Quick Reference

To see help pages while you work type:

help(function)

example:

help(fetch_rows)

Import available cdapython functions¶

In [2]:

from cdapython import tables, columns, column_values, fetch_rows, summary_counts

from cdapython import tables, columns, column_values, fetch_rows, summary_counts

Get a list of searchable CDA tables¶

In [3]:

tables()

tables()

Out[3]:

['diagnosis',
 'file',
 'researchsubject',
 'somatic_mutation',
 'specimen',
 'subject',
 'treatment']

Explore CDA tables' columns in detail¶

In [4]:

columns()

columns()

Out[4]:

table	column	data_type	nullable	description
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See what values are populated in a given column¶

In [5]:

column_values( 'primary_diagnosis_site' )

column_values( 'primary_diagnosis_site' )

Out[5]:

primary_diagnosis_site	count
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Fetch subject row summary information for a column value¶

In [6]:

summary_counts( table= 'subject', match_all = 'primary_diagnosis_site = kid*')

summary_counts( table= 'subject', match_all = 'primary_diagnosis_site = kid*')

Out[6]:

[   total_subject_matches
 0                   2731,
    total_related_files
 0               527032,
   system  count
 0    GDC   2427
 1    IDC   1380
 2    PDC    228
 3    CDS    216,
       sex  count
 0    male   1482
 1  female    949
 2       M    122
 3       F     89
 4    Male     49
 5  Female     35
 6              5,
                                         race  count
 0                                      White   1597
 1                                               812
 2                  Black or African American    277
 3                                      Asian     42
 4           American Indian or Alaska Native      2
 5  Native Hawaiian or Other Pacific Islander      1,
                 ethnicity  count
 0                           1344
 1  Not Hispanic or Latino   1343
 2                   White     44,
             cause_of_death  count
 0                            2564
 1           Cancer Related    154
 2                Infection      7
 3       Not Cancer Related      4
 4  Cardiovascular Disorder      1
 5    Surgical Complication      1]

Fetch rows from any table for a column value¶

subject dataresearch subject dataspecimen datadiagnosis datatreatment datamutation data

fetch_rows( table= "subject", match_all='primary_diagnosis_site = kid*' )

fetch_rows( table= "researchsubject", match_all='primary_diagnosis_site = kid*' )

fetch_rows( table= "specimen", match_all='primary_diagnosis_site = kid*' )

fetch_rows( table= "diagnosis", match_all='primary_diagnosis_site = kid*' )

fetch_rows( table= "treatment", match_all='primary_diagnosis_site = kid*' )

fetch_rows( table= "somatic_mutation", match_all='primary_diagnosis_site = kid*' )

Fetch subject rows for a column value¶

In [7]:

fetch_rows( table= 'somatic_mutation', match_all = 'subject_id = TCGA.TCGA-04-1369')

fetch_rows( table= 'somatic_mutation', match_all = 'subject_id = TCGA.TCGA-04-1369')

Out[7]:

case_id	cda_subject_id	entrez_gene_id	file_gdc_id	hgnc_id	transcript_id	aliquot_barcode_normal	aliquot_barcode_tumor	all_effects	allele	amino_acids	appris	bam_file	biotype	callers	canonical	case_barcode	ccds	cdna_position	cds_position	center	chromosome	clin_sig	codons	consequence	context	cosmic	dbsnp_rs	dbsnp_val_status	distance	domains	end_position	ensp	esp_aa_af	esp_ea_af	existing_variation	exon	exon_number	feature	feature_type	flags	gdc_filter	gene	gene_pheno	gnomad_af	gnomad_afr_af	gnomad_amr_af	gnomad_asj_af	gnomad_eas_af	gnomad_fin_af	gnomad_nfe_af	gnomad_non_cancer_af	gnomad_non_cancer_afr_af	gnomad_non_cancer_ami_af	gnomad_non_cancer_amr_af	gnomad_non_cancer_asj_af	gnomad_non_cancer_eas_af	gnomad_non_cancer_fin_af	gnomad_non_cancer_max_af_adj	gnomad_non_cancer_max_af_pops_adj	gnomad_non_cancer_mid_af	gnomad_non_cancer_nfe_af	gnomad_non_cancer_oth_af	gnomad_non_cancer_sas_af	gnomad_oth_af	gnomad_sas_af	hgvs_offset	hgvsc	hgvsp	hgvsp_short	high_inf_pos	hotspot	hugo_symbol	impact	intron	mane	match_norm_seq_allele1	match_norm_seq_allele2	match_norm_validation_allele1	match_norm_validation_allele2	matched_norm_aliquot_barcode	matched_norm_aliquot_uuid	max_af	max_af_pops	mirna	motif_name	motif_pos	motif_score_change	muse	mutation_status	mutect2	n_alt_count	n_depth	n_ref_count	ncbi_build	normal_submitter_uuid	one_consequence	pheno	pick	pindel	polyphen	primary_site	project_short_name	protein_position	pubmed	reference_allele	refseq	rna_alt_count	rna_depth	rna_ref_count	rna_support	sample_barcode_normal	sample_barcode_tumor	score	sequence_source	sequencer	sequencing_phase	sift	somatic	start_position	strand	swissprot	symbol	symbol_source	t_alt_count	t_depth	t_ref_count	thousg_af	thousg_afr_af	thousg_amr_af	thousg_eas_af	thousg_eur_af	thousg_sas_af	transcript_strand	transcription_factors	trembl	tsl	tumor_aliquot_barcode	tumor_aliquot_uuid	tumor_seq_allele1	tumor_seq_allele2	tumor_submitter_uuid	tumor_validation_allele1	tumor_validation_allele2	uniparc	uniprot_isoform	validation_method	validation_status	variant_class	variant_classification	variant_type	varscan2	verification_status
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