def get_recomb_stats_splitweight0(clones):
# in case of unambiguous calls, split the weight
model = RecombModel()
for clone in clones:
# V
vsize = 1.0 / len(clone.vgenes)
for v in clone.vgenes:
model.update_attr('v', v, vsize)
model.update_attr2('v2del', clone.vgenes[0], clone.vdel, vsize)
# J
jsize = 1.0 / len(clone.jgenes)
for j in clone.jgenes:
model.update_attr('j', j, jsize)
model.update_attr2('j2del', clone.jgenes[0], clone.jdel, jsize)
# D
dsize = 1.0 / len(clone.dgenes)
for d in clone.dgenes:
model.update_attr('d', d, dsize)
model.update_attr2('d2del', clone.dgenes[0], (clone.d5del, clone.d3del), dsize)
# DJ
numdj = len(clone.jgenes) * len(clone.dgenes)
djsize = 1.0 / numdj
for d in clone.dgenes:
for j in clone.jgenes:
model.update_attr('dj', (d, j), djsize)
# Insertion length
ins_vd = clone.firstdpos - clone.lastvpos - 1
model.update_attr('ins_vd', ins_vd, vsize)
ins_dj = clone.firstjpos - clone.lastdpos - 1
model.update_attr('ins_dj', ins_dj, jsize)
# inserted nt given 5' nt
vd_nts = clone.nuc[clone.lastvpos: clone.firstdpos] # include the lastV
model.update_vd2next(vd_nts, vsize)
dj_nts = clone.nuc[clone.lastdpos + 1: clone.firstjpos + 1] # include lastJ
model.update_dj2prev(dj_nts, jsize)
return model
def get_recomb_stats_splitweight(clones):
# in case of unambiguous calls, split the weight
model = RecombModel()
for clone in clones:
# V
model.update_attr('v', clone.v, 1.0)
model.update_attr2('v2del', clone.v, clone.vdel, 1.0)
# J
model.update_attr('j', clone.j, 1.0)
model.update_attr2('j2del', clone.j, clone.jdel, 1.0)
# D
model.update_attr('d', clone.d, 1.0)
model.update_attr2('d2del', clone.d, (clone.d5del, clone.d3del), 1.0)
# DJ
model.update_attr('dj', (clone.d, clone.j), 1.0)
# Insertion length
ins_vd = len(clone.vdins) - 1
model.update_attr('ins_vd', ins_vd, 1.0)
ins_dj = len(clone.djins) - 1
model.update_attr('ins_dj', ins_dj, 1.0)
# inserted nt given 5' nt
model.update_vd2next(clone.vdins, 1.0)
model.update_dj2prev(clone.djins, 1.0)
return model
def get_recomb_stats0(clones):
# in case of unambiguous calls, just record the first call
model = RecombModel()
for clone in clones:
# V
model.update_attr('v', clone.vgenes[0], 1)
model.update_attr2('v2del', clone.vgenes[0], clone.vdel, 1)
# J
model.update_attr('j', clone.jgenes[0], 1)
model.update_attr2('j2del', clone.jgenes[0], clone.jdel, 1)
# D
model.update_attr('d', clone.dgenes[0], 1)
model.update_attr2('d2del', clone.dgenes[0],
(clone.d5del, clone.d3del), 1)
# DJ
model.update_attr('dj', (clone.dgenes[0], clone.jgenes[0]), 1)
# Insertion length
ins_vd = clone.firstdpos - clone.lastvpos - 1
model.update_attr('ins_vd', ins_vd, 1)
ins_dj = clone.firstjpos - clone.lastdpos - 1
model.update_attr('ins_dj', ins_dj, 1)
# inserted nt given 5' nt
vd_nts = clone.nuc[clone.lastvpos: clone.firstdpos] # include the lastV
model.update_vd2next(vd_nts, 1)
dj_nts = clone.nuc[clone.lastdpos + 1: clone.firstjpos + 1] # include lastJ
model.update_dj2prev(dj_nts, 1)
return model
def get_recomb_stats(clones):
# in case of unambiguous calls, just record the first call
model = RecombModel()
for clone in clones:
# V
model.update_attr('v', clone.v, 1)
model.update_attr2('v2del', clone.v, clone.vdel, 1)
# J
model.update_attr('j', clone.j, 1)
model.update_attr2('j2del', clone.j, clone.jdel, 1)
# D
model.update_attr('d', clone.d, 1)
model.update_attr2('d2del', clone.d, (clone.d5del, clone.d3del), 1)
# DJ
model.update_attr('dj', (clone.d, clone.j), 1)
# Insertion length
ins_vd = len(clone.vdins) - 1
model.update_attr('ins_vd', ins_vd, 1)
ins_dj = len(clone.djins) - 1
model.update_attr('ins_dj', ins_dj, 1)
# inserted nt given 5' nt
model.update_vd2next(clone.vdins, 1) # include the lastV
model.update_dj2prev(clone.djins, 1) # include the fistJ
return model