def test_external_db_mapping_transcript(self, new_pipegraph, mock_download,
shared_prebuild):
# the smallest eukaryotic species at the time of writing this at 2.8 mb
g = EnsemblGenome("Ustilago_maydis", 33, shared_prebuild)
ppg.run_pipegraph()
ena = g.get_external_db_to_gene_id_mapping("ENA_FEATURE_TRANSCRIPT")
assert ena["CM003155.1:CDS:9690..12623"] == set(["UMAG_05624"])
def test_same_same(self, new_pipegraph):
g = EnsemblGenome("Ustilago_maydis", 33)
g2 = EnsemblGenome("Ustilago_maydis", 33)
assert g is g2
new_pipegraph.new_pipegraph()
g3 = EnsemblGenome("Ustilago_maydis", 33)
assert g is not g3
def test_additional_fasta(self, mock_download, shared_prebuild):
g = EnsemblGenome("Ustilago_maydis", 33, shared_prebuild)
ppg.run_pipegraph()
seq = g.get_genome_sequence("U37796.1", 0, 100)
assert (seq == (
"taatcgtgaattgagctaggggcgccaagttacgtggcaaaagcgggctgactggcggcgaagatgtgt"
"tggtctgcacctgagttcacgaacctgagac").upper())
def test_get_additional_gene_gtfs_land_in_df_genes(self, mock_download,
shared_prebuild):
g = EnsemblGenome("Ustilago_maydis", 33, shared_prebuild)
assert len(g.get_additional_gene_gtfs()) == 1
ppg.run_pipegraph()
print(g.df_genes.chr.unique())
assert "A2_pra2" in g.df_genes.index
assert "A2_pra2.1" in g.df_transcripts.index
def test_external_db_mapping(self, new_pipegraph, mock_download,
shared_prebuild):
# the smallest eukaryotic species at the time of writing this at 2.8 mb
g = EnsemblGenome("Ustilago_maydis", 33, shared_prebuild)
ppg.run_pipegraph()
goa = g.get_external_db_to_gene_id_mapping("GOA")
assert goa["A0A0D1CJ64"] == set(["UMAG_05734"])
with pytest.raises(KeyError):
g.get_external_db_to_gene_id_mapping("GOAnosuchthing")
def test_external_db_mapping_translation(self, new_pipegraph,
mock_download, shared_prebuild):
# the smallest eukaryotic species at the time of writing this at 2.8 mb
g = EnsemblGenome("Ustilago_maydis", 33, shared_prebuild)
ppg.run_pipegraph()
up = g.get_external_db_to_gene_id_mapping("Uniprot/SWISSPROT")
assert up["P30598"] == set(["UMAG_10718"])
upp = g.get_external_db_to_translation_id_mapping("Uniprot/SWISSPROT")
assert upp["P30598"] == set(["KIS66849.N"])
def test_transcript_ids(self, mock_download, shared_prebuild):
# test that ustilago has at least one gene with multilpe transcripts
g = EnsemblGenome("Ustilago_maydis", 33, shared_prebuild)
ppg.run_pipegraph()
df = g.df_genes
assert (df.transcript_stable_ids.apply(lambda x: len(x)) > 1).any()
def test_outside_of_ppg_after_download(self, mock_download,
shared_prebuild):
species = "Ashbya_gossypii" # the smallest eukaryotic species at the time of writing this at 2.8 mb
g = EnsemblGenome(species, "41", prebuild_manager=shared_prebuild)
ppg.run_pipegraph()
len_genes = len(g.df_genes)
len_transcripts = len(g.df_transcripts)
