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fix suffixes not being removed in preclusters
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@AroneyS
AroneyS committed Oct 2, 2024
1 parent f6aa5d3 commit 46e34c2
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Showing 2 changed files with 96 additions and 3 deletions.
18 changes: 18 additions & 0 deletions binchicken/workflow/scripts/target_elusive.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -20,6 +20,7 @@

def get_clusters(
sample_distances,
samples,
PRECLUSTER_SIZE=2,
MAX_COASSEMBLY_SAMPLES=2):
logging.info(f"Polars using {str(pl.thread_pool_size())} threads")
Expand All @@ -31,6 +32,18 @@ def get_clusters(
# Set to 2 to produce paired edges
MAX_COASSEMBLY_SAMPLES = 2

sample_distances = (
sample_distances
.with_columns(
pl.when(pl.col("query_name").is_in(samples))
.then(pl.col("query_name"))
.otherwise(pl.col("query_name").str.replace(SUFFIX_RE, "")),
pl.when(pl.col("match_name").is_in(samples))
.then(pl.col("match_name"))
.otherwise(pl.col("match_name").str.replace(SUFFIX_RE, "")),
)
)

logging.info("Converting to sparse array")
samples = np.unique(np.concatenate([
sample_distances.select("query_name").to_numpy().flatten(),
Expand Down Expand Up @@ -185,6 +198,8 @@ def process_chunk(df):
processed_chunk = process_chunk(chunk)
processed_chunk.write_csv(f, separator="\t", include_header=i==0)

logging.info("Done")

return

def pipeline(
Expand Down Expand Up @@ -325,6 +340,7 @@ def process_groups(df):
)
sample_preclusters = get_clusters(
sample_distances,
samples,
PRECLUSTER_SIZE=PRECLUSTER_SIZE,
MAX_COASSEMBLY_SAMPLES=MAX_COASSEMBLY_SAMPLES,
)
Expand All @@ -349,3 +365,5 @@ def process_groups(df):
)
targets.write_csv(targets_path, separator="\t")
edges.sort("style", "cluster_size", "samples").write_csv(edges_path, separator="\t")

logging.info("Done")
81 changes: 78 additions & 3 deletions test/test_target_elusive.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -56,13 +56,62 @@ def test_get_clusters(self):
["sample_1", "sample_3", 1-1],
["sample_2", "sample_3", 1-0.9],
], orient="row", schema=SAMPLE_DISTANCES_COLUMNS)
samples = set(["sample_1", "sample_2", "sample_3"])

expected_clusters = pl.DataFrame([
["sample_1,sample_2"],
["sample_2,sample_3"],
], orient="row", schema=CLUSTERS_COLUMNS)

observed_clusters = get_clusters(sample_distances, samples)
self.assertDataFrameEqual(expected_clusters, observed_clusters)

def test_get_clusters_suffix(self):
sample_distances = pl.DataFrame([
["sample_1.1", "sample_2.1", 1-0.5],
["sample_1.1", "sample_3.1", 1-1],
["sample_2.1", "sample_3.1", 1-0.9],
], orient="row", schema=SAMPLE_DISTANCES_COLUMNS)
samples = set(["sample_1", "sample_2", "sample_3"])

expected_clusters = pl.DataFrame([
["sample_1,sample_2"],
["sample_2,sample_3"],
], orient="row", schema=CLUSTERS_COLUMNS)

observed_clusters = get_clusters(sample_distances)
observed_clusters = get_clusters(sample_distances, samples)
self.assertDataFrameEqual(expected_clusters, observed_clusters)

def test_get_clusters_suffix_underscore(self):
sample_distances = pl.DataFrame([
["sample_1_1", "sample_2_1", 1-0.5],
["sample_1_1", "sample_3_1", 1-1],
["sample_2_1", "sample_3_1", 1-0.9],
], orient="row", schema=SAMPLE_DISTANCES_COLUMNS)
samples = set(["sample_1", "sample_2", "sample_3"])

expected_clusters = pl.DataFrame([
["sample_1,sample_2"],
["sample_2,sample_3"],
], orient="row", schema=CLUSTERS_COLUMNS)

observed_clusters = get_clusters(sample_distances, samples)
self.assertDataFrameEqual(expected_clusters, observed_clusters)

def test_get_clusters_suffix_R(self):
sample_distances = pl.DataFrame([
["sample_1_R1", "sample_2_R1", 1-0.5],
["sample_1_R1", "sample_3_R1", 1-1],
["sample_2_R1", "sample_3_R1", 1-0.9],
], orient="row", schema=SAMPLE_DISTANCES_COLUMNS)
samples = set(["sample_1", "sample_2", "sample_3"])

expected_clusters = pl.DataFrame([
["sample_1,sample_2"],
["sample_2,sample_3"],
], orient="row", schema=CLUSTERS_COLUMNS)

observed_clusters = get_clusters(sample_distances, samples)
self.assertDataFrameEqual(expected_clusters, observed_clusters)

def test_get_clusters_size_three(self):
Expand All @@ -71,6 +120,7 @@ def test_get_clusters_size_three(self):
["1", "3", 1-1],
["2", "3", 1-0.9],
], orient="row", schema=SAMPLE_DISTANCES_COLUMNS)
samples = set(["1", "2", "3"])

expected_clusters = pl.DataFrame([
["1,2"],
Expand All @@ -81,6 +131,7 @@ def test_get_clusters_size_three(self):

