def setup(cls, config, in_container):
with codecs.open(os.path.dirname(os.path.abspath(__file__)) +
"/../VERSION",
"r",
encoding="utf-8") as inp:
cls.sVersionCode = inp.read().strip()
cls.sConfig = config
MirrorUiDirectory.setup(cls.sConfig.get("mirror-ui"))
IntUI.setup(config, in_container)
cls.sMongoConn = MongoConnector(cls.sConfig["mongo-db"],
cls.sConfig.get("mongo-host"),
cls.sConfig.get("mongo-port"))
if cls.sConfig.get("link-base") is not None:
AttrH.setupLinkBase(*cls.sConfig["link-base"])
cls.sDruidAgent = DruidAgent(cls.sConfig)
cls.sDataVault = DataVault(cls, cls.sConfig["data-vault"],
cls.sConfig.get("default-ws"),
cls.sConfig.get("default-xl"))
cls.sJobPool = JobPool(AnfisaConfig.configOption("job.pool.threads"),
AnfisaConfig.configOption("job.pool.size"))
signal.signal(signal.SIGTERM, terminateAll)
signal.signal(signal.SIGHUP, terminateAll)
signal.signal(signal.SIGINT, terminateAll)
def __init__(self, view, ds_h):
AttrH.__init__(self,
"OP_filters",
title="Presence in filters",
tooltip="Filters positive on variant")
self.mDS = ds_h
self.setAspect(view)
def __init__(self, view):
AttrH.__init__(self,
"BEACONS",
title="Beacons",
tooltip="Search what other organizations have "
"observed the same variant")
self.setAspect(view)
def __init__(self, view, ds_h):
AttrH.__init__(self,
"OP_dtrees",
title="Presence in decision trees",
tooltip="Decision trees positive on variant")
self.mDS = ds_h
self.setAspect(view)
def __init__(self, view, ds_h):
AttrH.__init__(self,
"OP_has_variant",
title="Has variant",
tooltip="Samples having variant")
self.mDS = ds_h
self.mFamilyInfo = self.mDS.getFamilyInfo()
self.setAspect(view)
def regAspect(self, asp_h):
asp_checker = None
if asp_h.getColGroups() is None:
if asp_h.getField() is not None:
if asp_h.getMode() == "dict":
asp_checker = DictTypeChecker(asp_h.getField(),
self.getName(),
base_asp=asp_h)
self.mAspectCheckers.append(asp_checker)
elif asp_h.getMode() == "string":
attr_h = AttrH(asp_h.getField())
asp_checker = AttrTypeChecker(asp_h.getField(), attr_h)
self.regIt(asp_checker)
else:
asp_checker = self
assert self.mBaseAsp is None
self.mBaseAsp = asp_h
else:
attr_names = asp_h.getColGroups().getAttrNames()
asp_checker = ColGroupTypeChecker(asp_h.getTitle(), self.getName(),
asp_h)
for nm in attr_names:
self.regIt(asp_checker, nm)
self.mAspectCheckers.append(asp_checker)
for attr_h in asp_h.getAttrs():
asp_checker.addAttr(attr_h)
def fixUp(self, master, rep_output, no_mode=False):
self.mOwnCnt.fixType(no_mode=no_mode)
if self.mOwnCnt.getErrorCount() > 0:
master.problem("fatal", self)
self.mStatus = "fatal"
else:
self.mStatus = "ok"
for a_check in self.mChildren:
if not isinstance(a_check, AttrTypeChecker):
a_check.fixUp(master, rep_output, no_mode=no_mode)
continue
a_type = a_check.fixType(no_mode=no_mode)
if a_check.getBaseAttr() is None:
if a_check.getName().startswith('_'):
a_check.setStatus("skipped")
continue
a_seq, a_kind = a_type
assert a_type is not None
if self.mBaseAsp:
self.mBaseAsp.addAttr(
AttrH(a_check.getName(), a_kind, is_seq=a_seq))
master.problem("added", a_check, self)
a_check.setStatus("added")
else:
master.problem("lost", a_check, self)
a_check.setStatus("lost")
else:
if self.mBaseAsp is None:
# lack of accuracy
continue
attr_h = a_check.getBaseAttr()
if a_type is None:
if (not attr_h.hasKind("place")
and not attr_h.hasKind("posted")):
self.mBaseAsp.delAttr(attr_h)
master.problem("empty", a_check, self)
a_check.setStatus("empty")
else:
a_seq, a_kind = a_type
if (a_check.getErrorCount() > 0
or a_seq != attr_h.isSeq()):
print("Update field %s.%s:" %
(self.mName, a_check.getName()),
attr_h.getMainKind(),
"is_seq=",
attr_h.isSeq(),
"->",
a_kind,
"is_seq=",
a_seq,
"errors=",
a_check.getErrorCount(),
file=rep_output)
attr_h.reset(a_kind, a_seq)
master.problem("updated", a_check, self)
a_check.setStatus("updated")
else:
a_check.setStatus("ok")
class IGV_AttrH(AttrH):
def __init__(self, app, view_gen, case, samples, reference):
bam_base = app.getOption("http-bam-base")
AttrH.__init__(self,
"IGV",
kind="hidden" if bam_base is None else None)
self.mBase = "hg38" if reference and "38" in reference else "hg19"
self.setAspect(view_gen)
if bam_base is None:
self.mPreUrl = None
return
# we are not sure what is the key to samples, so have to repackage
samples = {info["id"]: info["name"] for info in samples.values()}
samples_ids = sorted(samples)
samples_names = [samples[id] for id in samples_ids]
file_urls = ','.join([
"%s/%s/%s.%s.bam" % (bam_base, case, sample_id, self.mBase)
for sample_id in samples_ids
])
class IGV_AttrH(AttrH):
def __init__(self, app, view_gen, case, samples, reference):
bam_base = app.getOption("http-bam-base")
AttrH.__init__(self,
"IGV",
kind="hidden" if bam_base is None else None)
self.mBase = "hg38" if reference and "38" in reference else "hg19"
self.setAspect(view_gen)
if bam_base is None:
self.mPreUrl = None
return
# we are not sure what is the key to samples, so have to repackage
samples = {info["id"]: info["name"] for info in samples.values()}
samples_ids = sorted(samples.keys())
samples_names = ",".join([samples[id] for id in samples_ids])
file_urls = ','.join([
f"{bam_base}/{case}/{sample_id}.{self.mBase}.bam"
for sample_id in samples_ids
])
self.mPreUrl = (
f"http://localhost:60151/load?file={file_urls}"
f"&genome={self.mBase}&merge=false&name={samples_names}")
def __init__(self, view, name, title, tooltip):
AttrH.__init__(self, name, title=title, tooltip=tooltip)
self.setAspect(view)
def __init__(self, view):
AttrH.__init__(self,
"GENE_CARDS",
title="GeneCards",
tooltip="Read GeneCards")
self.setAspect(view)
def __init__(self, view):
AttrH.__init__(self, "MEDGEN", title="MedGen", tooltip="Search MedGen")
self.setAspect(view)
def getViewSetupReport(self):
return {
"aspects": self.mAspects.dump(),
"opts": AttrH.getJSonOptions()
}
def defFavorView(metadata_record):
assert metadata_record.get("data_schema") == "FAVOR"
aspect_list = [
AspectH("view_bas", "Basic", "_view", field="general"),
AspectH("view_variant_category",
"Variant Category",
"_view",
field="variant_category"),
AspectH("view_allele_frequencies",
"Frequencies",
"_view",
field="allele_frequencies"),
AspectH("view_integrative_score",
"Score",
"_view",
field="integrative_score"),
AspectH("view_protein_function",
"Protein Function",
"_view",
field="protein_function"),
AspectH("view_conservation",
"Conservation",
"_view",
field="conservation"),
AspectH("view_epigenetics",
"Epigenetics",
"_view",
col_groups=ColGroupsH([["epigenetics", None]])),
AspectH("view_transcription_factors",
"Transcription Factors",
"_view",
field="transcription_factors"),
AspectH("view_chromatin_states",
"Chromatin States",
"_view",
field="chromatin_states"),
AspectH("view_local_nucleotide_diversity",
"Nucleotide Diversity",
"_view",
field="local_nucleotide_diversity"),
AspectH("view_mutation_rate",
"Mutation Rate",
"_view",
field="mutation_rate"),
AspectH("view_mappability",
"Mappability",
"_view",
field="mappability"),
AspectH("_main", "VEP Data", "__data")
]
aspects = AspectSetH(aspect_list)
aspects["view_bas"].setAttributes([
AttrH("type",
title="Variant Type",
kind="string",
tooltip="Type of variant"),
AttrH("gene_panels", title="Gene panels", is_seq=True),
AttrH("rsID", kind="string"),
AttrH("TOPMed_Depth", kind="string"),
AttrH("TOPMed_QC_Status", kind="string"),