len_proteins = len(g.df_proteins)
assert len_genes > 0
assert len_transcripts > 0
assert len_proteins > 0
ppg.util.global_pipegraph = None
g = EnsemblGenome(species, "41", prebuild_manager=shared_prebuild)
assert len_genes == len(g.df_genes)
assert len_transcripts == len(g.df_transcripts)
assert len_proteins == len(g.df_proteins)
def test_transcript_iterator(self, mock_download, shared_prebuild):
g = EnsemblGenome("Ashbya_gossypii", 41, shared_prebuild)
ppg.run_pipegraph()
transcripts = list(g.transcripts.values())
assert len(transcripts) == len(g.df_transcripts)
assert set([x.transcript_stable_id
for x in transcripts]) == set(g.df_transcripts.index)
def test_multiple_exon_transcripts(self, mock_download, shared_prebuild):
# test that ustilago has at least one transcript with multiple exons
g = EnsemblGenome("Ustilago_maydis", 33, shared_prebuild)
ppg.run_pipegraph()
df = g.df_transcripts
print(df.exons)
assert (df.exons.apply(lambda x: len(x)) > 1).any()
def test_df_exons(self, mock_download, shared_prebuild):
g = EnsemblGenome("Ustilago_maydis", 33, shared_prebuild)
ppg.run_pipegraph()
ppg.util.global_pipegraph.test_keep_output = True
ppg.util.global_pipegraph.dump_runtimes("logs/runtimes.txt")
exon_count = sum([len(x) for x in g.df_transcripts["exons"]])
df_exons = g.df_exons
assert len(df_exons) > 0
assert len(g.df_exons) == exon_count
assert hasattr(type(g).df_exons, "__call__")
def test_newest_gene_ids(self, new_pipegraph, mock_download,
shared_prebuild):
# the smallest eukaryotic species at the time of writing this at 2.8 mb
g = EnsemblGenome("Ustilago_maydis", 33, shared_prebuild)
ppg.run_pipegraph()
assert g.newest_stable_ids_for("UM05644") == set(["UMAG_05644"])
assert g.newest_stable_ids_for("UMAG_05629") == set(["UMAG_05629"])
assert g.newest_stable_ids_for("UM06501P0") == set([])
assert g.newest_stable_ids_for("UM04933T0") == set([])
with pytest.raises(KeyError):
g.newest_stable_ids_for("no_such_gene")
def test_get_true_chromosomes(self, mock_download, shared_prebuild):
# we need something with contigs and chromosomes
g = EnsemblGenome("Ustilago_maydis", 33, shared_prebuild)
ppg.run_pipegraph()
should = [
"1",
"2",
"3",
"4",
"5",
"6",
"7",
"8",
"9",
"10",
"11",
"12",
"13",
"14",
"15",
"16",
"17",
"18",
"19",
"20",
"21",
"22",
"23",
"U37796.1", # it is a true chromosome if there's chromosome: in the fasta description
]
all_contigs = should + [
"um_scaf_contig_1.256",
"um_scaf_contig_1.265",
"um_scaf_contig_1.271",
"um_scaf_contig_1.264",
]
assert set(g.get_true_chromosomes()) == set(should)
assert set(g.get_chromosome_lengths()) == set(should + all_contigs)
def test_get_external_dbs(self, new_pipegraph, mock_download,
shared_prebuild):
g = EnsemblGenome("Ustilago_maydis", 33, shared_prebuild)
ppg.run_pipegraph()
assert g.get_external_dbs() == [
