| Next changeset 1:4a5c94d1d8bb (2022-08-31) |
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Commit message:
"planemo upload for repository https://github.com/kirstvh/MultiplexCrisprDOE commit b6c1b1860eee82b06ed4a592d1f9eee6886be318-dirty" |
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added:
MultiplexCrisprDOE.jl README.rst main.jl mcdoe.xml report.jmd test-data/example_data.xlsx test-data/test_ccp_report.html test-data/test_countKOs.xlsx test-data/test_gRNA_edit.xlsx test-data/test_gRNA_reads.xlsx test-data/test_ged_report.html test-data/test_gfd_report.html test-data/test_sim_report.html |
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| diff -r 000000000000 -r cc0957c46408 MultiplexCrisprDOE.jl --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/MultiplexCrisprDOE.jl Thu May 12 17:39:18 2022 +0000 |
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| b'@@ -0,0 +1,1048 @@\n+"""\n+ gRNA_frequency_distribution(m, \n+ sd, \n+ l, \n+ u, \n+ n_gRNA_total; \n+ normalize = true, \n+ visualize = false)\n+\n+Generates vector with frequencies in the combinatorial gRNA/Cas9 construct library for all gRNAs\n+\n+***INPUT***\n+m: the average abundance of the gRNAs (in terms of absolute or relative frequency)\n+sd: the standard deviation on the gRNA abundances (in terms of absolute or relative frequency)\n+l: minimal gRNA abundance (in terms of absolute or relative frequency)\n+u: maximal gRNA abundance (in terms of absolute or relative frequency)\n+n_gRNA_total: the total number of gRNAs in the experiment\n+normalize: if set to "true", the gRNA abundances (absolute frequencies) are converted into relative frequencies\n+visualize: if set to "true", a histogram of all gRNA abundances is plotted\n+\n+***OUTPUT***\n+p_gRNA_freq: vector with frequencies for all gRNAs in the construct library\n+"""\n+function gRNA_frequency_distribution(m, \n+ sd, \n+ l, \n+ u, \n+ n_gRNA_total; \n+ normalize = true, \n+ visualize = false)\n+\n+ d_gRNA_freq = truncated(Normal(m, sd), l, u) # gRNA frequency distribution\n+ p_gRNA_freq = collect(rand(d_gRNA_freq, n_gRNA_total)) # sample gRNA frequencies from distribution\n+ \n+ if normalize # convert into relative frequencies\n+ p_gRNA_freq /= sum(p_gRNA_freq)\n+ end\n+\n+ if visualize\n+ return histogram(p_gRNA_freq, label="", \n+ xlabel="Number of reads per gRNA", \n+ linecolor="white", \n+ normalize=:probability,\n+ xtickfontsize=10,ytickfontsize=10,\n+ color=:mediumturquoise, size=(600,350), bins = 25,\n+ ylabel="Relative frequency", \n+ title="gRNA frequency distribution")\n+ else\n+ return p_gRNA_freq\n+ end\n+end\n+\n+"""\n+ gRNA_edit_distribution(f_act, \n+ \xcf\xb5_edit_act, \n+ \xcf\xb5_edit_inact, \n+ sd_act, \n+ n_gRNA_total; \n+ visualize = false) \n+\n+Generates vector with genome editing efficiencies for all the gRNAs in the experiment. \n+\n+***INPUT***\n+f_act: fraction of all gRNAs that is active\n+\xcf\xb5_edit_act: Average genome editing efficiency for active gRNAs - mean of the genome editing efficiency distribution for active gRNAs\n+\xcf\xb5_edit_inact: Average genome editing efficiency for inactive gRNAs - mean of the genome editing efficiency distribution for inactive gRNAs\n+sd_act: standard deviation of the genome editing efficiency distributions for active and inactive gRNAs\n+n_gRNA_total: the total number of gRNAs in the experiment\n+visualize: if set to "true", a histogram of all genome editing efficiency is plotted\n+\n+***OUTPUT***\n+p_gRNA_edit: vector with genome editing efficiencies for all gRNAs\n+"""\n+function gRNA_edit_distribution(f_act, \xcf\xb5_edit_act, \xcf\xb5_edit_inact, sd_act, n_gRNA_total; visualize=false) \n+ d_act = Binomial(1, f_act) # there is a probability f_act that a gRNA is active\n+ d_high_act = truncated(Normal(\xcf\xb5_edit_act, sd_act), 0.01, 1) # average genome editing efficiency for active gRNAs is equal to \xcf\xb5_edit_act\n+ d_low_act = truncated(Normal(\xcf\xb5_edit_inact, sd_act), 0.01, 1) # average genome editing efficiency for inactive gRNAs is equal to \xcf\xb5_edit_inact\n+ p_gRNA_edit = zeros(n_gRNA_total) # initialize vector with genome editing efficiencies for gRNAs\n+ \n+ for i in 1:n_gRNA_total\n+ if rand(d_act, 1) == [1] # gRNA is active\n+ p_gRNA_edit[i] = rand(d_high_act, 1)[1]\n+ else # gRNA is inactive\n+ p_gRNA_ed'..b' p_gRNA_freq, \n+ p_gRNA_edit, \n+ \xcf\xb5_KO)\n+\n+Computes the probability of full coverage of all triple combinations of gene knockouts (Px,3) for an experiment with given plant library size using BioCCP\n+\n+***INPUT***\n+x: number of target genes in the experiment\n+N: plant library size\n+g: number of gRNAs designed per target gene\n+r: number of gRNA sequences per combinatorial gRNA/Cas construct\n+n_gRNA_total: total number of gRNAs in the experiment\n+p_gRNA_freq: vector with relative frequencies for all gRNAs in the construct library (normalized!)