AttrH("TOPMed_Bravo_AF", kind="string"),
AttrH("GNOMAD_Total_AF", kind="string"),
AttrH("ALL_1000G_AF", kind="string")
])
aspects["view_variant_category"].setAttributes([
AttrH("GENCODE_Category", title="GENCODE Category", kind="string"),
AttrH("GENCODE_Exonic_Category", kind="string"),
AttrH("GENCODE_Exonic_Info", kind="string"),
AttrH("GENCODE_Info", kind="string"),
AttrH("CAGE_Enhancer", kind="string"),
AttrH("CAGE_Promoter", kind="string"),
AttrH("ClinVar", kind="string"),
AttrH("Disruptive_Missense", kind="string"),
AttrH("GeneHancer", kind="string"),
AttrH("SuperEnhancer", kind="string")
])
aspects["view_allele_frequencies"].setAttributes([
AttrH("AFR_1000G_AF", kind="string"),
AttrH("ALL_1000G_AF", kind="string"),
AttrH("AMR_1000G_AF", kind="string"),
AttrH("EAS_1000G_AF", kind="string"),
AttrH("ESP_AA", kind="string"),
AttrH("ESP_ALL", kind="string"),
AttrH("ESP_EA", kind="string"),
AttrH("EUR_1000G_AF", kind="string"),
AttrH("ExAC03", kind="string"),
AttrH("ExAC03_nontcga", kind="string"),
AttrH("GNOMAD_Total_AF", kind="string"),
AttrH("SAS_1000G_AF", kind="string"),
AttrH("TOPMed_Bravo_AF", kind="string")
])
aspects["view_integrative_score"].setAttributes([
AttrH("LINSIGHT", title="LINSIGHT", kind="string"),
AttrH("gc", title="GC", kind="string"),
AttrH("cpg", title="CpG", kind="string"),
AttrH("APC_Conservation", kind="string"),
AttrH("APC_Epigenetics", kind="string"),
AttrH("APC_Local_Nucleotide_Diversity", kind="string"),
AttrH("APC_MapAbility", kind="string"),
AttrH("APC_MutationDensity", kind="string"),
AttrH("APC_ProteinFunction", kind="string"),
AttrH("APC_Proximity_To_TSSTES", kind="string"),
AttrH("APC_TranscriptionFactor", kind="string"),
AttrH("CADD_PHRED", kind="string"),
AttrH("CADD_RawScore", kind="string"),
AttrH("FATHMM_XF_coding", kind="string"),
AttrH("FATHMM_XF_noncoding", kind="string")
])
aspects["view_protein_function"].setAttributes([
AttrH("APC_ProteinFunction",
title="APC ProteinFunction",
kind="string"),
AttrH("Grantham", kind="string"),
AttrH("MutationAssessor", kind="string"),
AttrH("MutationTaster", kind="string"),
AttrH("PolyPhenCat", kind="string"),
AttrH("PolyPhenVal", kind="string"),
AttrH("SIFTcat", kind="string"),
AttrH("SIFTval", kind="string"),
AttrH("polyphen2_hdiv", kind="string"),
AttrH("polyphen2_hdiv_score", kind="string"),
AttrH("polyphen2_hvar", kind="string"),
AttrH("polyphen2_hvar_score", kind="string")
])
aspects["view_conservation"].setAttributes([
AttrH("APC_Conservation", title="APC Conservation", kind="string"),
AttrH("GerpN", kind="string"),
AttrH("GerpS", kind="string"),
AttrH("mamPhCons", kind="string"),
AttrH("mamPhyloP", kind="string"),
AttrH("priPhCons", kind="string"),
AttrH("priPhyloP", kind="string"),
AttrH("verPhCons", kind="string"),
AttrH("verPhyloP", kind="string"),
])
aspects["view_epigenetics"].setAttributes([
AttrH("APC_Epigenetics", kind="string", title="APC Epigenetics"),
AttrH("DNase", kind="string"),
AttrH("H2AFZ", kind="string"),
AttrH("H3K27ac", kind="string"),
AttrH("H3K27me3", kind="string"),
AttrH("H3K36me3", kind="string"),
AttrH("H3K4me1", kind="string"),
AttrH("H3K4me2", kind="string"),
AttrH("H3K4me3", kind="string"),
AttrH("H3K79me2", kind="string"),
AttrH("H3K9ac", kind="string"),
AttrH("H3K9me3", kind="string"),
AttrH("H4K20me1", kind="string"),
AttrH("totalRNA", kind="string")
])
aspects["view_transcription_factors"].setAttributes([
AttrH("APC_TranscriptionFactor",
kind="string",
title="APC TranscriptionFactor"),
AttrH("OverlapCL", kind="string"),
AttrH("OverlapTF", kind="string")
])
aspects["view_chromatin_states"].setAttributes([
AttrH("cHmm_E1", title="cHmm E1", kind="string"),
AttrH("cHmm_E2", title="cHmm E2", kind="string"),
AttrH("cHmm_E3", title="cHmm E3", kind="string"),
AttrH("cHmm_E4", title="cHmm E4", kind="string"),
AttrH("cHmm_E5", title="cHmm E5", kind="string"),
AttrH("cHmm_E6", title="cHmm E6", kind="string"),
AttrH("cHmm_E7", title="cHmm E7", kind="string"),
AttrH("cHmm_E8", title="cHmm E8", kind="string"),
AttrH("cHmm_E9", title="cHmm E9", kind="string"),
AttrH("cHmm_E10", title="cHmm E10", kind="string"),
AttrH("cHmm_E11", title="cHmm E11", kind="string"),
AttrH("cHmm_E12", title="cHmm E12", kind="string"),
AttrH("cHmm_E13", title="cHmm E13", kind="string"),
AttrH("cHmm_E14", title="cHmm E14", kind="string"),
AttrH("cHmm_E15", title="cHmm E15", kind="string"),
AttrH("cHmm_E16", title="cHmm E16", kind="string"),
AttrH("cHmm_E17", title="cHmm E17", kind="string"),
AttrH("cHmm_E18", title="cHmm E18", kind="string"),
AttrH("cHmm_E19", title="cHmm E19", kind="string"),
AttrH("cHmm_E20", title="cHmm E20", kind="string"),
AttrH("cHmm_E21", title="cHmm E21", kind="string"),
AttrH("cHmm_E22", title="cHmm E22", kind="string"),
AttrH("cHmm_E23", title="cHmm E23", kind="string"),
AttrH("cHmm_E24", title="cHmm E24", kind="string"),
AttrH("cHmm_E25", title="cHmm E25", kind="string")
])
aspects["view_local_nucleotide_diversity"].setAttributes([
AttrH("APC_Local_Nucleotide_Diversity",
kind="string",
title="APC Local Nucleotide Diversity"),
AttrH("NucDiv", kind="string"),
AttrH("RecRate", kind="string"),
AttrH("bStatistics", kind="string"),
])
aspects["view_mutation_rate"].setAttributes([
AttrH("APC_MutationDensity",
kind="string",
title="APC MutationDensity"),
AttrH("Freq1000bp", kind="string"),
AttrH("Rare1000bp", kind="string"),
AttrH("Sngl1000bp", kind="string")
])
aspects["view_mappability"].setAttributes([
AttrH("APC_MapAbility", kind="string", title="APC MapAbility"),
AttrH("Bismap_k100", kind="string"),
AttrH("Bismap_k24", kind="string"),
AttrH("Bismap_k50", kind="string"),
AttrH("Umap_k100", kind="string"),
AttrH("Umap_k24", kind="string"),
AttrH("Umap_k50", kind="string")
])
aspects["_main"].setAttributes([AttrH("label"), AttrH("color_code")])
return aspects
def __init__(self, view):
AttrH.__init__(self,
"REFERENCES",
title="Found in PubMed",
tooltip="PubMed Abstracts")
self.setAspect(view)
def __init__(self, view):
AttrH.__init__(self,
"HGMD_PMIDs",
title="HGMD PMIDs",
tooltip="PubMed Abstracts (from HGMD)")
self.setAspect(view)
def defineViewSchema():
aspects = AspectSetH([
AspectH("view_gen", "General", "view", field="general"),
AspectH("view_qsamples",
"Quality",
"view",
col_groups=ColGroupsH(attr="quality_samples")),
AspectH("view_gnomAD",
"gnomAD",
"view",
col_groups=ColGroupsH(attr="gnomAD")),
AspectH("view_db", "Databases", "view", field="databases"),
AspectH("view_pred", "Predictions", "view", field="predictions"),
AspectH("view_genetics",
"Bioinformatics",
"view",
field="bioinformatics"),
AspectH("view_inheritance",
"Inheritance",
"view",
field="inheritance",
ignored=True),
AspectH("_main", "VEP Data", "data"),
AspectH("transcripts",
"VEP Transcripts",
"data",
col_groups=ColGroupsH([
("transcript_consequences", "Transcript"),
("regulatory_feature_consequences", "Regulatory"),
("motif_feature_consequences", "Motif"),
("intergenic_consequences", "Intergenic")
])),
AspectH("colocated_v",
"Colocated Variants",
"data",
col_groups=ColGroupsH(attr="colocated_variants")),
AspectH("input", "VCF", "data", field="input", mode="string")
])
aspects["view_gen"].setAttributes([
AttrH("genes",
title="Gene(s)",
is_seq=True,
tooltip="Gene Symbol (Ensembl classification)"),
AttrH("hg19", tooltip="Genetic coordinates in HG19 Assembly"),
AttrH("hg38", tooltip="Genetic coordinates in HG38 Assembly"),
