1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
|
# pylint: disable=[R0902, R0903]
"""This contains all the necessary functions that access the phenotypes from
the db"""
from typing import Optional
from dataclasses import dataclass
from MySQLdb.cursors import DictCursor
from wqflask.database import Connection as DBConnection
@dataclass(frozen=True)
class Phenotype:
"""Data Type that represents a Phenotype"""
id_: Optional[int] = None
pre_pub_description: Optional[str] = None
post_pub_description: Optional[str] = None
original_description: Optional[str] = None
units: Optional[str] = None
pre_pub_abbreviation: Optional[str] = None
post_pub_abbreviation: Optional[str] = None
lab_code: Optional[str] = None
submitter: Optional[str] = None
owner: Optional[str] = None
authorized_users: Optional[str] = None
# Mapping from the Phenotype dataclass to the actual column names in the
# database
phenotype_mapping = {
"id_": "id",
"pre_pub_description": "Pre_publication_description",
"post_pub_description": "Post_publication_description",
"original_description": "Original_description",
"units": "Units",
"pre_pub_abbreviation": "Pre_publication_abbreviation",
"post_pub_abbreviation": "Post_publication_abbreviation",
"lab_code": "Lab_code",
"submitter": "Submitter",
"owner": "Owner",
"authorized_users": "Authorized_Users",
}
@dataclass(frozen=True)
class PublishXRef:
"""Data Type that represents the table PublishXRef"""
id_: Optional[int] = None
inbred_set_id: Optional[str] = None
phenotype_id: Optional[int] = None
publication_id: Optional[str] = None
data_id: Optional[int] = None
mean: Optional[float] = None
locus: Optional[str] = None
lrs: Optional[float] = None
additive: Optional[float] = None
sequence: Optional[int] = None
comments: Optional[str] = None
# Mapping from the PublishXRef dataclass to the actual column names in the
# database
publish_x_ref_mapping = {
"id_": "Id",
"inbred_set_id": "InbredSetId",
"phenotype_id": "PhenotypeId",
"publication_id": "PublicationId",
"data_id": "DataId",
"mean": "mean",
"locus": "locus",
"lrs": "lrs",
"additive": "additive",
"sequence": "sequence",
"comments": "comments",
}
@dataclass(frozen=True)
class Publication:
"""Data Type that represents the table Publication"""
id_: Optional[int] = None
pubmed_id: Optional[int] = None
abstract: Optional[str] = None
authors: Optional[str] = None
title: Optional[str] = None
journal: Optional[str] = None
volume: Optional[str] = None
pages: Optional[str] = None
month: Optional[str] = None
year: Optional[str] = None
publication_mapping = {
"id_": "id",
"pubmed_id": "PubMed_ID",
"abstract": "Abstract",
"authors": "Authors",
"title": "Title",
"journal": "Journal",
"volume": "Volume",
"pages": "Pages",
"month": "Month",
"year": "Year",
}
@dataclass(frozen=True)
class Probeset:
"""Data Type that represents a Probeset"""
id_: Optional[int] = None
name: Optional[str] = None
symbol: Optional[str] = None
description: Optional[str] = None
probe_target_description: Optional[str] = None
chr_: Optional[str] = None
mb: Optional[float] = None # pylint: disable=C0103
alias: Optional[str] = None
geneid: Optional[str] = None
homologeneid: Optional[str] = None
unigeneid: Optional[str] = None
omim: Optional[str] = None
refseq_transcriptid: Optional[str] = None
blatseq: Optional[str] = None
targetseq: Optional[str] = None
strand_probe: Optional[str] = None
probe_set_target_region: Optional[str] = None
probe_set_specificity: Optional[float] = None
probe_set_blat_score: Optional[float] = None
probe_set_blat_mb_start: Optional[float] = None
probe_set_blat_mb_end: Optional[float] = None
probe_set_strand: Optional[str] = None
probe_set_note_by_rw: Optional[str] = None
flag: Optional[str] = None
# Mapping from the Phenotype dataclass to the actual column names in the
# database
probeset_mapping = {
"id_": "Id",
"name": "Name",
"symbol": "symbol",
"description": "description",
"probe_target_description": "Probe_Target_Description",
"chr_": "Chr",
"mb": "Mb",
"alias": "alias",
"geneid": "GeneId",
"homologeneid": "HomoloGeneID",
"unigeneid": "UniGeneId",
"omim": "OMIM",
"refseq_transcriptid": "RefSeq_TranscriptId",
"blatseq": "BlatSeq",
"targetseq": "TargetSeq",
"strand_probe": "Strand_Probe",
"probe_set_target_region": "Probe_set_target_region",
"probe_set_specificity": "Probe_set_specificity",
"probe_set_blat_score": "Probe_set_BLAT_score",
"probe_set_blat_mb_start": "Probe_set_Blat_Mb_start",
"probe_set_blat_mb_end": "Probe_set_Blat_Mb_end",
"probe_set_strand": "Probe_set_strand",
"probe_set_note_by_rw": "Probe_set_Note_by_RW",
"flag": "flag"
}
def fetch_trait(conn: DBConnection, dataset_id: int, trait_name: str) -> dict:
"""Fetch phenotype 'traits' by `dataset_id` and `trait_name`."""
query = (
"SELECT "
"pxr.Id AS _id, pxr.Id as trait_name, pxr.PhenotypeId AS phenotype_id, "
"pxr.PublicationId AS publication_id, pxr.DataId AS data_id, "
"pxr.mean, pxr.locus, pxr.LRS as lrs, pxr.additive, "
"pxr.Sequence as sequence, pxr.comments "
"FROM PublishFreeze AS pf INNER JOIN InbredSet AS iset "
"ON pf.InbredSetId=iset.Id "
"INNER JOIN PublishXRef AS pxr ON iset.Id=pxr.InbredSetId "
"WHERE pf.Id=%(dataset_id)s AND pxr.Id=%(trait_name)s")
with conn.cursor(cursorclass=DictCursor) as cursor:
cursor.execute(
query, {"dataset_id": dataset_id, "trait_name": trait_name})
return cursor.fetchone()
def _mapping_to_query_columns_(mapping_dict: dict[str, str]) -> tuple[str, ...]:
"""
Internal function to convert mapping dicts into column clauses for queries.
"""
return tuple(f"{tcol} as {dcol}" for dcol, tcol in mapping_dict.items())
def fetch_metadata(conn: DBConnection, phenotype_id: int) -> dict:
"""Get the phenotype metadata by ID."""
with conn.cursor(cursorclass=DictCursor) as cursor:
cols = ', '.join(_mapping_to_query_columns_(phenotype_mapping))
cursor.execute(
(f"SELECT Id as id, {cols} FROM Phenotype "
"WHERE Id=%(phenotype_id)s"),
{"phenotype_id": phenotype_id})
return cursor.fetchone()
def fetch_publication(conn: DBConnection, publication_id: int) -> dict:
"""Fetch the publication by its ID."""
with conn.cursor(cursorclass=DictCursor) as cursor:
cols = ', '.join(_mapping_to_query_columns_(publication_mapping))
cursor.execute(
(f"SELECT Id as id, {cols} FROM Publication "
"WHERE Id=%(publication_id)s"),
{"publication_id": publication_id})
return cursor.fetchone()
|