\n+p_gRNA_edit: vector with genome editing efficiencies for all gRNAs \n+\xcf\xb5_KO: global knockout efficiency; fraction of mutations leading to effective gene knockout\n+ \n+***OUTPUT***\n+P\xe2\x82\x93\xe2\x82\x83: probability of full coverage of all triple combinations of gene knockouts\n+"""\n+function BioCCP_P\xe2\x82\x93\xe2\x82\x83(x, \n+ N,\n+ g, \n+ r, \n+ n_gRNA_total, \n+ p_gRNA_freq, \n+ p_gRNA_edit, \n+ \xcf\xb5_KO)\n+ \n+ # how many triple combinations of gRNAs\n+ ind_combinations_gRNA = collect(combinations(1:n_gRNA_total, 3))\n+ n_combinations_gRNA = length(ind_combinations_gRNA)\n+ \n+ # calculate probability and activity of triple gRNA combinations\n+ p_combinations_gRNA_library = zeros(n_combinations_gRNA)\n+ p_combinations_gRNA_act = zeros(n_combinations_gRNA)\n+ for i in 1:n_combinations_gRNA\n+ p_combinations_gRNA_library[i] = p_gRNA_freq[ind_combinations_gRNA[i][1]] * p_gRNA_freq[ind_combinations_gRNA[i][2]] * p_gRNA_freq[ind_combinations_gRNA[i][3]]\n+ p_combinations_gRNA_act[i] = p_gRNA_edit[ind_combinations_gRNA[i][1]] * p_gRNA_edit[ind_combinations_gRNA[i][2]] * p_gRNA_edit[ind_combinations_gRNA[i][3]]\n+ end\n+ \n+ # normalize probability gRNA combinations\n+ p_combinations_gRNA_library /= sum(p_combinations_gRNA_library)\n+\n+ # select triple gRNA combinations of which each component codes for different gene (goal is to study combinations of knockouts in different genes)\n+ p_combinations_gRNA_library_interest = []\n+ p_combinations_gRNA_act_interest = []\n+ ind_combinations_gRNA_interest = []\n+ for i in 1:n_combinations_gRNA\n+ if ceil(ind_combinations_gRNA[i][1]/g) != ceil(ind_combinations_gRNA[i][2]/g) && ceil(ind_combinations_gRNA[i][1]/g) != ceil(ind_combinations_gRNA[i][3]/g) && ceil(ind_combinations_gRNA[i][3]/g) != ceil(ind_combinations_gRNA[i][2]/g)\n+ push!(p_combinations_gRNA_library_interest, p_combinations_gRNA_library[i])\n+ push!(p_combinations_gRNA_act_interest, p_combinations_gRNA_act[i])\n+ push!(ind_combinations_gRNA_interest, ind_combinations_gRNA[i])\n+ end\n+ end\n+ \n+ n_combinations_gRNA_interest = length(p_combinations_gRNA_library_interest)\n+ p_combinations_gRNA = p_combinations_gRNA_library_interest .* p_combinations_gRNA_act_interest * \xcf\xb5_KO^3\n+\n+ # sum up probabilities or gRNA combinations for corresponding gene knockout combinations\n+ p_genes_matrix = zeros(x, x, x)\n+ for i in 1:n_combinations_gRNA_interest\n+ gene1 = Int(ceil(ind_combinations_gRNA_interest[i][1]/g))\n+ gene2 = Int(ceil(ind_combinations_gRNA_interest[i][2]/g))\n+ gene3 = Int(ceil(ind_combinations_gRNA_interest[i][3]/g))\n+ p_genes_matrix[gene1, gene2, gene3] += p_combinations_gRNA[i]\n+ end\n+ \n+ combinations_genes = collect(combinations(1:x, 3))\n+ p_genes = []\n+ for combination in combinations_genes\n+ push!(p_genes, p_genes_matrix[combination[1], combination[2], combination[3]])\n+ end\n+ \n+ n_combinations_genes = length(p_genes)\n+ combinations_pp = length(collect(combinations(1:r, 3)))\n+ \n+ # Apply BioCCP function\n+ P\xe2\x82\x93\xe2\x82\x83 = success_probability(n_combinations_genes, N; p=p_genes, r=combinations_pp, normalize=false)\n+\n+ return P\xe2\x82\x93\xe2\x82\x83 \n+end\n+ \n+ \n\\ No newline at end of file\n' |
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| diff -r 000000000000 -r cc0957c46408 README.rst --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/README.rst Thu May 12 17:39:18 2022 +0000 |
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| @@ -0,0 +1,4 @@ +MultiplexCrisprDOE +================== +provides simulation- and BioCCP-based approaches for computing the minimal plant library size +that guarantees full combinatorial coverage (and other relevant statistics) for multiplex CRISPR/Cas experiments in plants. \ No newline at end of file |
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| diff -r 000000000000 -r cc0957c46408 main.jl --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/main.jl Thu May 12 17:39:18 2022 +0000 |
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| b'@@ -0,0 +1,612 @@\n+using Pkg\n+Pkg.add("Plots");\n+Pkg.add("Distributions");\n+Pkg.add("LinearAlgebra");\n+Pkg.add("Combinatorics");\n+Pkg.add("BioCCP");\n+Pkg.add("ArgParse");\n+Pkg.add("XLSX");\n+Pkg.add("DataFrames");\n+Pkg.add("Weave");\n+Pkg.add("DataStructures");\n+Pkg.add("PrettyTables");\n+\n+using Random\n+using Plots\n+using Distributions\n+using LinearAlgebra\n+using Combinatorics\n+using BioCCP\n+using ArgParse\n+using XLSX\n+using DataFrames\n+using Weave\n+using DataStructures\n+using PrettyTables\n+\n+global current_dir = pwd()\n+include("MultiplexCrisprDOE.jl");\n+\n+function main(args)\n+\n+ aps = ArgParseSettings("MultiplexCrisprDOE")\n+\n+ @add_arg_table! aps begin\n+ "gfd" #, "gRNA_freq_dist"\n+ action = :command # adds a command which will be read from an argument\n+ help = "gRNA/Cas9 frequencies"\n+ "ged" #, "gRNA_edit_dist" \n+ action = :command\n+ help = "gRNA/Cas9 editing efficiencies"\n+ "sim" # simulation\n+ action = :command\n+ help = "simulation-based approaches for computing the minimal plant library size that guarantees full combinatorial coverage (and other relevant statistics)"\n+ "ccp" # bioccp\n+ action = :command\n+ help = "BioCCP-based approaches for