"BRENDA",
"BioCyc",
"ChEMBL",
"ENA_FEATURE_GENE",
"ENA_FEATURE_PROTEIN",
"ENA_FEATURE_TRANSCRIPT",
"ENA_GENE",
"Ensembl_Fungi",
"GO",
"GOA",
"IntAct",
"IntEnz",
"Interpro",
"KEGG",
"KEGG_Enzyme",
"MEROPS",
"MINT",
"MetaCyc",
"NCBI_TAXONOMY",
"PHI",
"PHIE",
"PHIP",
"PRIDE",
"PUBMED",
"PeroxiBase",
"Reactome",
"SWISS_MODEL",
"UniParc",
"UniPathway",
"Uniprot/SPTREMBL",
"Uniprot/SWISSPROT",
"protein_id",
]
def test_transcript_sequence(self, shared_prebuild):
g = EnsemblGenome("Ustilago_maydis", 33, shared_prebuild)
ppg.run_pipegraph()
assert g.transcripts["KIS71708"].mrna == (
"ATGAACGTCAAGCTTGCGCCGCCCGACGAGATGAACGGCGAGATCATTGCCATCCTCATT"
"CTCTTCAACTTTCATTGCCGCGTTCAACTTAATGACGAGGCACAAGCCGCTCGCAAAAAG"
"TTGCTCCTCTTCCTCATGGACAAAATTTACCAGACACGCGCACCTGCGCCTTCGTATGCA"
"GCATTTGCAGACGAGCTCGGGGCCGCGATGGAAGGAGACGAGGACAATCACCGTATCATG"
"ACCGACTACCTCGAGACCATGCTCGATCTGCTCCATGTTCCCGATGGTTTGACCAAGCTG"
"TTCAACGAAAAGCTGAACAGAATCCTGCCTAGCTACGAGCCCATGGGATTGCTCAATGCC"
"ACCGACATCTTCTTCGAGCGAAGGTCCTTCTTCGGCCTCTTTTTCCGTCGCATCAAGTTG"
"ATCTTTGACAGTCTGGATTTGCAAACAAGGGATCACTTGACAATAGCTGCGCGCGCATGG"
"AAAGAGGGACAGGCTTTCGACTTGAATGACAGCGAGCTCTCCGGTATCGACTCGGCGCAT"
"TTGCTCGATGCAAGGCTTGGCGCGTTCCGAGACTACCAGCTTGGCTTACTCCGCGGCGAC"
"TATACCATGGCAAAGGACAACATGGAAAGGTTCTTTGACTTTTACGCTCCTGGCGCTGAC"
"CGCGAGCTTCATCAACACACGCTTCTTCATCTAGCCGCTTTCCATGTCAGGACTGAGAGC"
"TTCTGCGCAGCCAAAGCAGCCTTGGACGAGGCTATAAGCCTTGCGCGGTCGGCAAACGAC"
"AGCGAGTGCATCTCTGCCTGCGAGAGCCTCATGCAATACATCCAAGGTGTGGGCACTAGC"
"ACCCTCGCTTCTGTTCCGGGAGCAGCCAATGTCTCGACGAACGAGAGGCAACGCCGACCT"
"ATCTATGACGCGGTGTGGCAGACCCGTTGCAGCCTAGCTAAGGGCCGCTCAGCAATCGAG"
"ACACTTCAAGACTTGGAGGATTGTGCTGCACCTTCTCAGCCTTCTAGGGACTCGTTGGCG"
"GCCAGCGAGGCCTCCTTGCAGCTCATTCAGGATGCCAAACGACGTCTCGGCAGGGATACA"
"TTTCCAAGCGACGGTGAAGTCGCGCGTCTTTGGGATACCTTGGGCCAGCCAGCGCTTGCT"
"GACGTCTATCGGAATCGGAACATTGCAGGTGCAAATGGTCGAGCACGCTCAGCTTTGCAA"
"GAAGAAAGCCGAATCGATTGCATCTGTCACAAAGCCAAAACG"
"CTTGCACGTGCGGGAGAGTACGAAGCGGCGCTCAGCTTGCTGGTCTCACCGGCCACTTTC"
"GAAGCGATCTCATTCTGCGAGTACACGATCTGGCACAGGGCAATCGCTGAGGTCCTGCGC"
"TTACGAGCAACGCGCAGACAAGATGTAGCGACCTTGCAATTGTTGGCAGAGAGCCTGCCG"
"GGTTCCGACCAGGCTCATGTCGATCGCGACGTTGAAGATGCTGTCGATTCGCCGAGCGCT"
"TTGGTCGAGCTCGCGTTGCGCTGCCTCAAGTCCGGAAAATCGAGTGCGACTGAGAAGAAT"
"TTCGGATTGCGATTCAAAGAGTACAGCCGACTTACAGCAGAGCAAGTGGCAGAAGCGCTG"
"CTGAACAAAGCTGCGATAAGGATGAAACGTGGTCGACCGATCCTCGCACTGATGCCTACA"
"CTGGCAAGTCTATCGATTGCCAAGGACATGGAGTGCAATCGGTTGATCCTCAATGCAAGA"
"GTTCAGCTAGCTGAGGCATTGGGGCTTCAGCTCAAGATGCCAGATGGAGCACGGCTGCTC"
"TTGGAATCGGATCTGCCCAACTGCCTGTCGAGTGATGATGTCGAGCTGAGAGCGCGCGCG"
"AAGTGGACGTATGCACGGATGCTGCTCTCATGCTCGGACAAGCAAGAGCGCGAAGATCTG"
"ACCAAGGTGCTCTACTGGTTGCGAGAAGCCGAAAGAG"
"ACGCACAACAGGCCGAATGCCTCGAGCTTCACACGCAGATTCTCTACTATATGTTGCGGC"
"TGCACCACCACCTGGGCGATGACAGAGAAACAATCTCTGTGACAGCTCGTTTAGATACAG"