AttrH("worst_annotation",
title="Worst Annotation",
tooltip="Most Severe Consequences from the transcript" +
" with the worst annotation"),
AttrH("canonical_annotation",
title="Canonical Annotation",
tooltip="Most Severe Consequences from canonical transcripts"),
AttrH("refseq_transcript_canonical",
title="RefSeq Transcript (Canonical)",
is_seq=True),
AttrH("refseq_transcript_worst",
title="RefSeq Transcript (Worst)",
is_seq=True),
AttrH("ensembl_transcripts_canonical",
title="Ensembl Transcripts (Canonical)",
is_seq=True),
AttrH("ensembl_transcripts_worst",
title="Ensembl Transcripts (Worst)",
is_seq=True),
AttrH("ref", title="Ref"),
AttrH("alt", title="Alt"),
AttrH("splice_region", title="Splice Region", is_seq=True),
AttrH("gene_splicer", title="GeneSplicer", is_seq=True),
AttrH("splice_altering", title="Splice AI splice altering"),
AttrH("cpos_worst", title="cPos (Worst)", is_seq=True),
AttrH("cpos_canonical", title="cPos (Canonical)", is_seq=True),
AttrH("cpos_other", title="cPos (Other)", is_seq=True),
AttrH("ppos_worst", title="pPos (Worst)", is_seq=True),
AttrH("ppos_canonical", title="pPos (Canonical)", is_seq=True),
AttrH("ppos_other", title="pPos (Other)", is_seq=True),
AttrH("variant_exon_canonical",
title="Variant Exon (Canonical)",
is_seq=True,
tooltip="Exon # according to canonical transcript"),
AttrH("variant_exon_worst",
title="Variant Exon (Worst Annotation)",
is_seq=True,
tooltip="Exon # according to the transcript with " +
"the worst annotation"),
AttrH("variant_intron_worst",
title="Variant Intron (Worst Annotation)",
is_seq=True,
tooltip="Intron # according to the transcript with " +
"the worst annotation"),
AttrH("variant_intron_canonical",
title="Variant Intron (Canonical)",
is_seq=True,
tooltip="Intron # according to canonical transcript"),
AttrH("gene_panels", title="Gene panels", is_seq=True),
AttrH(None),
AttrH("proband_genotype", title="Proband Genotype"),
AttrH("maternal_genotype", title="Maternal Genotype"),
AttrH("paternal_genotype", title="Paternal Genotype"),
AttrH("igv",
title="IGV",
kind="place",
tooltip="Open this variant in local IGV "
"(https://software.broadinstitute.org/software/igv/)"),
AttrH("ucsc",
title="View in UCSC",
kind="place",
tooltip="View this variant in UCSC Browser")
])
aspects["view_qsamples"].setAttributes([
AttrH("title", title="Title"),
AttrH("qd",
title="Quality by Depth",
tooltip="The QUAL score normalized by allele depth (AD) "
"for a variant. This annotation puts the variant confidence "
"QUAL score into perspective by normalizing for the amount "
"of coverage available. Because each read contributes a little "
"to the QUAL score, variants in regions with deep coverage "
"can have artificially inflated QUAL scores, giving the "
"impression that the call is supported by more evidence "
"than it really is. To compensate for this, we normalize "
"the variant confidence by depth, which gives us a more "
"objective picture of how well supported the call is."),
AttrH("mq", title="Mapping Quality"),
AttrH("variant_call_quality",
title="Variant Call Quality",
tooltip="QUAL tells you how confident we are that there is "
"some kind of variation at a given site. The variation may be "
"present in one or more samples."),
AttrH("strand_odds_ratio", title="Strand Odds Ratio", tooltip=""),
AttrH("fs", title="Fisher Strand Bias", tooltip=""),
AttrH(
"allelic_depth",
title="Allelic Depth",
is_seq=True,
tooltip="AD is the unfiltered allele depth, i.e. "
"the number of reads that support each of the reported "
"alleles. All reads at the position (including reads that "
"did not pass the variant caller's filters) are included in "
"this number, except reads that were considered uninformative. "
"Reads are considered uninformative when they do not provide "
"enough statistical evidence to support one allele over another."),
AttrH("read_depth",
title="Read Depth",
tooltip="DP - is a number of times that base pair locus "
"was read"),
AttrH("ft",
title="FILTERs",
tooltip="This field contains the name(s) of any filter(s) "
"that the variant fails to pass, or the value PASS if the "
"variant passed all filters. If the FILTER value is ., "
"then no filtering has been applied to the records."),
AttrH("genotype_quality",
title="Genotype Quality",
tooltip="GQ tells you how confident we are that "
"the genotype we assigned to a particular sample is correct. "
"It is simply the second lowest PL, because it is the "
"difference between the second lowest PL and the lowest PL "
"(always 0).")
])
aspects["view_gnomAD"].setAttributes([
AttrH("allele", title="Allele"),
AttrH("proband", title="Proband"),
AttrH("pli", title="pLI", is_seq=True),
AttrH("af", title="Overall AF"),
AttrH("genome_af", title="Genome AF"),
AttrH("exome_af", title="Exome AF"),
AttrH("hem", title="Number of homozygotes"),
AttrH("hom", title="Number of hemizygotes"),
AttrH("genome_an", title="Genome AN"),
AttrH("exome_an", title="Exome AN"),
AttrH("url", title="URL", kind="link", is_seq=True),
AttrH(
"pop_max",
title="PopMax",
)
])
aspects["view_db"].setAttributes([
AttrH("hgmd", title="HGMD"),
AttrH("hgmd_hg38", title="HGMD (HG38)"),
AttrH("hgmd_tags", title="HGMD TAGs", is_seq=True),
AttrH("hgmd_phenotypes", title="HGMD Phenotypes", is_seq=True),
AttrH("hgmd_pmids", title="HGMD PMIDs", is_seq=True, kind="link"),
AttrH("omim", title="OMIM", is_seq=True, kind="place"),
AttrH("clinVar_variants", title="ClinVar Variants", is_seq=True),
AttrH("clinVar_significance",
title="ClinVar Significance",
is_seq=True),
AttrH("clinvar_review_status",
title="ClinVar Review Status",
is_seq=False),
AttrH("num_clinvar_submitters",
title="ClinVar: Number of submitters",
is_seq=False),
AttrH("clinvar_acmg_guidelines",
title="ClinVar ACMG Guidelines",
is_seq=True),
AttrH("lmm_significance", title="Clinical Significance by LMM"),
AttrH("gene_dx_significance", title="Clinical Significance by GeneDx"),
AttrH("clinVar_phenotypes", title="ClinVar Phenotypes", is_seq=True),
AttrH("clinVar_submitters", title="ClinVar Submitters", is_seq=True),
AttrH("clinVar", title="ClinVar", is_seq=True, kind="link"),
AttrH(
"gtex",
kind="place",
),
AttrH("gene_cards", title="GeneCards", is_seq=True, kind="link"),
AttrH("grev", is_seq=True, kind="place"),
AttrH("medgen", is_seq=True, kind="place"),
AttrH("pubmed_search",
title="PubMed Search Results",
is_seq=True,
kind="link"),
AttrH("beacons", title="Observed at", is_seq=True),
AttrH("beacon_url", title="Search Beacons", is_seq=True, kind="link")
])
aspects["view_pred"].setAttributes([
AttrH("lof_score", title="LoF Score", is_seq=True),
AttrH("lof_score_canonical",
title="LoF Score (Canonical)",
is_seq=True),
AttrH("max_ent_scan", title="MaxEntScan", is_seq=True),
AttrH("polyphen", title="Polyphen", is_seq=True),
AttrH("polyphen2_hvar", title="Polyphen 2 HVAR", is_seq=True),
AttrH("polyphen2_hdiv", title="Polyphen 2 HDIV", is_seq=True),
AttrH("sift", title="SIFT from dbNSFP", is_seq=True),
AttrH("sift_vep", title="SIFT from VEP", is_seq=True),
AttrH("revel", title="REVEL", is_seq=True),
AttrH("mutation_taster", title="Mutation Taster", is_seq=True),
AttrH("fathmm", title="FATHMM", is_seq=True),
AttrH("cadd_phred", title="CADD (Phred)", is_seq=True),
AttrH("cadd_raw", title="CADD (Raw)", is_seq=True),
AttrH("mutation_assessor", title="Mutation Assessor", is_seq=True),