computing the minimal plant library size that guarantees full combinatorial coverage (and other relevant statistics)"\n+ end\n+\n+ @add_arg_table! aps["gfd"] begin # add command arg_table: same as usual, but invoked on s["grna"]\n+ "m"\n+ arg_type = Int\n+ help = "plant library size"\n+ "sd"\n+ arg_type = Int\n+ help = "the standard deviation on the gRNA abundances (in terms of absolute or relative frequency)"\n+ "l"\n+ arg_type = Int\n+ help = "minimal gRNA abundance (in terms of absolute or relative frequency)"\n+ "u"\n+ arg_type = Int\n+ help = "maximal gRNA abundance (in terms of absolute or relative frequency)"\n+ "n" #, "--n_gRNA_total"\n+ arg_type = Int\n+ help = "the total number of gRNAs in the experiment"\n+ "--normalize"\n+ action = :store_true\n+ # arg_type = Bool\n+ # default = true\n+ help = "if provided, the gRNA abundances (absolute frequencies) are converted into relative frequencies"\n+ "--visualize"\n+ action = :store_true\n+ # arg_type = Bool\n+ # default = false\n+ help = "if provided, a histogram of all gRNA abundances is plotted"\n+ "--out_file"\n+ arg_type = String\n+ default = "gRNA_reads"\n+ help = "Output excel file prefix"\n+ end\n+\n+ @add_arg_table! aps["ged"] begin # add command arg_table: same as usual, but invoked on s["grna"]\n+ "f_act"\n+ arg_type = Float16\n+ help = "fraction of all gRNAs that is active"\n+ "eps_edit_act"\n+ arg_type = Float16\n+ help = "Average genome editing efficiency for active gRNAs - mean of the genome editing efficiency distribution for active gRNAs"\n+ "eps_edit_inact"\n+ arg_type = Float16\n+ help = "Average genome editing efficiency for inactive gRNAs - mean of the genome editing efficiency distribution for inactive gRNAs"\n+ "sd_act"\n+ arg_type = Float16\n+ help = "standard deviation of the genome editing efficiency distributions for active and inactive gRNAs"\n+ "n_gRNA_total"\n+ arg_type = Int\n+ help = "the total number of gRNAs in the experiment"\n+ "--visualize"\n+ action = :store_true\n+ # arg_type = Bool\n+ # default = false\n+ help = "if provided a histogram of all genome editing efficiency is plotted"\n+ "--out_file"\n+ arg_type = String\n+ default = "gRNA_edit"\n+ help = "Output excel file prefix"\n+ end\n+ \n+'..b' end\n+ end\n+ # E_sim, sd_sim = BioCCP_\xce\xb3\xe2\x82\x93\xe2\x82\x82(x, N, g, r, t, f, e, E)\n+ out_dict["E_cov"] = exp_cov\n+ out_dict["N_95"] = N_95\n+ out_dict["pls"] = plant_library_sizes\n+\n+ elseif command_args["M"] == 9\n+ tool_info["mode"] = "BioCCP_\xce\xb3x3"\n+ tool_info["mode_description"] = "Computes the expected coverage of all "*\n+ "triple combinations of gene knockouts (E[\xce\xb3x,3]) for an experiment with "*\n+ "given plant library size using BioCCP"\n+\n+ if s != nothing && MN != nothing\n+ plant_library_sizes = N:s:MN\n+ else\n+ plant_library_sizes = N\n+ end\n+ exp_cov = []\n+ global N_95 = nothing\n+ for N in plant_library_sizes \n+ E_cov = BioCCP_\xce\xb3\xe2\x82\x93\xe2\x82\x83(x, N, g, r, t, f, e, E)\n+ push!(exp_cov, E_cov)\n+ if E_cov < 0.95\n+ N_95 = N\n+ end\n+ end\n+ # E_sim, sd_sim = BioCCP_\xce\xb3\xe2\x82\x93\xe2\x82\x83(x, N, g, r, t, f, e, E)\n+ out_dict["E_cov"] = exp_cov\n+ out_dict["N_95"] = N_95\n+ out_dict["pls"] = plant_library_sizes\n+\n+ end\n+ end\n+ end\n+\n+ println(parsed_args)\n+ println("Parsed args:")\n+ for (key,val) in parsed_args\n+ println(" $key => $(repr(val))")\n+ end\n+ println()\n+ println("Command: ", parsed_args["%COMMAND%"])\n+ # h1 = histogram(grna_dict["p_gRNA_reads"], label="", \n+ # xlabel="Number of reads per gRNA", \n+ # linecolor="white", \n+ # normalize=:probability,\n+ # xtickfontsize=10,ytickfontsize=10,\n+ # color=:mediumturquoise, size=(600,350), bins = 25,\n+ # ylabel="Relative frequency", \n+ # title="gRNA frequency distribution")\n+ \n+ # h2 = histogram(grna_dict["p_gRNA_edit"], \n+ # normalize = :probability,\n+ # linecolor = "white",\n+ # label="", \n+ # color=:turquoise4,\n+ # xtickfontsize=10,ytickfontsize=10, xlim = (0, 1),\n+ # xticks=(0:0.1:1),\n+ # bins = 150,\n+ # xlabel="gRNA editing efficiency", \n+ # ylabel="Relative frequency", \n+ # title="gRNA genome editing effiency distribution")\n+\n+ # p_plot = plot(plant_library_sizes, P\xe2\x82\x93\xe2\x82\x82, label="P\xe2\x82\x93\xe2\x82\x82", \n+ # title="Probability of full combinatorial coverage with respect to plant library size",\n+ # xlabel="N", ylabel="P\xe2\x82\x93\xe2\x82\x96", \n+ # xticks = (0:500:50000, string.(0:500:50000)),\n+ # size=(900,400), color=:turquoise4, linewidth=2)\n+ # hline!([0.95], linestyle=:dash, color=:grey, label="P\xe2\x82\x93\xe2\x82\x96 = 0.95", legend=:bottomright)\n+\n+ # exp_plot = plot(plant_library_sizes, expected_\xce\xb3\xe2\x82\x93\xe2\x82\x82,\n+ # label="E[\xce\xb3\xe2\x82\x93\xe2\x82\x82]", title="Expected combinatorial coverage w.r.t. plant library size",\n+ # xlabel="N", ylabel="E[\xce\xb3\xe2\x82\x93\xe2\x82\x96]", \n+ # xticks = (0:500:50000, string.(0:500:50000)),\n+ # size=(800,400), color=:turquoise4, linewidth=2)\n+ # hline!([0.95], linestyle=:dash, color=:grey, label="E[\xce\xb3\xe2\x82\x93\xe2\x82\x96] = 0.95", legend=:bottomright)\n+ \n+\n+ ENV["GKSwstype"]="nul"\n+ weave(string(@__DIR__) * "/report.jmd", \n+ args = (parsed_args = parsed_args,\n+ tool_info = tool_info,\n+ args_info = args_info,\n+ grna_dict = grna_dict,\n+ #h1 = h1, h2 = h2,\n+ output = out_dict); \n+ doctype = "md2html", out_path = :pwd)\n+ ENV["GKSwstype"]="gksqt"\n+end\n+\n+main(ARGS)\n' |