"TAGAGCGCGCTTGGACTCGCTTGGATGCTTCGCAGGATCAAGCCCATCTGCAACAGGTTC"
"GCCAAATCCTAGATATCGTTGTCTCTGTCGCAGGTTATGTGGCTAGCGGAGAAGCTGCGA"
"ACAAGCGTCTTGAAATGGTCTAG")
assert (g.transcripts["KIS71709"].mrna == "ATGGCATTTTCAGAAGATACCAAG"
"GAGCGAATCATTAAGGCGGTCGATGTCTCCAAGACTTTGTTGCATTACGGCTG"
"GGTGCCTTTCGTTCTTTACATCGGCTTCACCCGAAGCACGCCCCAGCCTAGCTTGATCAA"
"GCTCATCAGTCCTCTCGCATGA")
assert g.transcripts["KIS71709"].mrna == g.transcripts["KIS71709"].cdna
def test_all_transcripts(self, mock_download, shared_prebuild):
g = EnsemblGenome("Ustilago_maydis", 33, shared_prebuild)
ppg.run_pipegraph()
df = g.df_transcripts
assert "gene_stable_id" in df.columns
assert len(df) == 6928 + 4 # from the a2 locus
assert df["chr"].dtype.name == "category"
assert df["biotype"].dtype.name == "category"
assert df.loc["KIS71021"].chr == "2"
assert df.loc["KIS71021"].strand == 1
assert df.loc["KIS71021"].start == 354_742
assert df.loc["KIS71021"].stop == 356_690
assert df.loc["KIS71021"].gene_stable_id == "UMAG_12118"
assert df.loc["KIS71021"].biotype == "protein_coding"
assert df.loc["KIS71021"].exons == ((354_742, 354_936), (355_222,
356_690))
assert df.loc["KIS71021"].exon_stable_ids == ("KIS71021-1",
"KIS71021-2")
def test_all_genes(self, mock_download, shared_prebuild):
g = EnsemblGenome("Ustilago_maydis", 33, shared_prebuild)
ppg.run_pipegraph()
df = g.df_genes
df2 = g.df_genes # caching
assert len(df) == 6910 + 4 # from the a2 locus
assert df is df2
assert df.loc["UMAG_12015"].strand == 1
assert df.loc["UMAG_12015"].tss == 4370
assert df.loc["UMAG_12015"].tes == 5366
assert df.loc["UMAG_12015"].transcript_stable_ids == ("KIS66832", )
assert df.loc["UMAG_00663"].strand == -1
assert df.loc["UMAG_00663"].tss == 1_947_590
assert df.loc["UMAG_00663"].tes == 1_945_040
assert df.loc["UMAG_00663"].transcript_stable_ids == ("KIS72250", )
assert df.loc["UMAG_03168"].transcript_stable_ids == ("KIS68597",
"KIS68596")
assert df["chr"].dtype.name == "category"
assert df["biotype"].dtype.name == "category"
def test_download(self, new_pipegraph, mock_download, shared_prebuild):
species = "Ashbya_gossypii" # the smallest eukaryotic species at the time of writing this at 2.8 mb
g = EnsemblGenome(species, "41", prebuild_manager=shared_prebuild)
def shorten_genome_fasta(output_path):
with open(g.find_file("genome.fasta")) as op:
head = op.read(1024 * 100)
(output_path / "test.fasta").write_text(head)
test_fasta_job = g.prebuild_manager.prebuild(
f"ensembl/{g.species}_{g.revision}/test_fasta",
"1",
[],
["test.fasta"],
shorten_genome_fasta,
)
test_fasta_job.depends_on(g.download_genome())
g._prebuilds.append(test_fasta_job)
subread = Subread(version="1.6.3")
index = g.build_index(subread, "test.fasta")
subread_old = Subread(version="1.4.3-p1")
index_old = g.build_index(subread_old, "test.fasta")
new_pipegraph.run()
