cmapBQ¶

cmapBQ.config module¶

class cmapBQ.config.Configuration(credentials: str, tables: cmapBQ.config.TableDirectory)¶

Data class for configuration of cmapBQ. Object for config.txt

credentials: str¶

tables: cmapBQ.config.TableDirectory¶

class cmapBQ.config.TableDirectory(compoundinfo: str, genetic_pertinfo: str, geneinfo: str, cellinfo: str, instinfo: str, siginfo: str, level3: str, level4: str, level5: str)¶

cellinfo: str¶

compoundinfo: str¶

geneinfo: str¶

genetic_pertinfo: str¶

instinfo: str¶

level3: str¶

level4: str¶

level5: str¶

siginfo: str¶

cmapBQ.config.get_bq_client(config=None)¶

Return authenticated BigQuery client object.

Parameters: config – optional path to config if not default
Returns: BigQuery Client

cmapBQ.config.get_default_config()¶

Get configuration object from reading ~/.cmapBQ/config.txt

Returns: cmapBQ.config.Configuration class.

cmapBQ.config.set_default_config(input_config_path)¶

Change configuration in ~/.cmapBQ to input config path. Overwrites ~/.cmapBQ/config.txt.,

Parameters: input_config_path – valid YAML formatted config file
Returns: location in ~/.cmapBQ

cmapBQ.config.setup_credentials(path_to_credentials)¶

Setup script for pointing config.txt to a GOOGLE_APPLICATION_CREDENTIALS JSON key. Writes default tables if ~/.cmapBQ/config.txt does not exist.

Parameters: path_to_credentials –
Returns: None (side effect)

cmapBQ.query module¶

cmapBQ.query.cmap_cell(client, cell_iname=None, cell_alias=None, ccle_name=None, primary_disease=None, cell_lineage=None, cell_type=None, table=None, verbose=False)¶

Query cellinfo table

Parameters

client – Bigquery Client
cell_iname – List of cell_inames
cell_alias – List of cell aliases
ccle_name – List of ccle_names
primary_disease – List of primary_diseases
cell_lineage – List of cell_lineages
cell_type – List of cell_types
table – table to query. This by default points to the siginfo table and normally should not be changed.
verbose – Print query and table address.

Returns

Pandas DataFrame

cmapBQ.query.cmap_compounds(client, pert_id=None, cmap_name=None, moa=None, target=None, compound_aliases=None, limit=None, verbose=False)¶

Query compoundinfo table for various field by providing lists of compounds, moa, targets, etc. ‘AND’ operator used for multiple conditions.

Parameters

client – BigQuery Client
pert_id – List of pert_ids
cmap_name – List of cmap_names
target – List of targets
moa – List of MoAs
compound_aliases – List of compound aliases
limit – Maximum number of rows to return
verbose – Print query and table address.

Returns

Pandas Dataframe matching queries

cmapBQ.query.cmap_genes(client, gene_id=None, gene_symbol=None, ensembl_id=None, gene_title=None, gene_type=None, feature_space='landmark', src=None, table=None, verbose=False)¶

Query geneinfo table. Geneinfo contains information about genes including ids, symbols, types, ensembl_ids, etc.

Parameters

client – Bigquery Client
gene_id – list of gene_ids
gene_symbol – list of gene_symbols
ensembl_id – list of ensembl_ids
gene_title – list of gene_titles
gene_type – list of gene_types
feature_space –
Common featurespaces to extract. ‘rid’ overrides selection

Choices: [‘landmark’, ‘bing’, ‘aig’]

landmark: 978 landmark genes

bing: Best-inferred set of 10,174 genes

aig: All inferred genes including 12,328 genes

Default is landmark.
src – list of gene sources
table – table to query. This by default points to the siginfo table and normally should not be changed.
verbose – Print query and table address.

Returns

Pandas DataFrame

cmapBQ.query.cmap_genetic_perts(client, pert_id=None, cmap_name=None, gene_id=None, gene_title=None, ensemble_id=None, table=None, verbose=False)¶

Query genetic_pertinfo table

Parameters

client – Bigquery Client
pert_id – List of pert_ids
cmap_name – List of cmap_names
gene_id – List of type INTEGER corresponding to gene_ids
gene_title – List of gene_titles
ensemble_id – List of ensumble_ids
table – table to query. This by default points to the siginfo table and normally should not be changed.
verbose – Print query and table address.

Returns

cmapBQ.query.cmap_matrix(client, data_level='level5', feature_space='landmark', rid=None, cid=None, verbose=False, chunk_size=1000, table=None, limit=4000)¶

Query for numerical data for signature-gene level data.