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| diff -r 000000000000 -r cc0957c46408 mcdoe.xml --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/mcdoe.xml Thu May 12 17:39:18 2022 +0000 |
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| b'@@ -0,0 +1,341 @@\n+<tool id="mcdoe" name="MultiplexCrisprDOE - simulation- and BioCCP-based approaches for computing the minimal plant library size" version="0.1.0" python_template_version="3.5">\n+ <requirements>\n+ <requirement type="package" version="1.7.2">julia</requirement>\n+ </requirements>\n+ <command detect_errors="exit_code"><![CDATA[\n+ \n+ ## method $t $x $g $r $n_gRNA_total $filename $filename $\xcf\xb5_KO --i 10\n+\n+ #if $tools.tool_selector == "gfd"\n+ julia \'$__tool_directory__/main.jl\' gfd $tools.pls $tools.sd $tools.min_gRNA_abundance \n+ $tools.max_gRNA_abundance $tools.n_gRNA_total $tools.normalize\n+ &&\n+ mv ./gRNA_reads.xlsx $gRNA_reads\n+ #elif $tools.tool_selector == "ged"\n+ julia \'$__tool_directory__/main.jl\' ged $tools.f_act $tools.eps_edit_act $tools.eps_edit_inact \n+ $tools.sd_act $tools.n_gRNA_total\n+ &&\n+ mv ./gRNA_edit.xlsx $gRNA_edit\n+ #elif $tools.tool_selector == "sim"\n+ julia \'$__tool_directory__/main.jl\' sim $tools.simulation_mode.simulation_mode_selector $tools.n_target_genes \n+ $tools.n_designed_gRNAs $tools.simulation_mode.n_gRNA_seqs $tools.n_gRNA_total $tools.p_gRNA_freq \n+ $tools.p_gRNA_edit $tools.g_KO --iter $tools.iter\n+ #if $tools.simulation_mode.simulation_mode_selector == "4"\n+ &&\n+ mv ./countKOs.xlsx $countKOs\n+ #end if\n+ #elif $tools.tool_selector == "ccp"\n+ julia \'$__tool_directory__/main.jl\' ccp $tools.bioccp_mode.bioccp_mode_selector $tools.n_target_genes $tools.pls \n+ $tools.n_designed_gRNAs $tools.bioccp_mode.n_gRNA_seqs $tools.n_gRNA_total $tools.p_gRNA_freq \n+ $tools.p_gRNA_edit $tools.g_KO --step $tools.step --MN $tools.max_pls\n+ #end if\n+ &&\n+ mv ./report.html $report\n+\n+ ]]></command>\n+ <inputs>\n+ <conditional name="tools">\n+ <param name="tool_selector" type="select" label="Select tool for processing the alignment(s)">\n+ <option value="gfd">Generate vector with frequencies in the combinatorial gRNA/Cas9 construct library for all gRNAs</option>\n+ <option value="ged">Generate vector with genome editing efficiencies for all the gRNAs in the experiment</option>\n+ <option value="sim">Simulation-based approaches for computing the minimal plant library size that guarantees full combinatorial coverage</option>\n+ <option value="ccp">BioCCP-based approaches for computing the minimal plant library size that guarantees full combinatorial coverage</option>\n+ </param>\n+ <when value="gfd">\n+ <param name="pls" type="integer" value="75" optional="false" />\n+ <param name="sd" type="integer" value="25" optional="false" />\n+ <param name="min_gRNA_abundance" value="50" type="integer" optional="false" />\n+ <param name="max_gRNA_abundance" value="100" type="integer" optional="false" />\n+ <param name="n_gRNA_total" value="120" type="integer" optional="false" />\n+ <param name="normalize" type="boolean" truevalue="--normalize" falsevalue="" checked="False" label="Convert gRNA abundances into relative frequencies" />\n+ </when>\n+ <when value="ged">\n+ <param name="f_act" type="float" value="0.9" optional="false" />\n+ <param name="eps_edit_act" type="float" value="0.95" optional="false" />\n+ <param name="eps_edit_inact" type="float" value="0.1" optional="false" />\n+ <param name="sd_act" type="float" value="0.01" optional="false" />\n+ <param name="n_gRNA_total" type="integer" value="120" optional="false" />\n+ </when>\n+ <when value="sim">\n+ <conditional name="simulation_mode">\n+ <param name="'..b'+ efficiency distributions for active and\n+ inactive gRNAs (type: Float16)\n+ n_gRNA_total the total number of gRNAs in the experiment\n+ (type: Int64)\n+\n+optional arguments:\n+ --visualize if provided a histogram of all genome editing\n+ efficiency is plotted\n+ --out_file OUT_FILE Output excel file prefix (default: "gRNA_edit")\n+ -h, --help show this help message and exit\n+\n+usage: main.jl sim [--i I] [-h] [M] [x] [g] [r] [t] [f] [e] [E]\n+\n+positional arguments:\n+ M Select simulation mode (1: simulate_N\xe2\x82\x93\xe2\x82\x81; 2:\n+ simulate_N\xe2\x82\x93\xe2\x82\x82; 3: simulate_N\xe2\x82\x93\xe2\x82\x83; 4:\n+ simulate_N\xe2\x82\x93\xe2\x82\x82_countKOs) (type: Int64)\n+ x number of target genes in the experiment (type:\n+ Int64)\n+ g number of gRNAs designed per target gene (type:\n+ Int64)\n+ r number of gRNA sequences per combinatorial gRNA/Cas\n+ construct (type: Int64)\n+ t total number of gRNAs in the experiment (type: Int64)\n+ f vector with relative frequencies for all gRNAs in the\n+ construct library (normalized!)