# note that these are not the checksums from CHECKSUMS files (those are fore
# the gziped variants, we keep them ungziped and let the filesystem handle
# the gzip, since we can't rely on the downstream reading gzip...
assert (checksum_file(
g.find_file("genome.fasta")) == "584a734589964a654c7c1dc23b0167ab")
assert (checksum_file(
g.find_file("cdna.fasta")) == "3fc1f19ab829573169cb2488abe39211")
assert (checksum_file(
g.find_file("genes.gtf")) == "8bdeec9b3db5278668dbff8b34e9d93b")
assert (checksum_file(
g.find_file("genes.gtf")) == "8bdeec9b3db5278668dbff8b34e9d93b")
assert (checksum_file(
g.find_file("pep.fasta")) == "9580fd44832d419c38469d657f6e2484")
with pytest.raises(OSError):
g.find_file("no such file")
assert index.name_file("subread_index.reads").exists()
assert index.name_file("subread_index.files").exists()
assert index.name_file("subread_index.00.b.array").exists()
assert index_old.name_file("subread_index.reads").exists()
assert index_old.name_file("subread_index.files").exists()
assert index_old.name_file("subread_index.00.b.array").exists()
assert index.name_file("subread_index.reads") != index_old.name_file(
"subread_index.reads")
assert g.find_file("test.fasta.md5sum").exists()
with pytest.raises(OSError):
assert g.find_file("test.fasta.md5sum.nosuchfile").exists()
assert g.find_prebuild("test.fasta") is test_fasta_job
with pytest.raises(OSError):
assert g.find_prebuild("test.fasta.md5sum.nosuchfile").exists()
assert g.find_file("genome.fasta.fai").exists()
assert g.find_file("cdna.fasta.fai").exists()
new_pipegraph.new_pipegraph()
pb = PrebuildManager(shared_prebuild.prebuilt_path)
g = EnsemblGenome(species, "41", prebuild_manager=pb)
test_fasta_job = g.prebuild_manager.prebuild(
f"ensembl/{g.species}_{g.revision}/test_fasta",
"1",
[],
["test.fasta"],
shorten_genome_fasta,
)
g._prebuilds.append(test_fasta_job)
subread_intermediate = Subread(version="1.5.0")
index_intermediate = g.build_index(subread_intermediate, "test.fasta")
assert index_intermediate.name_file(
"subread_index.reads") == index_old.name_file(
"subread_index.reads")
index_genome = g.build_index(subread_intermediate)
assert "/genome/" in str(index_genome.filenames[0])
assert g.get_chromosome_lengths() == {
"IV": 1_467_287,
"MT": 23564,
"V": 1_519_140,
"III": 907_494,
"II": 870_771,
"VII": 1_800_949,
"I": 693_414,
"VI": 1_836_693,
}
assert g.get_genome_sequence("VI", 20, 30) == "ACCGCTGAGA"
assert (g.get_cdna_sequence("EFAGOT00000000349") ==
"GCTCGCGTGGCGTAATGGCAACGCGTCTGACTTCTAATCAGAAGATTGTGGGTTCGACCC"
"CCACCGTGAGTG")
assert (g.get_protein_sequence("AAS53315") ==
"MFSTRICSLLARPFMVPIVPRFGSALLQKPLNGVVVPQFTRGFKVRTSVKKFCAHCYIVR"
"RKGRVYVYCKSNNKHKQRQG")
assert (g.genetic_code.translate_dna(g.get_cds_sequence("AAS53315")) ==
