Treatment are now allele strings

Manifest.toml

@@ -2,7 +2,7 @@
 
 julia_version = "1.10.4"
 manifest_format = "2.0"
-project_hash = "2b58dcc0ffd21f9ddd37c869a6c32c55af516134"
+project_hash = "b1a916e4f68d2fb953c6eba21c0fc7546e7dc5c6"
 
 [[deps.ARFFFiles]]
 deps = ["CategoricalArrays", "Dates", "Parsers", "Tables"]

src/inputs_from_config.jl

@@ -167,7 +167,7 @@ end
 """
 function treatments_from_variant(variant::String, dataset::DataFrame)
     variant_levels = sort(levels(dataset[!, variant], skipmissing=true))
-    return Dict{Symbol, Vector{UInt8}}(Symbol(variant)=>variant_levels)
+    return Dict{Symbol, Vector{String}}(Symbol(variant)=>variant_levels)
 end
 
 function estimands_from_gwas(dataset, variants, outcomes, confounders; 
@@ -198,14 +198,35 @@ function read_bed_chromosome(bedprefix)
     return SnpData(bed_file, famnm=fam_file, bimnm=bim_file)
 end
 
+function map_allele(value, allele1, allele2)
+    if value == 0x00
+        return "$allele1$allele1"
+    elseif value == 0x01
+        return missing
+    elseif value == 0x02
+        return "$allele1$allele2"
+    elseif value == 0x03
+        return "$allele2$allele2"
+    end
+end
+
+function convert_string(snpdata)
+    genotypes_data = []
+    for col in 1:snpdata.snps
+        allele_col = snpdata.snparray[:,col]
+        allele1 = snpdata.snp_info[col, "allele1"]
+        allele2 = snpdata.snp_info[col, "allele2"]
+        mapped_col = map(value -> map_allele(value, allele1, allele2), allele_col)
+        push!(genotypes_data, mapped_col)
+    end
+    return DataFrame(genotypes_data, snpdata.snp_info."snpid")
+end
+
 function get_genotypes_from_beds(bedprefix)
     snpdata = read_bed_chromosome(bedprefix)
-    genotypes = DataFrame(convert(Matrix{UInt8}, snpdata.snparray), snpdata.snp_info."snpid")
-    genotype_map = Union{UInt8, Missing}[0, missing, 1, 2]
-    for col in names(genotypes)
-        genotypes[!, col] = [genotype_map[x+1] for x in genotypes[!, col]]
-    end
+    genotypes = convert_string(snpdata)
     insertcols!(genotypes, 1, :SAMPLE_ID => snpdata.person_info."iid")
+
     return genotypes
 end
 

test/inputs_from_gwas_config.jl

@@ -19,18 +19,27 @@ function get_summary_stats(estimands)
     return sort(combine(groupby(results, :OUTCOME), nrow), :OUTCOME)
 end
 
-function check_estimands_levels_order(estimands)
+function check_estimands_levels_order(estimands, snp_info)
     for Ψ in estimands
         # If the two components are present, the first is the 0 -> 1 and the second is the 1 -> 2
         variant = only(keys(Ψ.args[1].treatment_values))
+        variant_info = filter(:snpid=>x->x==String(variant),snp_info)
+        allele1, allele2 = variant_info.allele1[1], variant_info.allele2[1]
+
+        # Here, we check if the order is sufficient to be able to compute non-linear effects any of these combinations will do
         if length(Ψ.args) == 2
-            @test Ψ.args[1].treatment_values[variant] == (control = 0x00, case = 0x01)
-            @test Ψ.args[2].treatment_values[variant] == (control = 0x01, case = 0x02)
+            @test (Ψ.args[1].treatment_values[variant] == (control = allele1*allele1, case = allele1*allele2) && 
+            Ψ.args[2].treatment_values[variant] == (control = allele1*allele2, case = allele2*allele2)) || 
+            (Ψ.args[1].treatment_values[variant] == (control = allele2*allele2, case = allele1*allele2) && 
+            Ψ.args[2].treatment_values[variant] == (control = allele1*allele2, case = allele1*allele1))
         else
             # Otherwise we check they are one or the other
             arg = only(Ψ.args)
-            @test arg.treatment_values[variant]==(control = 0x00, case = 0x01) ||
-            arg.treatment_values[variant]==( control = 0x01, case = 0x02)
+            @test arg.treatment_values[variant] == (control = allele1*allele1, case = allele1*allele2)  ||
+            arg.treatment_values[variant] == (control = allele2*allele2, case = allele1*allele2) ||
+            arg.treatment_values[variant] == (control = allele1*allele2, case = allele2*allele2) ||
+            arg.treatment_values[variant] == (control = allele1*allele2, case = allele1*allele1) 
+
         end
    end
 end
@@ -48,6 +57,10 @@ end
         "--positivity-constraint=0"
     ])
     TargeneCore.julia_main()
+
+    # Define SNP information to check string allele defintions
+    snpdata = read_bed_chromosome(joinpath(TESTDIR, "data", "ukbb", "genotypes" , "ukbb_1."))
+    snp_info = select(DataFrame(snpdata.snp_info), [:snpid, :allele1, :allele2])
     # Check dataset
     dataset = DataFrame(Arrow.Table(joinpath(tmpdir, "final.data.arrow")))
     @test size(dataset) == (1940, 886)
@@ -68,7 +81,7 @@ end
         nrow = repeat([875], 5)
     )
 
-    check_estimands_levels_order(estimands)
+    check_estimands_levels_order(estimands, snp_info)
 end
 
 @testset "Test inputs_from_config gwas: positivity constraint" begin