\n+ e vector with genome editing efficiencies for all gRNAs\n+ E global knockout efficiency; fraction of mutations\n+ leading to effective gene knockout (type: Float16)\n+\n+optional arguments:\n+ --i, --iter I number of CRISPR/Cas experiments that are simulated\n+ (type: Int64, default: 500)\n+ -h, --help show this help message and exit\n+\n+usage: main.jl ccp [--s S] [--MN MN] [-h] [M] [x] [N] [g] [r] [t] [f]\n+ [e] [E]\n+\n+positional arguments:\n+ M Select BioCCP mode (1: BioCCP_N\xe2\x82\x93\xe2\x82\x81; 2:\n+ BioCCP_N\xe2\x82\x93\xe2\x82\x82; 3: BioCCP_N\xe2\x82\x93\xe2\x82\x83; 4: BioCCP_P\xe2\x82\x93\xe2\x82\x81; 5:\n+ BioCCP_P\xe2\x82\x93\xe2\x82\x82 ; 6: BioCCP_P\xe2\x82\x93\xe2\x82\x83; 7: BioCCP_\xce\xb3\xe2\x82\x93\xe2\x82\x81; 8:\n+ BioCCP_\xce\xb3\xe2\x82\x93\xe2\x82\x82; 9: BioCCP_\xce\xb3\xe2\x82\x93\xe2\x82\x83) (type: Int64)\n+ x number of target genes in the experiment\n+ (type: Int64)\n+ N (Minimum) plant library size (type: Int64)\n+ g number of gRNAs designed per target gene\n+ (type: Int64)\n+ r number of gRNA sequences per combinatorial\n+ gRNA/Cas construct (type: Int64)\n+ t total number of gRNAs in the experiment (type:\n+ Int64)\n+ f File containing vector with relative\n+ frequencies for all gRNAs in the construct\n+ library (normalized!)\n+ e File containing vector with genome editing\n+ efficiencies for all gRNAs\n+ E global knockout efficiency; fraction of\n+ mutations leading to effective gene knockout\n+ (type: Float16)\n+\n+optional arguments:\n+ --s, --step S Step size for plant library size (optional for\n+ calculating expected combinatorial coverage /\n+ plant library size) (type: Int64, default: 5)\n+ --MN, --max_pl_size MN\n+ Maximum plant library size (optional for\n+ calculating expected combinatorial coverage /\n+ plant library size) (type: Int64, default:\n+ 4000)\n+ -h, --help show this help message and exit\n+ ]]></help>\n+ <citations>\n+ <citation type="bibtex">\n+@misc{githubMultiplexCrisprDOE,\n+ author = {LastTODO, FirstTODO},\n+ year = {TODO},\n+ title = {MultiplexCrisprDOE},\n+ publisher = {GitHub},\n+ journal = {GitHub repository},\n+ url = {https://github.com/kirstvh/MultiplexCrisprDOE},\n+}</citation>\n+ </citations>\n+</tool>\n\\ No newline at end of file\n' |
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| @@ -0,0 +1,102 @@ +--- +title: MultiplexCrisprDOE +--- + +<!-- this setup dependencies, but doesn't appear in the generated document --> +```julia; echo = false; results = "hidden" +using Pkg +"Plots" ∉ keys(Pkg.project().dependencies) && Pkg.add("Plots") +#"DSP" ∉ keys(Pkg.project().dependencies) && Pkg.add("DSP") +#"Images" ∉ keys(Pkg.project().dependencies) && Pkg.add("Images") +"DataStructures" ∉ keys(Pkg.project().dependencies) && Pkg.add("DataStructures") +"PrettyTables" ∉ keys(Pkg.project().dependencies) && Pkg.add("PrettyTables") +"DataFrames" ∉ keys(Pkg.project().dependencies) && Pkg.add("DataFrames") +"Latexify" ∉ keys(Pkg.project().dependencies) && Pkg.add("Latexify") +``` +## Tool + +* **Method:** `j println(WEAVE_ARGS.tool_info["method"])` + +* **Description:** `j println(WEAVE_ARGS.tool_info["description"])` + +* **Mode:** `j println(WEAVE_ARGS.tool_info["mode"])` + +* **Mode description:** `j println(WEAVE_ARGS.tool_info["mode_description"])` + +## Variables + +```julia; echo = false +using DataFrames +using PrettyTables +df = DataFrame("Argument" => collect(keys(WEAVE_ARGS.args_info)), "Value" => collect(values(WEAVE_ARGS.args_info))) +#pt = pretty_table(df, nosubheader=true; alignment=:l) +``` + +```julia; echo = false + using Plots + if haskey(WEAVE_ARGS.grna_dict,"p_gRNA_reads") + h1 = histogram(WEAVE_ARGS.grna_dict["p_gRNA_reads"], label="", + xlabel="Number of reads per gRNA", + linecolor="white", + normalize=:probability, + xtickfontsize=10,ytickfontsize=10, + color=:mediumturquoise, size=(600,350), bins = 25, + ylabel="Relative frequency", + title="gRNA frequency distribution") + display(h1) + end +``` + +```julia; echo = false + using Plots + if haskey(WEAVE_ARGS.grna_dict,"p_gRNA_edit") + h2 = histogram(WEAVE_ARGS.grna_dict["p_gRNA_edit"], + normalize = :probability, + linecolor = "white", + label="", + color=:turquoise4, + xtickfontsize=10,ytickfontsize=10, xlim = (0, 1), + xticks=(0:0.1:1), + bins = 150, + xlabel="gRNA editing efficiency", + ylabel="Relative frequency", + title="gRNA genome editing effiency distribution") + display(h2) + end +``` + +```julia; echo = false + using Plots + if haskey(WEAVE_ARGS.output,"output file") + println("Output written to:") + println(WEAVE_ARGS.output["output file"]) + elseif haskey(WEAVE_ARGS.output,"E_sim") + E_sim = WEAVE_ARGS.output["E_sim"] + sd_sim = WEAVE_ARGS.output["sd_sim"] + k = WEAVE_ARGS.args_info["# of gRNAs / combi gRNA/Cas construct"] + x = WEAVE_ARGS.args_info["# of target genes in the experiment"] + println("**How many plants need to be included in the plant library (on average) to obtain full coverage of all k-combinations of gene knockouts?