"MFSTRICSLLARPFMVPIVPRFGSALLQKPLNGVVVPQFTRGFKVRTSVKKFCAHCYIVR"
"RKGRVYVYCKSNNKHKQRQG")
assert (g.genetic_code.translate_dna(
g.get_cds_sequence("AAS53315", g.df_proteins.loc["AAS53315"])) ==
"MFSTRICSLLARPFMVPIVPRFGSALLQKPLNGVVVPQFTRGFKVRTSVKKFCAHCYIVR"
"RKGRVYVYCKSNNKHKQRQG")
with pytest.raises(ValueError):
g.get_cds_sequence("AAS53315", g.df_proteins.loc["AAS53316"])
assert (
g.df_genes_meta.loc["AGOS_ADL186C"]["description"] ==
"Restriction of telomere capping protein 1 [Source:UniProtKB/Swiss-Prot;Acc:Q75AV6]"
)
def test_species_formating(self, shared_prebuild):
species = "ashbya_gossypii" # the smallest eukaryotic species at the time of writing this at 2.8 mb
with pytest.raises(ValueError):
EnsemblGenome(species, "41", prebuild_manager=shared_prebuild)
def test_unknown_species_raises(self, mock_download, shared_prebuild):
species = "Unknown_unknown" # the smallest eukaryotic species at the time of writing this at 2.8 mb
EnsemblGenome(species, "41",
prebuild_manager=shared_prebuild).download_genome()
with pytest.raises(ppg.RuntimeError):
ppg.run_pipegraph()
def test_get_canonical_ids(self, new_pipegraph, mock_download,
shared_prebuild):
g = EnsemblGenome("Homo_sapiens", 96, shared_prebuild)
g._pb_find_server().callback()
g._pb_download_sql_table("gene").callback()
g._pb_download_sql_table("alt_allele").callback()
g._pb_download_sql_table("seq_region").callback()
g._pb_download_sql_table("seq_region_attrib").callback()
g._pb_download_sql_table("attrib_type").callback()
g._pb_download_gtf().callback()
g._pb_download_sql_table_definitions().callback()
g.job_genes().callback()
g.job_transcripts().callback()
assert g.name_to_canonical_id("DSEL") == "ENSG00000171451"
assert g.name_to_canonical_id("THEMIS") == "ENSG00000172673"
# test the breakage
with pytest.raises(ValueError):
g.name_to_canonical_id("SOD2")
with pytest.raises(ValueError):
g.name_to_canonical_id("IGF2")
with pytest.raises(ValueError):
g.name_to_canonical_id("ABCF2")
with pytest.raises(ValueError):
g.name_to_canonical_id("TBCE")
assert g.name_to_canonical_id("SOD2", True) == "ENSG00000112096"
assert g.name_to_canonical_id("IGF2", True) == "ENSG00000167244"
assert g.name_to_canonical_id("ABCF2", True) == "ENSG00000033050"
assert g.name_to_canonical_id("TBCE", True) == "ENSG00000284770"
def test_all_proteins(self, mock_download, shared_prebuild):
g = EnsemblGenome("Ustilago_maydis", 33, shared_prebuild)
ppg.run_pipegraph()
df = g.df_proteins
assert df.strand.isin([1, -1]).all()
def test_get_additional_gene_gtfs(self, mock_download, shared_prebuild):
g = EnsemblGenome("Ashbya_gossypii", 33, shared_prebuild)
assert len(g.get_additional_gene_gtfs()) == 0
