24209217670

Committed 09 Apr 2026 07:27PM UTC coverage: 86.507% (+0.4%) from 86.074%

Build # 24209217670

Build Type

Pull #100

github

Committed by

iskandr

Commit Message

Rename norm→left_cdf/right_cdf, add hinge, aggregations, update docs

Rename survival/norm_lower → right_cdf, norm → left_cdf (keep norm as alias):
- left_cdf(mean, std): higher input → higher output (for scores)
- right_cdf(mean, std): lower input → higher output (for IC50, rank)

Add hinge() = max(0, x) on Expr.

Add aggregation functions for combining multiple expressions:
- mean(), geomean(), minimum(), maximum(), median()
- All skip NaN values; geomean skips non-positive
- Work with qualified fields: mean(Affinity["netmhcpan"].logistic(...), ...)

Update all docs and README:
- filter → filter_by in all examples
- norm → left_cdf/right_cdf with direction documentation
- Aggregation functions in transforms section and API reference
- hinge in transforms table

Bump version to 4.6.0.

Pull Request Pull Request #100: DSL polish: direction docs, log2/log1p, filter_by, parser errors

Coverage Stats

91 of 105 new or added lines in 4 files covered. (86.67%)

1449 of 1675 relevant lines covered (86.51%)

2.6 hits per line

Source File
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0.0

/topiary/cli/script.py

# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#       http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

"""
Script to generate epitope predictions from somatic cancer variants
and (optionally) tumor RNA-seq data.

Example usage:
    topiary \
        --mhc-predictor netmhcpan
        --mhc-alleles-file HLA.txt
        --vcf somatic.vcf
        --rna-gene-fpkm-file genes.fpkm_tracking
        --rna-transcript-fpkm-file isoforms.fpkm_tracking
        --filter-ic50 500
        --filter-percentile 2
        --output results.csv
"""

import sys

import argcomplete

from .args import arg_parser, predict_epitopes_from_args

from .outputs import write_outputs


def parse_args(args_list=None):
    if args_list is None:
        args_list = sys.argv[1:]
    argcomplete.autocomplete(arg_parser)
    return arg_parser.parse_args(args_list)


def main(args_list=None):
    """
    Script entry-point to predict neo-epitopes from genomic variants using
    Topiary.
    """
    args = parse_args(args_list)
    print("Topiary commandline arguments:")
    print(args)
    df = predict_epitopes_from_args(args)
    write_outputs(df, args)
    print("Total count: %d" % len(df))

1	# Licensed under the Apache License, Version 2.0 (the "License");
2	# you may not use this file except in compliance with the License.
3	# You may obtain a copy of the License at
4	#
5	# http://www.apache.org/licenses/LICENSE-2.0
6	#
7	# Unless required by applicable law or agreed to in writing, software
8	# distributed under the License is distributed on an "AS IS" BASIS,
9	# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
10	# See the License for the specific language governing permissions and
11	# limitations under the License.
12
13	"""
14	Script to generate epitope predictions from somatic cancer variants
15	and (optionally) tumor RNA-seq data.
16
17	Example usage:
18	topiary \
19	--mhc-predictor netmhcpan
20	--mhc-alleles-file HLA.txt
21	--vcf somatic.vcf
22	--rna-gene-fpkm-file genes.fpkm_tracking
23	--rna-transcript-fpkm-file isoforms.fpkm_tracking
24	--filter-ic50 500
25	--filter-percentile 2
26	--output results.csv
27	"""
28
29	import sys	×
30
NEW 31	import argcomplete	×
32
33	from .args import arg_parser, predict_epitopes_from_args	×
34
35	from .outputs import write_outputs	×
36
37
38	def parse_args(args_list=None):	×
39	if args_list is None:	×
40	args_list = sys.argv[1:]	×
NEW 41	argcomplete.autocomplete(arg_parser)	×
42	return arg_parser.parse_args(args_list)	×
43
44
45	def main(args_list=None):	×
46	"""
47	Script entry-point to predict neo-epitopes from genomic variants using
48	Topiary.
49	"""
50	args = parse_args(args_list)	×
51	print("Topiary commandline arguments:")	×
52	print(args)	×
53	df = predict_epitopes_from_args(args)	×
54	write_outputs(df, args)	×
55	print("Total count: %d" % len(df))	×

openvax / topiary / 24209217670

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