lgsl -lgslcblas -o panicmage
In addition the flag -std=c++11 is required for gcc < 6.0. You may now run panicmage from commandline. Type
./panicmage
to see basic usage.
panicmage requires at least 3 input parameters which have to be prompted in the correct order.
./panicmage [TREEFILE] [GFS\_FILE] [INT] ... [OPTIONS]
[TREEFILE] Has to be the tree your analysis is based on and represents the clonal genealogy of your sample. panicmage accepts only files in Newick format. For more infos on the Newick format have a look at http://en.wikipedia.org/wiki/Newick_format. The tree must contain the distances between the nodes and should be rooted. Note that only ultrametric bifurcating trees will give meaningful results! I.e. the distances between each pair of individuals have to equal. However panicmage does not check whether your tree is ultrametric, so be careful. The names/ID’s for the individuals can be any string or integer, but 1,...,no. of individuals. It is recommend to use ID’s between 1000 and 9999. A simple tree for 3 individuals might look like this: (101:0.6,(103:0.22,102:0.22):0.38);
[GFS_FILE] This file should contain the gene frequency data. The correct format is a simple text file which contains the number of genes per frequency class seperated by whitespaces. To be precise, the first number has to be the total number of unique genes in the population. The second number has to be the number of genes which are present in exactly two individuals. And so on such that the last number is the number of genes present in all individuals (i.e. the number of core genes).
[INT] Enter the number of individuals in your sample. This number should equal the number of leafs in your treefile!
optional option
-g [FLOAT] Set the number of generations up to the most recent common ancestor (MRCA) for your sample. Optional parameter but, enables panicmage to estimate several statistics of interest (e.g. total pangenome size, per generation gene gain and loss rates). Number is treated in millions, so “-g 1.234” equals 1234000 generations up to the MRCA.
For further options and instructions have a look at the ReadMe_Panicmage.pdf and the ReadMe_Panicmage.txt files.