g = EnsemblGenome("Homo_sapiens", 74, shared_prebuild)
assert "ribosomal_genes_grch37" in g.get_additional_gene_gtfs()[0].name
assert g.get_additional_gene_gtfs()[0].exists()
g = EnsemblGenome("Homo_sapiens", 75, shared_prebuild)
assert "ribosomal_genes_grch38" in g.get_additional_gene_gtfs()[0].name
assert g.get_additional_gene_gtfs()[0].exists()
g = EnsemblGenome("Mus_musculus", 68, shared_prebuild)
assert "ribosomal_genes_mm10" in g.get_additional_gene_gtfs()[0].name
assert g.get_additional_gene_gtfs()[0].exists()
g = EnsemblGenome("Mus_musculus", 67, shared_prebuild)
assert len(g.get_additional_gene_gtfs()) == 0
def test_genes_iterator(self, mock_download, shared_prebuild):
g = EnsemblGenome("Ashbya_gossypii", 41, shared_prebuild)
ppg.run_pipegraph()
genes = list(g.genes.values())
assert len(genes) == len(g.df_genes)
assert set([x.gene_stable_id for x in genes]) == set(g.df_genes.index)
def test_get_true_chromosomes_genome_without_chromosomes(
self, mock_download, shared_prebuild):
# we need something with contigs and chromosomes
g = EnsemblGenome("Giardia_lamblia", 43, shared_prebuild)
ppg.run_pipegraph()
should = [
"ctg02_1",
"ctg02_2",
"ctg02_3",
"ctg02_4",
"ctg02_5",
"ctg02_6",
"ctg02_7",
"ctg02_8",
"ctg02_9",
"ctg02_10",
"ctg02_11",
"ctg02_12",
"ctg02_13",
"ctg02_14",
"ctg02_15",
"ctg02_16",
"ctg02_17",
"ctg02_18",
"ctg02_19",
"ctg02_20",
"ctg02_21",
"ctg02_22",
"ctg02_23",
"ctg02_24",
"ctg02_25",
"ctg02_26",
"ctg02_27",
"ctg02_28",
"ctg02_29",
"ctg02_30",
"ctg02_31",
"ctg02_32",
"ctg02_33",
"ctg02_34",
"ctg02_35",
"ctg02_36",
"ctg02_37",
"ctg02_38",
"ctg02_39",
"ctg02_40",
"ctg02_41",
"ctg02_42",
"ctg02_43",
"ctg02_44",
"ctg02_45",
"ctg02_46",
"ctg02_47",
"ctg02_48",
"ctg02_49",
"ctg02_50",
"ctg02_51",
"ctg02_52",
"ctg02_53",
"ctg02_54",
"ctg02_55",
"ctg02_56",
"ctg02_57",
"ctg02_58",
"ctg02_59",
"ctg02_60",
"ctg02_61",
"ctg02_62",
"ctg02_63",
"ctg02_64",
"ctg02_65",
"ctg02_66",
"ctg02_67",
"ctg02_68",
"ctg02_69",
"ctg02_70",
"ctg02_71",
"ctg02_72",
"ctg02_73",
"ctg02_74",
"ctg02_75",
"ctg02_76",
"ctg02_77",
"ctg02_78",
"ctg02_79",
"ctg02_80",
"ctg02_81",
"ctg02_82",
"ctg02_83",
"ctg02_84",
"ctg02_85",
"ctg02_86",
"ctg02_87",
"ctg02_88",
"ctg02_89",
"ctg02_90",
"ctg02_91",
"ctg02_92",
"ctg02_93",
"ctg02_94",
"ctg02_95",
"ctg02_96",
"ctg02_97",
"ctg02_99",
"ctg02_98",
"ctg02_100",
"ctg02_101",
"ctg02_102",
"ctg02_103",
"ctg02_104",
"ctg02_105",
"ctg02_106",
"ctg02_107",
"ctg02_108",
"ctg02_109",
"ctg02_110",
"ctg02_111",
"ctg02_112",
"ctg02_113",
"ctg02_114",
"ctg02_115",
"ctg02_116",
"ctg02_117",
"ctg02_118",
"ctg02_120",
"ctg02_119",
"ctg02_121",
"ctg02_122",
"ctg02_123",
"ctg02_124",
"ctg02_125",
"ctg02_127",
"ctg02_126",
"ctg02_129",
"ctg02_128",
"ctg02_130",
"ctg02_131",
