aboutsummaryrefslogtreecommitdiff
path: root/gn3/db/phenotypes.py
blob: 0339abae8d158c47691fcb4d658b954b9c84ea91 (plain)
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
# 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 gn3.db_utils import Connection as DBConnection

from .query_tools import mapping_to_query_columns


@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",
}

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 iset.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 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_by_id(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()

def fetch_publication_by_pubmed_id(conn: DBConnection, pubmed_id: int) -> dict:
    """Fetch the publication by its PUBMED 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 PubMed_Id=%(pubmed_id)s"),
            {"pubmed_id": pubmed_id})
        return cursor.fetchone()

def update_publication(conn, data=dict) -> int:
    """Update the publication with the given data."""
    updatable_cols = ", ".join(f"{publication_mapping[col]}=%({col})s"
                               for col in data
                               if col not in ("id_", "id"))
    if not bool(updatable_cols):
        return 0
    with conn.cursor(cursorclass=DictCursor) as cursor:
        cursor.execute(
            f"UPDATE Publication SET {updatable_cols} WHERE Id=%(id_)s", data)
        return cursor.rowcount

def update_phenotype(conn, data:dict) -> int:
    """Update the `Phenotype` table with the given data."""
    cols = ", ".join(f"{phenotype_mapping[col]}=%({col})s"
                     for col in data
                     if col not in ("id_", "id"))
    if not bool(cols):
        return 0
    with conn.cursor(cursorclass=DictCursor) as cursor:
        cursor.execute(
            f"UPDATE Phenotype SET {cols} WHERE Id=%(id_)s", data)
        return cursor.rowcount

def update_cross_reference(conn, dataset_id, trait_name, data:dict) -> int:
    """Update the `PublishXRef` table with data."""
    cols = ", ".join(f"{publish_x_ref_mapping[col]}=%({col})s"
                     for col in data
                     if (col not in ("id_", "id") and
                         col in publish_x_ref_mapping))
    if not bool(cols):
        return 0
    with conn.cursor(cursorclass=DictCursor) as cursor:
        cursor.execute(
            f"UPDATE PublishXRef SET {cols} WHERE "
            "Id=%(trait_name)s AND "
            "InbredSetId=%(dataset_id)s",
            {
                "dataset_id": dataset_id,
                "trait_name": trait_name,
                **data
            })
        return cursor.rowcount