observed_clusters = get_clusters(
sample_distances,
samples,
PRECLUSTER_SIZE=3,
MAX_COASSEMBLY_SAMPLES=3,
)
Expand All @@ -95,6 +146,7 @@ def test_get_clusters_size_three_of_four(self):
["2", "4", 1-0.4],
["3", "4", 1-1],
], orient="row", schema=SAMPLE_DISTANCES_COLUMNS)
samples = set(["1", "2", "3", "4"])

expected_clusters = pl.DataFrame([
["1,2"],
Expand All @@ -111,6 +163,7 @@ def test_get_clusters_size_three_of_four(self):

observed_clusters = get_clusters(
sample_distances,
samples,
PRECLUSTER_SIZE=3,
MAX_COASSEMBLY_SAMPLES=3,
)
Expand All @@ -122,6 +175,7 @@ def test_get_clusters_size_three_of_four_missing(self):
["1", "3", 1-0.2],
["2", "3", 1-0.2],
], orient="row", schema=SAMPLE_DISTANCES_COLUMNS)
samples = set(["1", "2", "3"])

expected_clusters = pl.DataFrame([
["1,2"],
Expand All @@ -138,6 +192,7 @@ def test_get_clusters_size_three_of_four_missing(self):

observed_clusters = get_clusters(
sample_distances,
samples,
PRECLUSTER_SIZE=3,
MAX_COASSEMBLY_SAMPLES=3,
)
Expand All @@ -152,6 +207,7 @@ def test_get_clusters_size_three_of_four_balanced(self):
["2", "4", 1-0.2],
["3", "4", 1-0.1],
], orient="row", schema=SAMPLE_DISTANCES_COLUMNS)
samples = set(["1", "2", "3", "4"])

expected_clusters = pl.DataFrame([
["1,2"],
Expand All @@ -168,6 +224,7 @@ def test_get_clusters_size_three_of_four_balanced(self):

observed_clusters = get_clusters(
sample_distances,
samples,
PRECLUSTER_SIZE=3,
MAX_COASSEMBLY_SAMPLES=3,
)
Expand All @@ -181,6 +238,7 @@ def test_get_clusters_size_three_of_four_balanced_missing(self):
["2", "4", 1-0.2],
["3", "4", 1-0.1],
], orient="row", schema=SAMPLE_DISTANCES_COLUMNS)
samples = set(["1", "2", "3", "4"])

expected_clusters = pl.DataFrame([
["1,2"],
Expand All @@ -197,6 +255,7 @@ def test_get_clusters_size_three_of_four_balanced_missing(self):

observed_clusters = get_clusters(
sample_distances,
samples,
PRECLUSTER_SIZE=3,
MAX_COASSEMBLY_SAMPLES=3,
)
Expand All @@ -215,6 +274,7 @@ def test_get_clusters_size_four_of_five(self):
["3", "5", 1-0.3],
["4", "5", 1-0.1],
], orient="row", schema=SAMPLE_DISTANCES_COLUMNS)
samples = set(["1", "2", "3", "4", "5"])

expected_clusters = pl.DataFrame([
["1,2"],
Expand All @@ -241,6 +301,7 @@ def test_get_clusters_size_four_of_five(self):

observed_clusters = get_clusters(
sample_distances,
samples,
PRECLUSTER_SIZE=4,
MAX_COASSEMBLY_SAMPLES=3,
)
Expand All @@ -258,6 +319,7 @@ def test_get_clusters_size_four_of_five_missing(self):
["3", "5", 1-0.3],
["4", "5", 1-0.1],
], orient="row", schema=SAMPLE_DISTANCES_COLUMNS)
samples = set(["1", "2", "3", "4", "5"])

expected_clusters = pl.DataFrame([
["1,2"],
Expand All @@ -284,6 +346,7 @@ def test_get_clusters_size_four_of_five_missing(self):

observed_clusters = get_clusters(
sample_distances,
samples,
PRECLUSTER_SIZE=4,
MAX_COASSEMBLY_SAMPLES=3,
)
Expand All @@ -301,6 +364,17 @@ def test_get_clusters_real_world(self):
["SRR4249921", "SRR5207344", 1-0.15],
["SRR6979552", "SRR6980357", 1-0.25],
], orient="row", schema=SAMPLE_DISTANCES_COLUMNS)
samples = set([
"SRR12149290", "SRR10571243",
"ERR3201415", "ERR3220216",
"ERR1414209", "ERR4804028",
"SRR6979552", "SRR15213103",
"SRR12149290", "SRR12352217",
"SRR6979552", "SRR4831657",
"ERR3201415", "SRR11784293",
"SRR4249921", "SRR5207344",
"SRR6979552", "SRR6980357",
])

expected_clusters = pl.DataFrame([
["SRR10571243,SRR12149290"],
Expand All @@ -314,17 +388,18 @@ def test_get_clusters_real_world(self):
["SRR6979552,SRR6980357"],
], orient="row", schema=CLUSTERS_COLUMNS)

observed_clusters = get_clusters(sample_distances)
observed_clusters = get_clusters(sample_distances, samples)
self.assertDataFrameEqual(expected_clusters, observed_clusters)

def test_get_clusters_empty_inputs(self):
sample_distances = pl.DataFrame([
], orient="row", schema=SAMPLE_DISTANCES_COLUMNS)
samples = set(["sample_1", "sample_2"])

expected_clusters = pl.DataFrame([
], orient="row", schema=CLUSTERS_COLUMNS)

observed_clusters = get_clusters(sample_distances)
observed_clusters = get_clusters(sample_distances, samples)
self.assertDataFrameEqual(expected_clusters, observed_clusters)

def test_target_elusive(self):
Expand Down

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