"ctg02_132",
"ctg02_133",
"ctg02_134",
"ctg02_135",
"ctg02_136",
"ctg02_137",
"ctg02_138",
"ctg02_139",
"ctg02_140",
"ctg02_141",
"ctg02_142",
"ctg02_144",
"ctg02_143",
"ctg02_145",
"ctg02_146",
"ctg02_147",
"ctg02_148",
"ctg02_149",
"ctg02_151",
"ctg02_150",
"ctg02_152",
"ctg02_153",
"ctg02_155",
"ctg02_154",
"ctg02_157",
"ctg02_156",
"ctg02_158",
"ctg02_159",
"ctg02_160",
"ctg02_161",
"ctg02_162",
"ctg02_163",
"ctg02_164",
"ctg02_165",
"ctg02_167",
"ctg02_168",
"ctg02_166",
"ctg02_169",
"ctg02_170",
"ctg02_171",
"ctg02_172",
"ctg02_174",
"ctg02_176",
"ctg02_175",
"ctg02_178",
"ctg02_177",
"ctg02_179",
"ctg02_180",
"ctg02_181",
"ctg02_183",
"ctg02_182",
"ctg02_184",
"ctg02_185",
"ctg02_186",
"ctg02_187",
"ctg02_188",
"ctg02_189",
"ctg02_190",
"ctg02_191",
"ctg02_193",
"ctg02_192",
"ctg02_194",
"ctg02_196",
"ctg02_195",
"ctg02_197",
"ctg02_198",
"ctg02_200",
"ctg02_199",
"ctg02_201",
"ctg02_202",
"ctg02_203",
"ctg02_204",
"ctg02_206",
"ctg02_208",
"ctg02_207",
"ctg02_205",
"ctg02_209",
"ctg02_210",
"ctg02_211",
"ctg02_212",
"ctg02_214",
"ctg02_213",
"ctg02_215",
"ctg02_216",
"ctg02_220",
"ctg02_218",
"ctg02_221",
"ctg02_217",
"ctg02_219",
"ctg02_223",
"ctg02_222",
"ctg02_224",
"ctg02_225",
"ctg02_226",
"ctg02_227",
"ctg02_228",
"ctg02_229",
"ctg02_231",
"ctg02_230",
"ctg02_232",
"ctg02_234",
"ctg02_235",
"ctg02_233",
"ctg02_237",
"ctg02_238",
"ctg02_236",
"ctg02_239",
"ctg02_241",
"ctg02_240",
"ctg02_242",
"ctg02_245",
"ctg02_243",
"ctg02_246",
"ctg02_244",
"ctg02_247",
"ctg02_249",
"ctg02_250",
"ctg02_248",
"ctg02_252",
"ctg02_251",
"ctg02_253",
"ctg02_254",
"ctg02_255",
"ctg02_256",
"ctg02_257",
"ctg02_258",
"ctg02_259",
"ctg02_260",
"ctg02_173",
"ctg02_261",
"ctg02_262",
"ctg02_263",
"ctg02_266",
"ctg02_265",
"ctg02_268",
"ctg02_264",
"ctg02_267",
"ctg02_269",
"ctg02_271",
"ctg02_270",
"ctg02_273",
"ctg02_272",
"ctg02_274",
"ctg02_275",
"ctg02_276",
"ctg02_277",
"ctg02_278",
"ctg02_279",
"ctg02_280",
"ctg02_282",
"ctg02_281",
"ctg02_283",
"ctg02_284",
"ctg02_285",
"ctg02_286",
"ctg02_287",
"ctg02_289",
"ctg02_288",
"ctg02_290",
"ctg02_291",
"ctg02_292",
"ctg02_293",
"ctg02_294",
"ctg02_295",
"ctg02_296",
"ctg02_297",
"ctg02_298",
"ctg02_299",
"ctg02_300",
"ctg02_301",
"ctg02_302",
"ctg02_303",
"ctg02_304",
"ctg02_305",
"ctg02_306",
]
assert set(g.get_true_chromosomes()) == set(should)
assert set(g.get_true_chromosomes()) == set(g.get_chromosome_lengths())
def test_download_jobs_called_init(self, new_pipegraph, mock_download,
shared_prebuild):
species = "Ashbya_gossypii" # the smallest eukaryotic species at the time of writing this at 2.8 mb
g = EnsemblGenome(species, "41", prebuild_manager=shared_prebuild)
g.find_prebuild("genome.fasta") # this is the actual test.