def generate_trio_stats(
mt: hl.MatrixTable, autosomes_only: bool = True, bi_allelic_only: bool = True
) -> hl.Table:
"""
Default function to run `generate_trio_stats_expr` to get trio stats stratified by raw and adj
.. note::
Expects that `mt` is it a trio matrix table that was annotated with adj and if dealing with
a sparse MT `hl.experimental.densify` must be run first.
By default this pipeline function will filter `mt` to only autosomes and bi-allelic sites.
:param mt: A Trio Matrix Table returned from `hl.trio_matrix`. Must be dense
:param autosomes_only: If set, only autosomal intervals are used.
:param bi_allelic_only: If set, only bi-allelic sites are used for the computation
:return: Table with trio stats
"""
if autosomes_only:
mt = filter_to_autosomes(mt)
if bi_allelic_only:
mt = mt.filter_rows(bi_allelic_expr(mt))
logger.info(f"Generating trio stats using {mt.count_cols()} trios.")
trio_adj = mt.proband_entry.adj & mt.father_entry.adj & mt.mother_entry.adj
ht = mt.select_rows(
**generate_trio_stats_expr(
mt,
transmitted_strata={"raw": True, "adj": trio_adj},
de_novo_strata={"raw": True, "adj": trio_adj},
ac_strata={"raw": True, "adj": trio_adj},
)
).rows()
return ht
def generate_fam_stats(
mt: hl.MatrixTable,
fam_file: str
) -> hl.Table:
"""
Calculate transmission and de novo mutation statistics using trios in the dataset.
:param mt: Input MatrixTable
:param fam_file: path to text file containing trio pedigree
:return: Table containing trio stats
"""
# Load Pedigree data and filter MT to samples present in any of the trios
ped = hl.Pedigree.read(fam_file, delimiter="\t")
fam_ht = hl.import_fam(fam_file, delimiter="\t")
fam_ht = fam_ht.annotate(
fam_members=[fam_ht.id, fam_ht.pat_id, fam_ht.mat_id]
)
fam_ht = fam_ht.explode('fam_members', name='s')
fam_ht = fam_ht.key_by('s').select().distinct()
mt = mt.filter_cols(hl.is_defined(fam_ht[mt.col_key]))
logger.info(f"Generating family stats using {mt.count_cols()} samples from {len(ped.trios)} trios.")
mt = filter_to_autosomes(mt)
mt = annotate_adj(mt)
mt = mt.select_entries('GT', 'GQ', 'AD', 'END', 'adj')
mt = hl.experimental.densify(mt)
mt = mt.filter_rows(hl.len(mt.alleles) == 2)
mt = hl.trio_matrix(mt, pedigree=ped, complete_trios=True)
trio_adj = (mt.proband_entry.adj & mt.father_entry.adj & mt.mother_entry.adj)
ht = mt.select_rows(
**generate_trio_stats_expr(
mt,
transmitted_strata={
'raw': True,
'adj': trio_adj
},
de_novo_strata={
'raw': True,
'adj': trio_adj,
},
proband_is_female_expr=mt.is_female
)
).rows()
return ht.filter(
ht.n_de_novos_raw + ht.n_transmitted_raw + ht.n_untransmitted_raw > 0
)
def generate_fam_stats(mt: hl.MatrixTable, fam_file: str) -> hl.Table:
# Load Pedigree data and filter MT to samples present in any of the trios
ped = hl.Pedigree.read(fam_file, delimiter="\t")
fam_ht = hl.import_fam(fam_file, delimiter="\t")
fam_ht = fam_ht.annotate(
fam_members=[fam_ht.id, fam_ht.pat_id, fam_ht.mat_id])
fam_ht = fam_ht.explode('fam_members', name='s')
fam_ht = fam_ht.key_by('s').select().distinct()
mt = mt.filter_cols(hl.is_defined(fam_ht[mt.col_key]))
logger.info(
f"Generating family stats using {mt.count_cols()} samples from {len(ped.trios)} trios."
)
mt = filter_to_autosomes(mt)
mt = annotate_adj(mt)
mt = mt.select_entries('GT', 'GQ', 'AD', 'END', 'adj')
mt = hl.experimental.densify(mt)
mt = mt.filter_rows(hl.len(mt.alleles) == 2)
mt = hl.trio_matrix(mt, pedigree=ped, complete_trios=True)
trio_adj = (mt.proband_entry.adj & mt.father_entry.adj
& mt.mother_entry.adj)
parents_no_alt = (mt.mother_entry.AD[1] == 0) & (mt.father_entry.AD[1]
== 0)
parents_high_depth = (mt.mother_entry.AD[0] + mt.mother_entry.AD[1] >
20) & (mt.father_entry.AD[0] + mt.father_entry.AD[1]
> 20)
parents_high_gq = (mt.mother_entry.GQ >= 30) & (mt.father_entry.GQ >= 30)
ht = mt.select_rows(**generate_trio_stats_expr(
mt,
transmitted_strata={
'raw': None,
'adj': trio_adj
},
de_novo_strata={
'raw': None,
'adj': trio_adj,
'hq': trio_adj & parents_high_gq & parents_high_depth
& parents_no_alt
},
proband_is_female_expr=mt.is_female)).rows()
return ht.filter(
ht.n_de_novos_raw + ht.n_transmitted_raw + ht.n_untransmitted_raw > 0)