Mercurial > repos > padge > mcdoe
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planemo upload for repository https://github.com/kirstvh/MultiplexCrisprDOE commit a920127294bcfcb708881e28144a77a5c10d46d2-dirty
author | padge |
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date | Wed, 31 Aug 2022 13:17:33 +0000 |
parents | cc0957c46408 |
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--- 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 ```