AttrH("sift_score", title="SIFT score", is_seq=True),
AttrH("polyphen2_hvar_score",
title="Polyphen 2 HVAR score",
is_seq=True),
AttrH("polyphen2_hdiv_score",
title="Polyphen 2 HDIV score",
is_seq=True)
])
aspects["view_genetics"].setAttributes([
AttrH("zygosity", title="Zygosity"),
AttrH("inherited_from", title="Inherited from"),
AttrH("dist_from_exon_worst",
title="Distance From Intron/Exon Boundary (Worst)",
is_seq=True),
AttrH("dist_from_exon_canonical",
title="Distance From Intron/Exon Boundary (Canonical)",
is_seq=True),
AttrH("gerp_rs", title="GERP Score", is_seq=False),
AttrH("conservation", title="Conservation", kind="json"),
AttrH("species_with_variant", title="Species with variant"),
AttrH("species_with_others", title="Species with other variants"),
AttrH("max_ent_scan", title="MaxEntScan", is_seq=True),
AttrH("nn_splice", title="NNSplice"),
AttrH("human_splicing_finder", title="Human Splicing Finder"),
#AttrH("splice_ai", title = "Splice AI Max Score"),
AttrH("splice_ai_ag", title="Splice AI acceptor gain", is_seq=True),
AttrH("splice_ai_al", title="Splice AI acceptor loss", is_seq=True),
AttrH("splice_ai_dg", title="Splice AI donor gain", is_seq=True),
AttrH("splice_ai_dl", title="Splice AI donor loss", is_seq=True),
AttrH("splice_ai", kind="hidden"),
AttrH("other_genes",
title="Gene symbols from other transcripts",
is_seq=True),
AttrH("called_by", title="Called by", is_seq=True),
AttrH("caller_data", title="CALLER DATA")
])
aspects["_main"].setAttributes([
AttrH("label"),
AttrH("color_code"),
AttrH("id"),
AttrH("assembly_name", title="Assembly"),
AttrH("seq_region_name"),
AttrH("start"),
AttrH("end"),
AttrH("strand"),
AttrH("allele_string"),
AttrH("variant_class"),
AttrH("most_severe_consequence"),
AttrH("ClinVar"),
AttrH("clinvar_variants", is_seq=True),
AttrH("clinvar_phenotypes", is_seq=True),
AttrH("clinvar_significance", is_seq=True),
AttrH("HGMD"),
AttrH("HGMD_HG38"),
AttrH("HGMD_PIMIDs", kind="hidden", is_seq=True),
AttrH("HGMD_phenotypes", kind="hidden", is_seq=True),
AttrH("EXPECTED"),
AttrH("gnomad_db_genomes_af", kind="hidden"),
AttrH("gnomad_db_exomes_af", kind="hidden"),
AttrH("SEQaBOO")
])
aspects["transcripts"].setAttributes([
AttrH("amino_acids"),
AttrH("bam_edit"),
AttrH("biotype"),
AttrH("cadd_phred"),
AttrH("cadd_raw"),
AttrH("canonical"),
AttrH("ccds"),
AttrH("cdna_end"),
AttrH("cdna_start"),
AttrH("cds_end"),
AttrH("cds_start"),
AttrH("clinvar_clnsig"),
AttrH("clinvar_rs"),
AttrH("codons"),
AttrH("consequence_terms", is_seq=True),
AttrH("conservation"),
AttrH("distance"),
AttrH("domains", kind="json"),
AttrH("exacpli"),
AttrH("exon"),
AttrH("fathmm_pred"),
AttrH("fathmm_score"),
AttrH("flags", is_seq=True),
AttrH("gene_id"),
AttrH("gene_pheno"),
AttrH("genesplicer"),
AttrH("gene_symbol"),
AttrH("gene_symbol_source"),
AttrH("given_ref"),
AttrH("gnomad_exomes_ac"),
AttrH("gnomad_exomes_af"),
AttrH("gnomad_exomes_an"),
AttrH("gnomad_exomes_asj_af"),
AttrH("gnomad_genomes_ac"),
AttrH("gnomad_genomes_af"),
AttrH("gnomad_genomes_an"),
AttrH("gnomad_genomes_asj_af"),
AttrH("hgnc_id"),
AttrH("hgvs_offset"),
AttrH("hgvsc"),
AttrH("hgvsp"),
AttrH("high_inf_pos"),
AttrH("impact"),
AttrH("intron"),
AttrH("loftool"),
AttrH("maxentscan_alt"),
AttrH("maxentscan_diff"),
AttrH("maxentscan_ref"),
AttrH("motif_feature_id"),
AttrH("motif_name"),
AttrH("motif_pos"),
AttrH("motif_score_change"),
AttrH("mutationassessor_pred"),
AttrH("mutationassessor_score"),
AttrH("mutationtaster_pred"),
AttrH("mutationtaster_score"),
AttrH("polyphen2_hdiv_pred"),
AttrH("polyphen2_hdiv_score"),
AttrH("polyphen2_hvar_pred"),
AttrH("polyphen2_hvar_score"),
AttrH("polyphen_prediction"),
AttrH("polyphen_score"),
AttrH("protein_end"),
AttrH("protein_id"),
AttrH("protein_start"),
AttrH("regulatory_feature_id"),
AttrH("revel_score"),
AttrH("sift_pred"),
AttrH("sift_prediction"),
AttrH("sift_score"),
AttrH("strand"),
AttrH("source"),
AttrH("spliceregion", is_seq=True),
AttrH("swissprot", is_seq=True),
AttrH("transcript_id"),
AttrH("trembl", is_seq=True),
AttrH("uniparc", is_seq=True),
AttrH("used_ref"),
AttrH("variant_allele")
])
aspects["colocated_v"].setAttributes([
AttrH("id"),
AttrH("start"),
AttrH("end"),
AttrH("allele_string"),
AttrH("strand"),
AttrH("pubmed", is_seq=True),
AttrH("somatic"),
AttrH("gnomAD"),
AttrH("frequencies", kind="json"),
AttrH("phenotype_or_disease"),
AttrH("seq_region_name"),
AttrH("clin_sig", is_seq=True),
AttrH("minor")
])
return aspects
def __init__(self, view, key, is_simple):
AttrH.__init__(self, key.upper(), title=key.title())
self.setAspect(view)
self.key = key
self.simple = is_simple
def defineViewSchema():
aspects = AspectSetH([
AspectH("view_gen", "General", "view", field="general"),
AspectH("view_qsamples",
"Quality",
"view",
col_groups=ColGroupsH(attr="quality_samples")),
AspectH("view_gnomAD",
"gnomAD",
"view",
col_groups=ColGroupsH(attr="gnomAD")),
AspectH("view_db", "Databases", "view", field="databases"),
AspectH("view_pred", "Predictions", "view", field="predictions"),
AspectH("view_genetics",
"Bioinformatics",
"view",
field="bioinformatics"),
AspectH("view_inheritance",
"Inheritance",
"view",
field="inheritance",
ignored=True),
AspectH("_main", "VEP Data", "data"),
AspectH("transcripts",
"VEP Transcripts",
"data",
col_groups=ColGroupsH([
("intergenic_consequences", "Intergenic"),
("motif_feature_consequences", "Motif"),
("regulatory_feature_consequences", "Regulatory"),
("transcript_consequences", "Transcript")
])),
AspectH("colocated_v",
"Colocated Variants",
"data",
col_groups=ColGroupsH(attr="colocated_variants")),
AspectH("input", "VCF", "data", field="input", mode="string")
])
aspects["view_gen"].setAttributes([
AttrH("genes", title="Gene(s)", is_seq=True),
AttrH("hg19"),
AttrH("hg38"),
AttrH("worst_annotation", title="Worst Annotation"),
AttrH("canonical_annotation", title="Canonical Annotation"),
AttrH("refseq_transcript_canonical",
title="RefSeq Transcript (Canonical)",
is_seq=True),
AttrH("refseq_transcript_worst",
title="RefSeq Transcript (Worst)",
is_seq=True),
AttrH("ensembl_transcripts_canonical",
title="Ensembl Transcripts (Canonical)",
is_seq=True),
AttrH("ensembl_transcripts_worst",
title="Ensembl Transcripts (Worst)",
is_seq=True),
AttrH("ref", title="Ref"),
AttrH("alt", title="Alt"),
AttrH("splice_region", title="Splice Region", is_seq=True),
AttrH("gene_splicer", title="GeneSplicer", is_seq=True),
AttrH("cpos_worst", title="cPos (Worst)", is_seq=True),
AttrH("cpos_canonical", title="cPos (Canonical)", is_seq=True),
AttrH("cpos_other", title="cPos (Other)", is_seq=True),
AttrH("ppos_worst", title="pPos (Worst)", is_seq=True),
AttrH("ppos_canonical", title="pPos (Canonical)", is_seq=True),
AttrH("ppos_other", title="pPos (Other)", is_seq=True),
AttrH("variant_exon_canonical",
title="Variant Exon (Canonical)",
is_seq=True),
AttrH("variant_exon_worst",
title="Variant Exon (Worst Annotation)",
is_seq=True),
AttrH("variant_intron_worst",
title="Variant Intron (Worst Annotation)",
is_seq=True),
AttrH("variant_intron_canonical",
title="Variant Intron (Canonical)",
is_seq=True),
AttrH(None),
AttrH("proband_genotype", title="Proband Genotype"),
AttrH("maternal_genotype", title="Maternal Genotype"),
AttrH("paternal_genotype", title="Paternal Genotype"),
AttrH("igv", title="IGV", kind="link")
])
aspects["view_qsamples"].setAttributes([
AttrH("title", title="Title"),
