Query parquet

The query module provides the ability to quickly search through Parquet files.

Basic query

Basic query operations allow you to query all samples, peptides, proteins, genes, and MZML files. The query results will be deduplicated and then returned in a list format.

from quantmsio.core.query import Parquet
P = Parquet('PXD007683.feature.parquet')
P.get_unique_samples()
"""
['PXD007683-Sample-3',
'PXD007683-Sample-9',
'PXD007683-Sample-4',
'PXD007683-Sample-6',
'PXD007683-Sample-11',
'PXD007683-Sample-7',
'PXD007683-Sample-1',
'PXD007683-Sample-10',
'PXD007683-Sample-8',
'PXD007683-Sample-2',
'PXD007683-Sample-5']
"""
P.get_unique_peptides()
P.get_unique_proteins()
P.get_unique_genes()
P.get_unique_references()

Specific query

Specific queries allow you to individually search for certain values based on specific conditions. The results are returned in the form of a DataFrame.

P.query_peptide('QPAYVSK')
"""
    sequence    protein_accessions      protein_start_positions ...
    QPAYVSK     [sp|P36016|LHS1_YEAST]      [739]
    QPAYVSK     [sp|P36016|LHS1_YEAST]      [739]
    QPAYVSK     [sp|P36016|LHS1_YEAST]      [739]
    ...
"""
P.query_peptide('QPAYVSK',columns=['protein_start_positions','protein_end_positions'])

P.query_peptides(['QPAYVSK','QPCPSQYSAIK'],columns=None)
"""
    sequence    protein_accessions      protein_start_positions ...
    QPAYVSK     [sp|P36016|LHS1_YEAST]      [739]
    QPAYVSK     [sp|P36016|LHS1_YEAST]      [739]
    QPAYVSK     [sp|P36016|LHS1_YEAST]      [739]
    ...
    QPCPSQYSAIK [sp|O95861|BPNT1_HUMAN]     [98]
    ...
"""

P.query_protein('P36016',columns=None)
P.query_proteins(['P36016','O95861'],columns=None)
"""
    sequence    protein_accessions      protein_start_positions ...
    QPAYVSK     [sp|P36016|LHS1_YEAST]      [739]
    QPAYVSK     [sp|P36016|LHS1_YEAST]      [739]
    QPAYVSK     [sp|P36016|LHS1_YEAST]      [739]
    ...
    QPCPSQYSAIK [sp|O95861|BPNT1_HUMAN]     [98]
    ...
"""

P.get_samples_from_database(['PXD007683-Sample-3','PXD007683-Sample-9'],columns=None)
"""
sequence                protein_accessions          sample_accession
AAAAAAAAAAAAAAAGAGAGAK  [sp|P55011|S12A2_HUMAN]     PXD007683-Sample-3
AAAAAAAAAAAAAAAGAGAGAK  [sp|P55011|S12A2_HUMAN]     PXD007683-Sample-3
AAAAAAAAAK              [sp|Q99453|PHX2B_HUMAN]     PXD007683-Sample-3
"""
P.get_report_from_database(['a05063','a05059'],columns=None) # mzml
"""
sequence    protein_accessions      reference_file_name
AAAAAAALQAK [sp|P36578|RL4_HUMAN]   a05063
AAAAAAALQAK [sp|P36578|RL4_HUMAN]   a05063
AAAAAAALQAK [sp|P36578|RL4_HUMAN]   a05063
"""

Iter bacth

You can use the following method to produce values in batches.

 1for samples,df in P.iter_samples(file_num=10,columns=None):
 2    # A batch contains ten samples.
 3    print(samples,df)
 4
 5for df in P.iter_chunk(batch_size=500000,columns=None):
 6    # A batch contains 500,000 rows.
 7    print(df)
 8
 9for refs,df in P.iter_file(file_num=20,columns=None): # mzml
10    # A batch contains 20 mzML files.
11    print(refs,df)

Inject message

You can use the following method to fill in additional information.

1df = P.get_report_from_database(['a05063','a05059'],columns=None)
2df = P.inject_spectrum_msg(df, mzml_directory='./mzml')
3fasta = './Homo-sapiens-uniprot-reviewed-contaminants-decoy-202210.fasta'
4protein_dict = P.get_protein_dict(fasta_path=fasta)
5df = P.inject_position_msg(df, protein_dict)
6df = P.inject_gene_msg(df,fasta,map_parameter = "map_protein_accession",species = "human")