**") + println("On average, ", Int(ceil(E_sim)), " plants need to be sampled at random to observe all ", k, "-combinations of ", x, " gene knockouts. Standard deviation = ", Int(ceil(sd_sim)), " plants") + elseif haskey(WEAVE_ARGS.output,"P_sim") + p = plot(WEAVE_ARGS.output["pls"], WEAVE_ARGS.output["P_sim"], label="Pₓ₂", + title="Probability of full combinatorial coverage with respect to plant library size", + xlabel="N", ylabel="Pₓₖ", + xticks = (0:500:50000, string.(0:500:50000)), + size=(900,400), color=:turquoise4, linewidth=2) + hline!([0.95], linestyle=:dash, color=:grey, label="Pₓₖ = 0.95", legend=:bottomright) + display(p) + println("At a given number of plants, what is the probability that all pairwise combinations of gene knockouts are observed?") + println("N_95_P: ", WEAVE_ARGS.output["N_95_P"]) + elseif haskey(WEAVE_ARGS.output,"E_cov") + p = plot(WEAVE_ARGS.output["pls"], WEAVE_ARGS.output["E_cov"], + label="E[γₓ₂]", title="Expected combinatorial coverage w.r.t. plant library size", + xlabel="N", ylabel="E[γₓₖ]", + xticks = (0:500:50000, string.(0:500:50000)), + size=(800,400), color=:turquoise4, linewidth=2) + hline!([0.95], linestyle=:dash, color=:grey, label="E[γₓₖ] = 0.95", legend=:bottomright) + display(p) + println("At a given number of plants, what is the expected coverage of pairwise gene knockout combinations?") + println("N_95: ", WEAVE_ARGS.output["N_95"]) + end +``` + |
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| b'@@ -0,0 +1,704 @@\n+<!DOCTYPE html>\n+<HTML lang = "en">\n+<HEAD>\n+ <meta charset="UTF-8"/>\n+ <meta name="viewport" content="width=device-width, initial-scale=1.0, user-scalable=yes">\n+ <title>MultiplexCrisprDOE</title>\n+ \n+\n+ <script type="text/x-mathjax-config">\n+ MathJax.Hub.Config({\n+ tex2jax: {inlineMath: [[\'$\',\'$\'], [\'\\\\(\',\'\\\\)\']]},\n+ TeX: { equationNumbers: { autoNumber: "AMS" } }\n+ });\n+ </script>\n+\n+ <script type="text/javascript" async src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS-MML_HTMLorMML">\n+ </script>\n+\n+ \n+<style>\n+pre.hljl {\n+ border: 1px solid #ccc;\n+ margin: 5px;\n+ padding: 5px;\n+ overflow-x: auto;\n+ color: rgb(68,68,68); background-color: rgb(251,251,251); }\n+pre.hljl > span.hljl-t { }\n+pre.hljl > span.hljl-w { }\n+pre.hljl > span.hljl-e { }\n+pre.hljl > span.hljl-eB { }\n+pre.hljl > span.hljl-o { }\n+pre.hljl > span.hljl-k { color: rgb(148,91,176); font-weight: bold; }\n+pre.hljl > span.hljl-kc { color: rgb(59,151,46); font-style: italic; }\n+pre.hljl > span.hljl-kd { color: rgb(214,102,97); font-style: italic; }\n+pre.hljl > span.hljl-kn { color: rgb(148,91,176); font-weight: bold; }\n+pre.hljl > span.hljl-kp { color: rgb(148,91,176); font-weight: bold; }\n+pre.hljl > span.hljl-kr { color: rgb(148,91,176); font-weight: bold; }\n+pre.hljl > span.hljl-kt { color: rgb(148,91,176); font-weight: bold; }\n+pre.hljl > span.hljl-n { }\n+pre.hljl > span.hljl-na { }\n+pre.hljl > span.hljl-nb { }\n+pre.hljl > span.hljl-nbp { }\n+pre.hljl > span.hljl-nc { }\n+pre.hljl > span.hljl-ncB { }\n+pre.hljl > span.hljl-nd { color: rgb(214,102,97); }\n+pre.hljl > span.hljl-ne { }\n+pre.hljl > span.hljl-neB { }\n+pre.hljl > span.hljl-nf { color: rgb(66,102,213); }\n+pre.hljl > span.hljl-nfm { color: rgb(66,102,213); }\n+pre.hljl > span.hljl-np { }\n+pre.hljl > span.hljl-nl { }\n+pre.hljl > span.hljl-nn { }\n+pre.hljl > span.hljl-no { }\n+pre.hljl > span.hljl-nt { }\n+pre.hljl > span.hljl-nv { }\n+pre.hljl > span.hljl-nvc { }\n+pre.hljl > span.hljl-nvg { }\n+pre.hljl > span.hljl-nvi { }\n+pre.hljl > span.hljl-nvm { }\n+pre.hljl > span.hljl-l { }\n+pre.hljl > span.hljl-ld { color: rgb(148,91,176); font-style: italic; }\n+pre.hljl > span.hljl-s { color: rgb(201,61,57); }\n+pre.hljl > span.hljl-sa { color: rgb(201,61,57); }\n+pre.hljl > span.hljl-sb { color: rgb(201,61,57); }\n+pre.hljl > span.hljl-sc { color: rgb(201,61,57); }\n+pre.hljl > span.hljl-sd { color: rgb(201,61,57); }\n+pre.hljl > span.hljl-sdB { color: rgb(201,61,57); }\n+pre.hljl > span.hljl-sdC { color: rgb(201,61,57); }\n+pre.hljl > span.hljl-se { color: rgb(59,151,46); }\n+pre.hljl > span.hljl-sh { color: rgb(201,61,57); }\n+pre.hljl > span.hljl-si { }\n+pre.hljl > span.hljl-so { color: rgb(201,61,57); }\n+pre.hljl > span.hljl-sr { color: rgb(201,61,57); }\n+pre.hljl > span.hljl-ss { color: rgb(201,61,57); }\n+pre.hljl > span.hljl-ssB { color: rgb(201,61,57); }\n+pre.hljl > span.hljl-nB { color: rgb(59,151,46); }\n+pre.hljl > span.hljl-nbB { color: rgb(59,151,46); }\n+pre.hljl > span.hljl-nfB { color: rgb(59,151,46); }\n+pre.hljl > span.hljl-nh { color: rgb(59,151,46); }\n+pre.hljl > span.hljl-ni { color: rgb(59,151,46); }\n+pre.hljl > span.hljl-nil { color: rgb(59,151,46); }\n+pre.hljl > span.hljl-noB { color: rgb(59,151,46); }\n+pre.hljl > span.hljl-oB { color: rgb(102,102,102); font-weight: bold; }\n+pre.hljl > span.hljl-ow { color: rgb(102,102,102); font-weight: bold; }\n+pre.hljl > span.hljl-p { }\n+pre.hljl > span.hljl-c { color: rgb(153,153,119); font-style: italic; }\n+pre.hljl > span.hljl-ch { color: rgb(153,153,119); font-style: italic; }\n+pre.hljl > span.hljl-cm { color: rgb(153,153,119); font-style: italic; }\n+pre.hljl > span.hljl-cp { color: rgb(153,153,119); font-style: italic; }\n+pre.hljl > span.hljl-cpB { color: rgb(153,153,119); font-style: italic; }\n+pre.hljl > span.hljl-cs { color: rgb(153,153,119); font-style: italic; }\n+pre.hljl > span.hljl-csB { color: rgb(153,153,119); font-style: italic; }\n+pre.hljl > span.hljl-g { }\n+pre.'