Parameters

client – Bigquery Client
data_level – Data level requested. IDs from siginfo file correspond to ‘level5’. Ids from instinfo are available in ‘level3’ and ‘level4’. Choices are [‘level5’, ‘level4’, ‘level3’]
rid – Row ids
cid – Column ids
feature_space –
Common featurespaces to extract. ‘rid’ overrides selection

Choices: [‘landmark’, ‘bing’, ‘aig’]

landmark: 978 landmark genes

bing: Best-inferred set of 10,174 genes

aig: All inferred genes including 12,328 genes

Default is landmark.
chunk_size – Runs queries in stages to avoid query character limit. Default 1,000
limit – Soft limit for number of signatures allowed. Default is 4,000.
table – Table address to query. Overrides ‘data_level’ parameter. Generally should not be used.
verbose – Print query and table address.

Returns

GCToo object

cmapBQ.query.cmap_profiles(client, sample_id=None, pert_id=None, pert_type=None, cmap_name=None, cell_iname=None, det_plate=None, build_name=None, return_fields='priority', limit=None, table=None, verbose=False)¶

Query per sample metadata, corresponds to level 3 and level 4 data, AND operator used for multiple conditions.

Parameters

client – Bigquery client
sample_id – list of sample_ids
pert_id – list of pert_ids
pert_type – list of pert_types. Avoid using only this parameter as the return could be very large.
cmap_name – list of cmap_names
det_plate – list of det_plates
build_name – list of builds
return_fields – [‘priority’, ‘all’]
limit – Maximum number of rows to return
table – table to query. This by default points to the siginfo table and normally should not be changed.
verbose – Print query and table address.

Returns

Pandas Dataframe

cmapBQ.query.cmap_sig(client, sig_id=None, pert_id=None, pert_type=None, cmap_name=None, cell_iname=None, det_plates=None, build_name=None, return_fields='priority', limit=None, table=None, verbose=False)¶

Query level 5 metadata table. Multiple parameters are filtered using the ‘AND’ operator

Parameters

client – Bigquery Client
sig_id – list of sig_ids
pert_id – list of pert_ids
pert_type – list of pert_types. Avoid using only this parameter as the return could be very large.
cmap_name – list of cmap_name, formerly pert_iname
cell_iname – list of cell names
det_plates – list of det_plates. det_plates values are the concatenation of values from

instinfo det_plate field with the ‘|’ delimiter used. :param build_name: list of builds :param return_fields: [‘priority’, ‘all’] :param limit: Maximum number of rows to return :param table: table to query. This by default points to the level 5 siginfo table and normally should not be changed. :param verbose: Print query and table address. :return: Pandas Dataframe

cmapBQ.query.get_bq_client()¶

Return authenticated BigQuery client object.

Parameters: config – optional path to config if not default
Returns: BigQuery Client

cmapBQ.query.get_table_info(client, table_id)¶

Query a table address within client’s permissions for schema.

Parameters

client – Bigquery Client
table_id – table address as {dataset}.{table_id}

Returns

Pandas Dataframe of column names. Note: Not all column names are query-able but all will be returned from a given metadata table

cmapBQ.query.list_cmap_compounds(client)¶

List available compounds

Parameters: client – BigQuery Client
Returns: Single column Dataframe of compounds

cmapBQ.query.list_cmap_moas(client)¶

List available MoAs

Parameters: client – BigQuery Client
Returns: Single column Dataframe of MoAs

cmapBQ.query.list_cmap_targets(client)¶

List available targets

Parameters: client – BigQuery Client
Returns: Pandas DataFrame

cmapBQ.query.list_tables()¶

Print table addresses. Comes from defaults in config.

Returns: None

cmapBQ.query.run_query(client, query)¶

Runs BigQuery queryjob

Parameters

client – BigQuery client object
query – Query to run as a string

Returns

QueryJob object

cmapBQ.utils module¶

cmapBQ.utils.csv_to_gctx(filepaths, outpath, use_gctx=True)¶

Convert list of csv files to gctx. CSVs must have ‘rid’, ‘cid’ and ‘value’ columns No other columns or metadata is preserved.

Parameters

filepaths – List of paths to CSVs
outpath – output directory of file
use_gctx – use GCTX HDF5 format. Default is True

Returns

cmapBQ.utils.long_to_gctx(df)¶

Converts long csv table to GCToo Object. Dataframe must have ‘rid’, ‘cid’ and ‘value’ columns No other columns or metadata is preserved.

Parameters: df – Long form pandas DataFrame
Returns: GCToo object