AttrH("qd", title="Quality by Depth"),
AttrH("mq", title="Mapping Quality"),
AttrH("variant_call_quality", title="Variant Call Quality"),
AttrH("strand_odds_ratio", title="Strand Odds Ratio"),
AttrH("fs", title="Fisher Strand Bias"),
AttrH("allelic_depth", title="Allelic Depth", is_seq=True),
AttrH("read_depth", title="Read Depth"),
AttrH("ft", title="FILTERs"),
AttrH("genotype_quality", title="Genotype Quality")
])
aspects["view_gnomAD"].setAttributes([
AttrH("allele", title="Allele"),
AttrH("proband", title="Proband"),
AttrH("pli", title="pLI", is_seq=True),
AttrH("af", title="Overall AF"),
AttrH("genome_af", title="Genome AF"),
AttrH("exome_af", title="Exome AF"),
AttrH("genome_an", title="Genome AN"),
AttrH("exome_an", title="Exome AN"),
AttrH("url", title="URL", kind="link", is_seq=True),
AttrH(
"pop_max",
title="PopMax",
)
])
aspects["view_db"].setAttributes([
AttrH("hgmd", title="HGMD"),
AttrH("hgmd_hg38", title="HGMD (HG38)"),
AttrH("hgmd_tags", title="HGMD TAGs", is_seq=True),
AttrH("hgmd_phenotypes", title="HGMD Phenotypes", is_seq=True),
AttrH("hgmd_pmids", title="HGMD PMIDs", is_seq=True, kind="link"),
AttrH("omim", title="OMIM", is_seq=True, kind="link"),
AttrH("clinVar_variants", title="ClinVar Variants", is_seq=True),
AttrH("clinVar_significance",
title="ClinVar Significance",
is_seq=True),
AttrH("lmm_significance", title="Clinical Significance by LMM"),
AttrH("gene_dx_significance", title="Clinical Significance by GeneDx"),
AttrH("clinVar_phenotypes", title="ClinVar Phenotypes", is_seq=True),
AttrH("clinVar_submitters", title="ClinVar Submitters", is_seq=True),
AttrH("clinVar", title="ClinVar", is_seq=True, kind="link"),
AttrH("gene_cards", title="GeneCards", is_seq=True, kind="link"),
AttrH("pubmed_search",
title="PubMed Search Results",
is_seq=True,
kind="link"),
AttrH("beacons", title="Observed at", is_seq=True),
AttrH("beacon_url", title="Search Beacons", is_seq=True, kind="link")
])
aspects["view_pred"].setAttributes([
AttrH("lof_score", title="LoF Score", is_seq=True),
AttrH("lof_score_canonical",
title="LoF Score (Canonical)",
is_seq=True),
AttrH("max_ent_scan", title="MaxEntScan", is_seq=True),
AttrH("polyphen", title="Polyphen", is_seq=True),
AttrH("polyphen2_hvar", title="Polyphen 2 HVAR", is_seq=True),
AttrH("polyphen2_hdiv", title="Polyphen 2 HDIV", is_seq=True),
AttrH("sift", title="SIFT", is_seq=True),
AttrH("revel", title="REVEL", is_seq=True),
AttrH("mutation_taster", title="Mutation Taster", is_seq=True),
AttrH("fathmm", title="FATHMM", is_seq=True),
AttrH("cadd_phred", title="CADD (Phred)", is_seq=True),
AttrH("cadd_raw", title="CADD (Raw)", is_seq=True),
AttrH("mutation_assessor", title="Mutation Assessor", is_seq=True),
AttrH("sift_score", title="SIFT score", is_seq=True),
AttrH("polyphen2_hvar_score",
title="Polyphen 2 HVAR score",
is_seq=True),
AttrH("polyphen2_hdiv_score",
title="Polyphen 2 HDIV score",
is_seq=True)
])
aspects["view_genetics"].setAttributes([
AttrH("zygosity", title="Zygosity"),
AttrH("inherited_from", title="Inherited from"),
AttrH("dist_from_exon_worst",
title="Distance From Intron/Exon Boundary (Worst)",
is_seq=True),
AttrH("dist_from_exon_canonical",
title="Distance From Intron/Exon Boundary (Canonical)",
is_seq=True),
AttrH("conservation", title="Conservation", is_seq=True),
AttrH("species_with_variant", title="Species with variant"),
AttrH("species_with_others", title="Species with other variants"),
AttrH("max_ent_scan", title="MaxEntScan", is_seq=True),
AttrH("nn_splice", title="NNSplice"),
AttrH("human_splicing_finder", title="Human Splicing Finder"),
AttrH("other_genes",
title="Gene symbols from other transcripts",
is_seq=True),
AttrH("called_by", title="Called by", is_seq=True),
AttrH("caller_data", title="CALLER DATA")
])
aspects["_main"].setAttributes([
AttrH("label"),
AttrH("color_code"),
AttrH("id"),
AttrH("assembly_name", title="Assembly"),
AttrH("seq_region_name"),
AttrH("start"),
AttrH("end"),
AttrH("strand"),
AttrH("allele_string"),
AttrH("variant_class"),
AttrH("most_severe_consequence"),
AttrH("ws_compound_heterosygotes"),
AttrH("ClinVar"),
AttrH("clinvar_variants", is_seq=True),
AttrH("clinvar_phenotypes", is_seq=True),
AttrH("clinvar_significance", is_seq=True),
AttrH("HGMD"),
AttrH("HGMD_HG38"),
AttrH("HGMD_PIMIDs", kind="hidden", is_seq=True),
AttrH("HGMD_phenotypes", kind="hidden", is_seq=True),
AttrH("EXPECTED"),
AttrH("gnomad_db_genomes_af", kind="hidden"),
AttrH("gnomad_db_exomes_af", kind="hidden"),
AttrH("SEQaBOO")
])
aspects["transcripts"].setAttributes([
AttrH("amino_acids"),
AttrH("bam_edit"),
AttrH("biotype"),
AttrH("cadd_phred"),
AttrH("cadd_raw"),
AttrH("canonical"),
AttrH("ccds"),
AttrH("cdna_end"),
AttrH("cdna_start"),
AttrH("cds_end"),
AttrH("cds_start"),
AttrH("clinvar_clnsig"),
AttrH("clinvar_rs"),
AttrH("codons"),
AttrH("consequence_terms", is_seq=True),
AttrH("conservation"),
AttrH("distance"),
AttrH("domains", kind="json"),
AttrH("exacpli"),
AttrH("exon"),
AttrH("fathmm_pred"),
AttrH("fathmm_score"),
AttrH("flags", is_seq=True),
AttrH("gene_id"),
AttrH("gene_pheno"),
AttrH("genesplicer"),
AttrH("gene_symbol"),
AttrH("gene_symbol_source"),
AttrH("given_ref"),
AttrH("gnomad_exomes_ac"),
AttrH("gnomad_exomes_af"),
AttrH("gnomad_exomes_an"),
AttrH("gnomad_exomes_asj_af"),
AttrH("gnomad_genomes_ac"),
AttrH("gnomad_genomes_af"),
AttrH("gnomad_genomes_an"),
AttrH("gnomad_genomes_asj_af"),
AttrH("hgnc_id"),
AttrH("hgvs_offset"),
AttrH("hgvsc"),
AttrH("hgvsp"),
AttrH("high_inf_pos"),
AttrH("impact"),
AttrH("intron"),
AttrH("loftool"),
AttrH("maxentscan_alt"),
AttrH("maxentscan_diff"),
AttrH("maxentscan_ref"),
AttrH("motif_feature_id"),
AttrH("motif_name"),
AttrH("motif_pos"),
AttrH("motif_score_change"),
AttrH("mutationassessor_pred"),
AttrH("mutationassessor_score"),
AttrH("mutationtaster_pred"),
AttrH("mutationtaster_score"),
AttrH("polyphen2_hdiv_pred"),
AttrH("polyphen2_hdiv_score"),
AttrH("polyphen2_hvar_pred"),
AttrH("polyphen2_hvar_score"),
AttrH("polyphen_prediction"),
AttrH("polyphen_score"),
AttrH("protein_end"),
AttrH("protein_id"),
AttrH("protein_start"),
AttrH("regulatory_feature_id"),
AttrH("revel_score"),
AttrH("sift_pred"),
AttrH("sift_prediction"),
AttrH("sift_score"),
AttrH("strand"),
AttrH("source"),
AttrH("spliceregion", is_seq=True),
AttrH("swissprot", is_seq=True),
AttrH("transcript_id"),
AttrH("trembl", is_seq=True),
AttrH("uniparc", is_seq=True),
AttrH("used_ref"),
AttrH("variant_allele")
])
aspects["colocated_v"].setAttributes([
AttrH("id"),
AttrH("start"),
AttrH("end"),
AttrH("allele_string"),
AttrH("strand"),
AttrH("pubmed", is_seq=True),
AttrH("somatic"),
AttrH("gnomAD"),
AttrH("frequencies", kind="json"),
AttrH("phenotype_or_disease"),
AttrH("seq_region_name"),
AttrH("clin_sig", is_seq=True),
AttrH("minor")
])
return aspects
def __init__(self, view):
AttrH.__init__(self,
"UNIPROT_ACC",
title="Uniprot",
tooltip="View on Uniprot site")
self.setAspect(view)
def __init__(self, view):
AttrH.__init__(self,
"GTEx",
title="View on GTEx",
tooltip="View this gene on GTEx portal")
self.setAspect(view)
def __init__(self, view_gen):
AttrH.__init__(self, "UCSC")
self.setAspect(view_gen)
def __init__(self, view):
AttrH.__init__(self, "OMIM")
self.setAspect(view)
def defineViewSchema(metadata_record=None):
data_schema = (metadata_record.get("data_schema")
if metadata_record else None)