..b'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" />\n+\n+<pre class="output">\n+Output written to:\n+gRNA_edit.xlsx\n+</pre>\n+\n+\n+\n+ <HR/>\n+ <div class="footer">\n+ <p>\n+ Published from <a href="report.jmd">report.jmd</a>\n+ using <a href="http://github.com/JunoLab/Weave.jl">Weave.jl</a> v0.10.10 on 2022-05-12.\n+ </p>\n+ </div>\n+ </div>\n+ </div>\n+ </div>\n+</BODY>\n+\n+</HTML>\n' |
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| diff -r 000000000000 -r cc0957c46408 test-data/test_gfd_report.html --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test_gfd_report.html Thu May 12 17:39:18 2022 +0000 |
| [ |
| b'@@ -0,0 +1,704 @@\n+<!DOCTYPE html>\n+<HTML lang = "en">\n+<HEAD>\n+ <meta charset="UTF-8"/>\n+ <meta name="viewport" content="width=device-width, initial-scale=1.0, user-scalable=yes">\n+ <title>MultiplexCrisprDOE</title>\n+ \n+\n+ <script type="text/x-mathjax-config">\n+ MathJax.Hub.Config({\n+ tex2jax: {inlineMath: [[\'$\',\'$\'], [\'\\\\(\',\'\\\\)\']]},\n+ TeX: { equationNumbers: { autoNumber: "AMS" } }\n+ });\n+ </script>\n+\n+ <script type="text/javascript" async src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS-MML_HTMLorMML">\n+ </script>\n+\n+ \n+<style>\n+pre.hljl {\n+ border: 1px solid #ccc;\n+ margin: 5px;\n+ padding: 5px;\n+ overflow-x: auto;\n+ color: rgb(68,68,68); background-color: rgb(251,251,251); }\n+pre.hljl > span.hljl-t { }\n+pre.hljl > span.hljl-w { }\n+pre.hljl > span.hljl-e { }\n+pre.hljl > span.hljl-eB { }\n+pre.hljl > span.hljl-o { }\n+pre.hljl > span.hljl-k { color: rgb(148,91,176); font-weight: bold; }\n+pre.hljl > span.hljl-kc { color: rgb(59,151,46); font-style: italic; }\n+pre.hljl > span.hljl-kd { color: rgb(214,102,97); font-style: italic; }\n+pre.hljl > span.hljl-kn { color: rgb(148,91,176); font-weight: bold; }\n+pre.hljl > span.hljl-kp { color: rgb(148,91,176); font-weight: bold; }\n+pre.hljl > span.hljl-kr { color: rgb(148,91,176); font-weight: bold; }\n+pre.hljl > span.hljl-kt { color: rgb(148,91,176); font-weight: bold; }\n+pre.hljl > span.hljl-n { }\n+pre.hljl > span.hljl-na { }\n+pre.hljl > span.hljl-nb { }\n+pre.hljl > span.hljl-nbp { }\n+pre.hljl > span.hljl-nc { }\n+pre.hljl > span.hljl-ncB { }\n+pre.hljl > span.hljl-nd { color: rgb(214,102,97); }\n+pre.hljl > span.hljl-ne { }\n+pre.hljl > span.hljl-neB { }\n+pre.hljl > span.hljl-nf { color: rgb(66,102,213); }\n+pre.hljl > span.hljl-nfm { color: rgb(66,102,213); }\n+pre.hljl > span.hljl-np { }\n+pre.hljl > span.hljl-nl { }\n+pre.hljl > span.hljl-nn { }\n+pre.hljl > span.hljl-no { }\n+pre.hljl > span.hljl-nt { }\n+pre.hljl > span.hljl-nv { }\n+pre.hljl > span.hljl-nvc { }\n+pre.hljl > span.hljl-nvg { }\n+pre.hljl > span.hljl-nvi { }\n+pre.hljl > span.hljl-nvm { }\n+pre.hljl > span.hljl-l { }\n+pre.hljl > span.hljl-ld { color: rgb(148,91,176); font-style: italic; }\n+pre.hljl > span.hljl-s { color: rgb(201,61,57); }\n+pre.hljl > span.hljl-sa { color: rgb(201,61,57); }\n+pre.hljl > span.hljl-sb { color: rgb(201,61,57); }\n+pre.hljl > span.hljl-sc { color: rgb(201,61,57); }\n+pre.hljl > span.hljl-sd { color: rgb(201,61,57); }\n+pre.hljl > span.hljl-sdB { color: rgb(201,61,57); }\n+pre.hljl > span.hljl-sdC { color: rgb(201,61,57); }\n+pre.hljl > span.hljl-se { color: rgb(59,151,46); }\n+pre.hljl > span.hljl-sh { color: rgb(201,61,57); }\n+pre.hljl > span.hljl-si { }\n+pre.hljl > span.hljl-so { color: rgb(201,61,57); }\n+pre.hljl > span.hljl-sr { color: rgb(201,61,57); }\n+pre.hljl > span.hljl-ss { color: rgb(201,61,57); }\n+pre.hljl > span.hljl-ssB { color: rgb(201,61,57); }\n+pre.hljl > span.hljl-nB { color: rgb(59,151,46); }\n+pre.hljl > span.hljl-nbB { color: rgb(59,151,46); }\n+pre.hljl > span.hljl-nfB { color: rgb(59,151,46); }\n+pre.hljl > span.hljl-nh { color: rgb(59,151,46); }\n+pre.hljl > span.hljl-ni { color: rgb(59,151,46); }\n+pre.hljl > span.hljl-nil { color: rgb(59,151,46); }\n+pre.hljl > span.hljl-noB { color: rgb(59,151,46); }\n+pre.hljl > span.hljl-oB { color: rgb(102,102,102); font-weight: bold; }\n+pre.hljl > span.hljl-ow { color: rgb(102,102,102); font-weight: bold; }\n+pre.hljl > span.hljl-p { }\n+pre.hljl > span.hljl-c { color: rgb(153,153,119); font-style: italic; }\n+pre.hljl > span.hljl-ch { color: rgb(153,153,119); font-style: italic; }\n+pre.hljl > span.hljl-cm { color: rgb(153,153,119); font-style: italic; }\n+pre.hljl > span.hljl-cp { color: rgb(153,153,119); font-style: italic; }\n+pre.hljl > span.hljl-cpB { color: rgb(153,153,119); font-style: italic; }\n+pre.hljl > span.hljl-cs { color: rgb(153,153,119); font-style: italic; }\n+pre.hljl > span.hljl-csB { color: rgb(153,153,119); font-style: italic; }\n+pre.hljl > span.hljl-g { }\n+pre.'..b'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" />\n+\n+\n+<pre class="output">\n+Output written to:\n+gRNA_reads.xlsx\n+</pre>\n+\n+\n+\n+ <HR/>\n+ <div class="footer">\n+ <p>\n+ Published from <a href="report.jmd">report.jmd</a>\n+ using <a href="http://github.com/JunoLab/Weave.jl">Weave.jl</a> v0.10.10 on 2022-05-11.\n+ </p>\n+ </div>\n+ </div>\n+ </div>\n+ </div>\n+</BODY>\n+\n+</HTML>\n' |
