test/runtests.jl: Add more tests to increase coverage and fix depreca…

…tion.

src/lineage_processing.jl

@@ -59,7 +59,7 @@ function process_lineages(df::DataFrame;
         if nrow(group) > 1
             dist = pairwise_hamming(LongDNA{4}.(group.cdr3))
             hclusters = hclust(dist, linkage=:average)
-            maximum_height = maximum(hclusters.height)
+            maximum_height = maximum(hclusters.heights)
             cutoff = maximum_height * cutoff_ratio
             group[!, :cluster] = cutree(hclusters, h=cutoff)
         else

test/runtests.jl

@@ -1,6 +1,102 @@
-using LineageCollapse
 using Test
+using DataFrames
+using BioSequences
+using LineageCollapse
+using CSV
+using CairoMakie
 
 @testset "LineageCollapse.jl" begin
-    @test 1 == 1
-end
+    @testset "Data Loading" begin
+        # Create a temporary TSV file for testing
+        test_data = """
+        sequence\tv_sequence_end\tj_sequence_start\tcdr3\tv_call\tj_call\tstop_codon
+        ACGT\t2\t3\tCDR3\tV1\tJ1\tfalse
+        TGCA\t3\t4\tCDR3_2\tV2\tJ2\ttrue
+        """
+        test_file = tempname() * ".tsv"
+        write(test_file, test_data)    
+        df = load_data(test_file)
+
+        @test size(df) == (2, 7)
+        @test names(df) == ["sequence", "v_sequence_end", "j_sequence_start", "cdr3", "v_call", "j_call", "stop_codon"]
+        @test df.sequence == ["ACGT", "TGCA"]
+
+        # Test with custom columns
+        custom_data = """
+        seq\tcdr3\tv_call
+        ACGT\tCDR3\tV1
+        TGCA\tCDR3_2\tV2
+        """
+        custom_file = tempname() * ".tsv"
+        write(custom_file, custom_data)
+
+        custom_df = load_data(custom_file, required_columns=[:seq, :cdr3, :v_call])
+        @test size(custom_df) == (2, 3)
+        @test names(custom_df) == ["seq", "cdr3", "v_call"]
+    end
+
+    @testset "Preprocessing" begin
+        test_df = DataFrame(
+            sequence = ["ACGT", "TGCA", "GTAC", "CATG"],
+            v_sequence_end = [2, 3, 2, 3],
+            j_sequence_start = [3, 4, 3, 4],
+            cdr3 = ["CDR3", "CDR3_2", missing, "CDR3_4"],
+            v_call = ["V1,V2", "V2", "V3", "V4"],
+            j_call = ["J1", "J2,J3", "J3", "J4"],
+            stop_codon = [false, true, false, false]
+        )
+
+        processed_df = preprocess_data(test_df, min_d_region_length=1)
+        @test nrow(processed_df) == 2  # After dropping missing CDR3 and stop codons
+        @test :d_region in propertynames(processed_df)
+        @test :v_call_first in propertynames(processed_df)
+        @test :j_call_first in propertynames(processed_df)
+        @test :cdr3_length in propertynames(processed_df)
+        @test processed_df.v_call_first == ["V1", "V4"]
+        @test processed_df.j_call_first == ["J1", "J4"]
+    end
+
+    @testset "Lineage Processing" begin
+        @testset "Hamming Distance" begin
+            seq1 = LongDNA{4}("ATCG")
+            seq2 = LongDNA{4}("ATTG")
+            @test LineageCollapse.hamming(seq1, seq2) == 1.0
+        end
+
+        @testset "Pairwise Hamming" begin
+            seqs = [LongDNA{4}("ATCG"), LongDNA{4}("ATTG"), LongDNA{4}("ATCG")]
+            dist_matrix = LineageCollapse.pairwise_hamming(seqs)
+            @test size(dist_matrix) == (3, 3)
+            @test dist_matrix[1,2] == dist_matrix[2,1] == 1.0
+            @test dist_matrix[1,3] == dist_matrix[3,1] == 0.0
+        end
+
+        @testset "Process Lineages" begin
+            test_df = DataFrame(
+                v_call_first = ["V1", "V1", "V2", "V2"],
+                j_call_first = ["J1", "J1", "J2", "J2"],
+                cdr3_length = [4, 4, 5, 5],
+                cdr3 = ["ATCG", "ATTG", "ATCGA", "ATCGA"],
+                d_region = ["TC", "TT", "TCG", "TCG"],
+                cluster_size = [1, 1, 1, 1]
+            )
+
+            processed_df = process_lineages(test_df)
+            @test :cluster in propertynames(processed_df)
+            @test :cdr3_frequency in propertynames(processed_df)
+            @test nrow(processed_df) <= nrow(test_df)  # Some rows might be filtered out
+        end
+    end
+
+    @testset "Visualization" begin
+        test_df = DataFrame(
+            cluster_size = [1, 2, 3, 4, 5],
+            cdr3_length = [10, 11, 12, 13, 14],
+            cdr3_frequency = [0.1, 0.2, 0.3, 0.4, 0.5],
+            v_call_first = ["V1", "V2", "V3", "V4", "V5"]
+        )
+
+        fig = plot_diagnostics(test_df)
+        @test fig isa CairoMakie.Figure
+    end
+end