if data_schema == "FAVOR":
return FavorSchema.defineViewSchema(metadata_record)
assert data_schema is None or data_schema == "CASE", ("Bad data schema: " +
data_schema)
aspect_list = [
AspectH("view_gen", "General", "_view", field="general"),
AspectH("view_transcripts",
"Transcripts",
"_view",
col_groups=ColGroupsH([("transcripts", "Transcripts")])),
AspectH("view_qsamples",
"Quality",
"_view",
col_groups=ColGroupsH([["quality_samples", None]])),
AspectH("view_gnomAD", "gnomAD", "_view", field="gnomAD"),
AspectH("view_db", "Databases", "_view", field="databases"),
AspectH("view_pred", "Predictions", "_view", field="predictions"),
AspectH("view_pharmagkb",
"Pharmacogenomics",
"_view",
field="pharmacogenomics"),
AspectH("view_genetics",
"Bioinformatics",
"_view",
field="bioinformatics")
]
cohorts = metadata_record.get("cohorts") if metadata_record else None
if cohorts:
cohort_columns = [[
"ALL", "ALL"
]] + [[ch["name"], ch.get("title", ch["name"])] for ch in cohorts]
aspect_list.append(
AspectH("view_cohorts",
"Cohorts",
"_view",
field="cohorts",
col_groups=ColGroupsH(attr_title_pairs=cohort_columns,
single_group_col=True)))
aspect_list += [
AspectH("view_inheritance",
"Inheritance",
"_view",
field="inheritance",
ignored=True),
AspectH("_main", "VEP Data", "__data"),
AspectH("transcripts",
"VEP Transcripts",
"__data",
col_groups=ColGroupsH([
("transcript_consequences", "Transcript"),
("regulatory_feature_consequences", "Regulatory"),
("motif_feature_consequences", "Motif"),
("intergenic_consequences", "Intergenic")
])),
AspectH("colocated_v",
"Colocated Variants",
"__data",
col_groups=ColGroupsH([["colocated_variants", None]])),
AspectH("input", "VCF", "__data", field="input", mode="string")
]
aspects = AspectSetH(aspect_list)
aspects["view_gen"].setAttributes([
AttrH("genes",
title="Gene(s)",
is_seq=True,
tooltip="Gene Symbol (Ensembl classification)"),
AttrH("hg19", tooltip="Genetic coordinates in HG19 Assembly"),
AttrH("hg38", tooltip="Genetic coordinates in HG38 Assembly"),
AttrH("worst_annotation",
title="Worst Annotation",
tooltip="Most Severe Consequences from the transcript" +
" with the worst annotation"),
AttrH("canonical_annotation",
title="Canonical Annotations",
is_seq=True,
tooltip="Most Severe Consequences from canonical transcripts"),
AttrH("refseq_transcript_canonical",
title="RefSeq Transcript (Canonical)",
is_seq=True),
AttrH("refseq_transcript_worst",
title="RefSeq Transcript (Worst)",
is_seq=True),
AttrH("ensembl_transcripts_canonical",
title="Ensembl Transcripts (Canonical)",
is_seq=True),
AttrH("ensembl_transcripts_worst",
title="Ensembl Transcripts (Worst)",
is_seq=True),
AttrH("ref", title="Ref"),
AttrH("original_ref", title="Denormalized Ref in VCF"),
AttrH("alt", title="Alt"),
AttrH("original_alt", title="Denormalized Alt in VCF"),
AttrH("mostly_expressed", title="Mostly expressed in", is_seq=True),
AttrH("splice_region", title="Splice Region", is_seq=True),
AttrH("gene_splicer", title="GeneSplicer", is_seq=True),
AttrH("splice_altering", title="Splice AI splice altering"),
AttrH("cpos_worst", title="cPos (Worst)", is_seq=True),
AttrH("cpos_canonical", title="cPos (Canonical)", is_seq=True),
AttrH("cpos_other", title="cPos (Other)", is_seq=True),
AttrH("ppos_worst", title="pPos (Worst)", is_seq=True),
AttrH("ppos_canonical", title="pPos (Canonical)", is_seq=True),
AttrH("ppos_other", title="pPos (Other)", is_seq=True),
AttrH("variant_exon_canonical",
title="Variant Exon (Canonical)",
is_seq=True,
tooltip="Exon # according to canonical transcript"),
AttrH("variant_exon_worst",
title="Variant Exon (Worst Annotation)",
is_seq=True,
tooltip="Exon # according to the transcript with "
"the worst annotation"),
AttrH("variant_intron_worst",
title="Variant Intron (Worst Annotation)",
is_seq=True,
tooltip="Intron # according to the transcript with "
"the worst annotation"),
AttrH("variant_intron_canonical",
title="Variant Intron (Canonical)",
is_seq=True,
tooltip="Intron # according to canonical transcript"),
AttrH("gene_panels", title="Gene panels", is_seq=True),
AttrH(None),
AttrH("proband_genotype", title="Proband Genotype"),
AttrH("maternal_genotype", title="Maternal Genotype"),
AttrH("paternal_genotype", title="Paternal Genotype"),
AttrH("igv",
title="IGV",
kind="place",
tooltip="Open this variant in local IGV "
"(https://software.broadinstitute.org/software/igv/)"),
AttrH("ucsc",
title="View in UCSC",
kind="place",
tooltip="View this variant in UCSC Browser"),
AttrH("transcripts", title="Transcripts", is_seq=True),
AttrH("op_filters",
title="Presence in filters",
kind="place",
tooltip="Filters positive on variant"),
AttrH("op_dtrees",
title="Presence in decision trees",
kind="place",
tooltip="Decision trees positive on variant")
])
aspects["view_transcripts"].setAttributes([
AttrH("id", title="Transcript Id"),
AttrH("gene", title="Gene"),
AttrH("is_canonical", title="Canonical"),
AttrH(
"gencode_basic",
title="GENCODE Basic",
tooltip="The transcripts tagged as “basic” form part of a subset "
"of representative transcripts for each gene. This subset "
"prioritises full-length protein coding transcripts over "
"partial or non-protein coding transcripts within the "
"same gene, and intends to highlight those transcripts "
"that will be useful to the majority of users."),
AttrH("is_worst", title="Worst?"),
AttrH("transcript_source", title="Source"),
AttrH("biotype", title="Biotype"),
AttrH("transcript_annotations", title="Consequences", is_seq=True),
AttrH("variant_exon", title="Exon"),
AttrH("variant_intron", title="Intron"),
AttrH("tr_gene_panels",
title="Gene panels",
is_seq=True,
kind="posted"),
AttrH("cpos", title="CPos"),
AttrH("hgvs_c_snp_eff", title="CPos SnpEff"),
AttrH("hgvs_c_annovar", title="CPos ANNOVAR"),
AttrH("ppos", title="PPos"),
AttrH("hgvs_p_snp_eff", title="PPos SnpEff"),
AttrH("hgvs_p_annovar", title="PPos ANNOVAR"),
AttrH("amino_acids", title="Amino acids"),
AttrH("codons", title="Codons"),
AttrH("codonpos", title="Codon Pos"),
AttrH("refcodon", title="Ref Codon"),
AttrH("region", title="Gene Region"),
AttrH("cds", title="CDS?"),
AttrH("masked_region", title="Masked"),
AttrH("dist_from_exon", title="Distance from Exon Boundary"),
AttrH("polyphen2_hdiv_prediction", title="Polyphen HDIV"),
AttrH("polyphen2_hvar_prediction", title="Polyphen HVAR"),
AttrH("sift_prediction", title="SIFT"),
AttrH("sift_4g_prediction", title="SIFT 4G"),
AttrH("mutation_assessor_prediction", title="Mutation Assessor"),
AttrH("fathmm_prediction", title="FATHMM"),
AttrH("polyphen2_hdiv_score", title="Polyphen HDIV Score"),
AttrH("polyphen2_hvar_score", title="Polyphen HVAR Score"),
AttrH("sift_score", title="SIFT Score"),
AttrH("sift_4g_score", title="SIFT 4G Score"),
AttrH("mutation_assessor_score", title="Mutation Assessor Score"),
AttrH("fathmm_score", title="FATHMM Score"),
AttrH("mpc_score", title="MPC Score"),
AttrH("ensembl_gene_id", title="Gene Id", kind="hidden"),
AttrH("ensembl_protein_id", title="Protein Id", kind="hidden"),
AttrH("uniprot_acc", title="Uniprot", kind="place"),
])
aspects["view_qsamples"].setAttributes([
AttrH("title", title="Title"),
AttrH("qd",
title="Quality by Depth",
is_seq=True,
tooltip="The QUAL score normalized by allele depth (AD) "
"for a variant. This annotation puts the variant confidence "
"QUAL score into perspective by normalizing for the amount "