| b |
| diff -r 000000000000 -r cc0957c46408 test-data/test_sim_report.html --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test_sim_report.html Thu May 12 17:39:18 2022 +0000 |
| [ |
| b'@@ -0,0 +1,705 @@\n+<!DOCTYPE html>\n+<HTML lang = "en">\n+<HEAD>\n+ <meta charset="UTF-8"/>\n+ <meta name="viewport" content="width=device-width, initial-scale=1.0, user-scalable=yes">\n+ <title>MultiplexCrisprDOE</title>\n+ \n+\n+ <script type="text/x-mathjax-config">\n+ MathJax.Hub.Config({\n+ tex2jax: {inlineMath: [[\'$\',\'$\'], [\'\\\\(\',\'\\\\)\']]},\n+ TeX: { equationNumbers: { autoNumber: "AMS" } }\n+ });\n+ </script>\n+\n+ <script type="text/javascript" async src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS-MML_HTMLorMML">\n+ </script>\n+\n+ \n+<style>\n+pre.hljl {\n+ border: 1px solid #ccc;\n+ margin: 5px;\n+ padding: 5px;\n+ overflow-x: auto;\n+ color: rgb(68,68,68); background-color: rgb(251,251,251); }\n+pre.hljl > span.hljl-t { }\n+pre.hljl > span.hljl-w { }\n+pre.hljl > span.hljl-e { }\n+pre.hljl > span.hljl-eB { }\n+pre.hljl > span.hljl-o { }\n+pre.hljl > span.hljl-k { color: rgb(148,91,176); font-weight: bold; }\n+pre.hljl > span.hljl-kc { color: rgb(59,151,46); font-style: italic; }\n+pre.hljl > span.hljl-kd { color: rgb(214,102,97); font-style: italic; }\n+pre.hljl > span.hljl-kn { color: rgb(148,91,176); font-weight: bold; }\n+pre.hljl > span.hljl-kp { color: rgb(148,91,176); font-weight: bold; }\n+pre.hljl > span.hljl-kr { color: rgb(148,91,176); font-weight: bold; }\n+pre.hljl > span.hljl-kt { color: rgb(148,91,176); font-weight: bold; }\n+pre.hljl > span.hljl-n { }\n+pre.hljl > span.hljl-na { }\n+pre.hljl > span.hljl-nb { }\n+pre.hljl > span.hljl-nbp { }\n+pre.hljl > span.hljl-nc { }\n+pre.hljl > span.hljl-ncB { }\n+pre.hljl > span.hljl-nd { color: rgb(214,102,97); }\n+pre.hljl > span.hljl-ne { }\n+pre.hljl > span.hljl-neB { }\n+pre.hljl > span.hljl-nf { color: rgb(66,102,213); }\n+pre.hljl > span.hljl-nfm { color: rgb(66,102,213); }\n+pre.hljl > span.hljl-np { }\n+pre.hljl > span.hljl-nl { }\n+pre.hljl > span.hljl-nn { }\n+pre.hljl > span.hljl-no { }\n+pre.hljl > span.hljl-nt { }\n+pre.hljl > span.hljl-nv { }\n+pre.hljl > span.hljl-nvc { }\n+pre.hljl > span.hljl-nvg { }\n+pre.hljl > span.hljl-nvi { }\n+pre.hljl > span.hljl-nvm { }\n+pre.hljl > span.hljl-l { }\n+pre.hljl > span.hljl-ld { color: rgb(148,91,176); font-style: italic; }\n+pre.hljl > span.hljl-s { color: rgb(201,61,57); }\n+pre.hljl > span.hljl-sa { color: rgb(201,61,57); }\n+pre.hljl > span.hljl-sb { color: rgb(201,61,57); }\n+pre.hljl > span.hljl-sc { color: rgb(201,61,57); }\n+pre.hljl > span.hljl-sd { color: rgb(201,61,57); }\n+pre.hljl > span.hljl-sdB { color: rgb(201,61,57); }\n+pre.hljl > span.hljl-sdC { color: rgb(201,61,57); }\n+pre.hljl > span.hljl-se { color: rgb(59,151,46); }\n+pre.hljl > span.hljl-sh { color: rgb(201,61,57); }\n+pre.hljl > span.hljl-si { }\n+pre.hljl > span.hljl-so { color: rgb(201,61,57); }\n+pre.hljl > span.hljl-sr { color: rgb(201,61,57); }\n+pre.hljl > span.hljl-ss { color: rgb(201,61,57); }\n+pre.hljl > span.hljl-ssB { color: rgb(201,61,57); }\n+pre.hljl > span.hljl-nB { color: rgb(59,151,46); }\n+pre.hljl > span.hljl-nbB { color: rgb(59,151,46); }\n+pre.hljl > span.hljl-nfB { color: rgb(59,151,46); }\n+pre.hljl > span.hljl-nh { color: rgb(59,151,46); }\n+pre.hljl > span.hljl-ni { color: rgb(59,151,46); }\n+pre.hljl > span.hljl-nil { color: rgb(59,151,46); }\n+pre.hljl > span.hljl-noB { color: rgb(59,151,46); }\n+pre.hljl > span.hljl-oB { color: rgb(102,102,102); font-weight: bold; }\n+pre.hljl > span.hljl-ow { color: rgb(102,102,102); font-weight: bold; }\n+pre.hljl > span.hljl-p { }\n+pre.hljl > span.hljl-c { color: rgb(153,153,119); font-style: italic; }\n+pre.hljl > span.hljl-ch { color: rgb(153,153,119); font-style: italic; }\n+pre.hljl > span.hljl-cm { color: rgb(153,153,119); font-style: italic; }\n+pre.hljl > span.hljl-cp { color: rgb(153,153,119); font-style: italic; }\n+pre.hljl > span.hljl-cpB { color: rgb(153,153,119); font-style: italic; }\n+pre.hljl > span.hljl-cs { color: rgb(153,153,119); font-style: italic; }\n+pre.hljl > span.hljl-csB { color: rgb(153,153,119); font-style: italic; }\n+pre.hljl > span.hljl-g { }\n+pre.'..b'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" />\n+\n+<pre class="output">\n+Output written to:\n+countKOs.xlsx\n+</pre>\n+\n+\n+\n+ <HR/>\n+ <div class="footer">\n+ <p>\n+ Published from <a href="report.jmd">report.jmd</a>\n+ using <a href="http://github.com/JunoLab/Weave.jl">Weave.jl</a> v0.10.10 on 2022-05-12.\n+ </p>\n+ </div>\n+ </div>\n+ </div>\n+ </div>\n+</BODY>\n+\n+</HTML>\n' |