"of coverage available. Because each read contributes a little "
"to the QUAL score, variants in regions with deep coverage "
"can have artificially inflated QUAL scores, giving the "
"impression that the call is supported by more evidence "
"than it really is. To compensate for this, we normalize "
"the variant confidence by depth, which gives us a more "
"objective picture of how well supported the call is."),
AttrH("mq",
title="Mapping Quality",
is_seq=True,
tooltip="This is the root mean square mapping quality over all "
"the reads at the site. Instead of the average mapping "
"quality of the site, this annotation gives the square root "
"of the average of the squares of the mapping qualities at "
"the site. When the mapping qualities are good at a site, "
"the MQ will be around 60. Broad Institute recommendation is "
"to fail any variant with an MQ value less than 40.0"),
AttrH("variant_call_quality",
title="Variant Call Quality",
tooltip="QUAL tells you how confident we are that there is "
"some kind of variation at a given site. The variation may be "
"present in one or more samples."),
AttrH("strand_odds_ratio",
title="Strand Odds Ratio",
is_seq=True,
tooltip="Another way to estimate strand bias using a "
"test similar to the symmetric odds ratio test. "
"SOR was created because FS tends to penalize variants "
"that occur at the ends of exons. Reads at the ends of "
"exons tend to only be covered by reads in one direction "
"and FS gives those variants a bad score. SOR will take "
"into account the ratios of reads that cover both alleles."),
AttrH("fs",
title="Fisher Strand Bias",
is_seq=True,
tooltip="Phred-scaled probability that there is strand bias at "
"the site. Strand Bias tells us whether the alternate "
"allele was seen more or less often on the forward or "
"reverse strand than the reference allele. When there "
"little to no strand bias at the site, the FS value "
"will be close to 0."),
AttrH(
"allelic_depth",
title="Allelic Depth",
tooltip="AD is the unfiltered allele depth, i.e. "
"the number of reads that support each of the reported "
"alleles. All reads at the position (including reads that "
"did not pass the variant caller's filters) are included in "
"this number, except reads that were considered uninformative. "
"Reads are considered uninformative when they do not provide "
"enough statistical evidence to support one allele over another."),
AttrH("read_depth",
title="Read Depth",
tooltip="DP - is a number of times that base pair locus "
"was read"),
AttrH("ft",
title="FILTERs",
is_seq=True,
tooltip="This field contains the name(s) of any filter(s) "
"that the variant fails to pass, or the value PASS if the "
"variant passed all filters. If the FILTER value is ., "
"then no filtering has been applied to the records."),
AttrH("genotype_quality",
title="Genotype Quality",
tooltip="GQ tells you how confident we are that "
"the genotype we assigned to a particular sample is correct. "
"It is simply the second lowest PL, because it is the "
"difference between the second lowest PL and the lowest PL "
"(always 0)."),
AttrH("genotype", title="Sample Genotype")
])
aspects["view_gnomAD"].setAttributes([
AttrH("allele", title="Allele"),
AttrH("proband", title="Proband"),
AttrH("pli", title="pLI", is_seq=True),
AttrH("af", title="Overall AF"),
AttrH("genome_af", title="Genome AF"),
AttrH("exome_af", title="Exome AF"),
AttrH("hom", title="Number of homozygotes"),
AttrH("hem", title="Number of hemizygotes", is_seq=True),
AttrH("genome_an", title="Genome AN"),
AttrH("exome_an", title="Exome AN"),
AttrH("url", title="URL", kind="link", is_seq=True),
AttrH(
"popmax",
title="PopMax (outbred populations)",
),
AttrH(
"raw_popmax",
title="PopMax (including inbred)",
)
])
aspects["view_db"].setAttributes([
AttrH("hgmd", title="HGMD"),
AttrH("hgmd_hg38", title="HGMD (HG38)"),
AttrH("hgmd_tags", title="HGMD TAGs", is_seq=True),
AttrH("hgmd_phenotypes", title="HGMD Phenotypes", is_seq=True),
AttrH("hgmd_pmids", title="HGMD PMIDs", is_seq=True, kind="place"),
AttrH("omim", title="OMIM", is_seq=True, kind="place"),
AttrH("clinVar_variants", title="ClinVar Variants", is_seq=True),
AttrH("clinVar_significance",
title="ClinVar Significance",
is_seq=True),
AttrH("clinvar_review_status",
title="ClinVar Review Status",
is_seq=False),
AttrH("num_clinvar_submitters",
title="ClinVar: Number of submitters",
is_seq=False),
AttrH("clinvar_acmg_guidelines",
title="ClinVar ACMG Guidelines",
is_seq=True),
AttrH("clinvar_trusted",
kind="json",
title="Clinical Significance by Trusted Submitters"),
AttrH("lmm_significance", title="Clinical Significance by LMM"),
AttrH("gene_dx_significance", title="Clinical Significance by GeneDx"),
AttrH("clinVar_phenotypes", title="ClinVar Phenotypes", is_seq=True),
AttrH("clinVar_submitters", title="ClinVar Submitters", is_seq=True),
AttrH("clinVar", title="ClinVar", is_seq=True, kind="link"),
AttrH(
"gtex",
kind="place",
),
AttrH("gene_cards", title="GeneCards", is_seq=True, kind="place"),
AttrH("grev", is_seq=True, kind="place"),
AttrH("medgen", is_seq=True, kind="place"),
# AttrH("pubmed_search", title = "PubMed Search Results",
# is_seq = True, kind = "link"),
AttrH("beacons", title="Observed at", is_seq=True),
AttrH("references", is_seq=True, kind="place")
])
aspects["view_pred"].setAttributes([
AttrH("lof_score", title="LoF Score", is_seq=True),
AttrH("lof_score_canonical",
title="LoF Score (Canonical)",
is_seq=True),
AttrH("max_ent_scan", title="MaxEntScan", is_seq=True),
AttrH(
"polyphen",
title="Polyphen",
is_seq=True,
tooltip="https://brb.nci.nih.gov/seqtools/colexpanno.html#dbnsfp"),
AttrH("polyphen2_hvar",
title="Polyphen 2 HVAR",
is_seq=True,
tooltip="HumVar (HVAR) is PolyPhen-2 classifier "
"trained on known human variation (disease mutations vs."
" common neutral variants)"),
AttrH(
"polyphen2_hdiv",
title="Polyphen 2 HDIV",
is_seq=True,
tooltip="HumDiv (HDIV) classifier is trained on a smaller "
"number of select extreme effect disease mutations vs. divergence "
"with close homologs (e.g. primates), which is supposed to "
"consist of mostly neutral mutations."),
AttrH("sift",
title="SIFT from dbNSFP",
is_seq=True,
tooltip="Sort intolerated from tolerated (An amino acid at a "
"position is tolerated | The most frequentest amino acid "
"being tolerated). D: Deleterious T: tolerated"),
AttrH("sift_vep", title="SIFT from VEP", is_seq=True),
AttrH("revel", title="REVEL", is_seq=True),
AttrH("mutation_taster",
title="Mutation Taster",
is_seq=True,
tooltip="Bayes Classifier. A: (disease_causing_automatic); "
"D: (disease_causing); N: (polymorphism [probably harmless]); "
"P: (polymorphism_automatic[known to be harmless])"),
AttrH("mutation_assessor_predictions",
title="MutationAssessor",
is_seq=True,
tooltip="MutationAssessor functional impact of a variant : "
"predicted functional, i.e. high (“H”) or medium (“M”), "
"or predicted non-functional, i.e. low (“L”) or neutral (“N”). "
"The MAori score cutoffs between “H” and “M”, “M” and “L”, and "
"“L” and “N”, are 3.5, 1.935 and 0.8, respectively. The "
"rankscore cutoffs between “H” and “M”, “M” and “L”, and “L” "
"and “L”, are 0.92922, 0.51944 and 0.19719, respectively."),
AttrH("fathmm",
title="FATHMM",
is_seq=True,
tooltip="Functional analysis through hidden markov model HMM."
"D: Deleterious; T: Tolerated"),
AttrH("primate_ai_pred",
title="PrimateAI",
is_seq=True,
tooltip="Prediction of PrimateAI score based on the authors "
"recommendation, “T(olerated)” or “D(amaging)”. "
"The score cutoff between “D” and “T” is 0.803."),
AttrH("cadd_phred",
title="CADD (Phred)",
is_seq=True,
tooltip="CADD Combined annotation dependent depletion"),
AttrH("cadd_raw",
title="CADD (Raw)",
is_seq=True,
tooltip="CADD Combined annotation dependent depletion"),
# AttrH("mutation_assessor", title = "Mutation Assessor",
# is_seq = True,
# tooltip = "Entropy of multiple sequence alighnment. "
# "H: high; M: medium; L: low; N: neutral. H/M means functional "
# "and L/N means non-functional higher values "
# "are more deleterious"),
AttrH("sift_score", title="SIFT score", is_seq=True),
AttrH("polyphen2_hvar_score",
title="Polyphen 2 HVAR score",
is_seq=True),
AttrH("polyphen2_hdiv_score",
title="Polyphen 2 HDIV score",
is_seq=True),
AttrH("mutation_assessor_scores",
title="MutationAssessor score (MAori)",
tooltip="MutationAssessor functional impact combined score "
"(MAori). Multiple entries are separated by “;”, corresponding "
"to Uniprot_entry.",
is_seq=True),
AttrH("dann_score",
title="DANN Functional Prediction score",
tooltip="DANN is a functional prediction score retrained based "
"on the training data of CADD using deep neural network",
is_seq=True)
])
aspects["view_pharmagkb"].setAttributes([
AttrH("diseases", title="Diseases", is_seq=True, kind="place"),
AttrH("chemicals", title="Chemicals", is_seq=True),
AttrH("notes", title="Notes", is_seq=True),
AttrH("pmids", title="PMIDs", is_seq=True)
])
aspects["view_genetics"].setAttributes([
AttrH("zygosity", title="Zygosity"),
AttrH("inherited_from", title="Inherited from"),
AttrH("region_worst", title="Gene Region (Worst)", is_seq=True),
AttrH("dist_from_exon_worst",
title="Distance From Intron/Exon Boundary (Worst)",
is_seq=True),
AttrH("region_canonical", title="Gene Region (Canonical)",
is_seq=True),
AttrH("dist_from_exon_canonical",
title="Distance From Intron/Exon Boundary (Canonical)",
is_seq=True),
AttrH("masked_region", title="Masked"),
AttrH("gerp_rs", title="GERP Score", is_seq=False),
AttrH("conservation", title="Conservation", kind="json"),
AttrH("species_with_variant", title="Species with variant"),
AttrH("species_with_others", title="Species with other variants"),
AttrH("max_ent_scan", title="MaxEntScan", is_seq=True),
AttrH("nn_splice", title="NNSplice"),
AttrH("human_splicing_finder", title="Human Splicing Finder"),
#AttrH("splice_ai", title = "Splice AI Max Score"),
AttrH("splice_ai_ag", title="Splice AI acceptor gain", is_seq=True),
AttrH("splice_ai_al", title="Splice AI acceptor loss", is_seq=True),
AttrH("splice_ai_dg", title="Splice AI donor gain", is_seq=True),
AttrH("splice_ai_dl", title="Splice AI donor loss", is_seq=True),
AttrH("splice_ai", kind="hidden"),
AttrH("eqtl_gene", title="EQTL Gene", is_seq=True),
AttrH("refcodon", title="Ref Codon(s)", is_seq=True),
AttrH("other_genes",
title="Gene symbols from other transcripts",
is_seq=True),
AttrH("called_by", title="Called by", is_seq=True),
AttrH("caller_data", title="CALLER DATA")
])
if cohorts:
aspects["view_cohorts"].setAttributes(
[AttrH("AF"), AttrH("AF2", title="AF_Hom")])
aspects["_main"].setAttributes([
AttrH("label"),
AttrH("color_code"),
AttrH("id", is_seq=True),
AttrH("assembly_name", title="Assembly"),
AttrH("seq_region_name"),
AttrH("start"),
AttrH("end"),
AttrH("strand"),
AttrH("allele_string"),
AttrH("variant_class"),
AttrH("most_severe_consequence"),
AttrH("ClinVar", is_seq=True),
AttrH("clinvar_variants", is_seq=True),
AttrH("clinvar_phenotypes", is_seq=True),
AttrH("clinvar_significance", is_seq=True),
AttrH("HGMD"),
AttrH("HGMD_HG38"),
AttrH("HGMD_PIMIDs", kind="hidden", is_seq=True),
AttrH("HGMD_phenotypes", kind="hidden", is_seq=True),
AttrH("EXPECTED"),
AttrH("gnomad_db_genomes_af", kind="hidden"),
AttrH("gnomad_db_exomes_af", kind="hidden"),
AttrH("SEQaBOO")
])
aspects["transcripts"].setAttributes([
AttrH("amino_acids"),
AttrH("bam_edit"),
AttrH("biotype"),
AttrH("cadd_phred"),
AttrH("cadd_raw"),
AttrH("canonical"),
AttrH("ccds"),
AttrH("cdna_end"),
AttrH("cdna_start"),
AttrH("cds_end"),
AttrH("cds_start"),
AttrH("clinvar_clnsig"),
AttrH("clinvar_rs"),
AttrH("codons"),
AttrH("consequence_terms", is_seq=True),
AttrH("conservation"),
AttrH("distance"),
AttrH("domains", kind="json", is_seq=True),
AttrH("exacpli"),
AttrH("exon"),
AttrH("fathmm_pred"),
AttrH("fathmm_score"),
AttrH("flags", is_seq=True),
AttrH("gene_id"),
AttrH("gene_pheno"),
AttrH("genesplicer"),
AttrH("gene_symbol"),
AttrH("gene_symbol_source"),
AttrH("given_ref"),
AttrH("gnomad_exomes_ac"),
AttrH("gnomad_exomes_af"),
AttrH("gnomad_exomes_an"),
AttrH("gnomad_exomes_asj_af"),
AttrH("gnomad_genomes_ac"),
AttrH("gnomad_genomes_af"),
AttrH("gnomad_genomes_an"),
AttrH("gnomad_genomes_asj_af"),
AttrH("hgnc_id"),
AttrH("hgvs_offset"),
AttrH("hgvsc"),
AttrH("hgvsp"),
AttrH("high_inf_pos"),
AttrH("impact"),
AttrH("intron"),
AttrH("loftool"),
AttrH("maxentscan_alt"),
AttrH("maxentscan_diff"),
AttrH("maxentscan_ref"),
AttrH("motif_feature_id"),
AttrH("motif_name"),
AttrH("motif_pos"),
AttrH("motif_score_change"),
AttrH("mutationassessor_pred"),
AttrH("mutationassessor_score"),
AttrH("mutationtaster_pred"),
AttrH("mutationtaster_score"),
AttrH("polyphen2_hdiv_pred"),
AttrH("polyphen2_hdiv_score"),
AttrH("polyphen2_hvar_pred"),
AttrH("polyphen2_hvar_score"),
AttrH("polyphen_prediction"),
AttrH("polyphen_score"),
AttrH("protein_end"),
AttrH("protein_id"),
AttrH("protein_start"),
AttrH("regulatory_feature_id"),
AttrH("revel_score"),
AttrH("sift_pred"),
AttrH("sift_prediction"),
AttrH("sift_score"),
AttrH("strand"),
AttrH("source"),
AttrH("spliceregion", is_seq=True),
AttrH("swissprot", is_seq=True),
AttrH("transcript_id"),
AttrH("trembl", is_seq=True),
AttrH("uniparc", is_seq=True),
AttrH("used_ref"),
AttrH("variant_allele")
])
aspects["colocated_v"].setAttributes([
AttrH("id"),
AttrH("start"),
AttrH("end"),
AttrH("allele_string"),
AttrH("strand"),
AttrH("pubmed", is_seq=True),
AttrH("somatic"),
AttrH("gnomAD"),
AttrH("frequencies", kind="json"),
AttrH("phenotype_or_disease"),
AttrH("seq_region_name"),
AttrH("clin_sig", is_seq=True),
AttrH("minor")
])
return aspects
def __init__(self, view):
AttrH.__init__(self,
"GREV",
title="GeneReviews®",
tooltip="Search GeneReviews®")
self.setAspect(view)
