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Example data

Example datasets are provided at the data/ directory of this repository. Users can use them to explore the different features available in iCARE and examine the outputs that they generate.

• bc_model_covariates_info.json: a JSON file containing the metadata about the risk factors present in the covariate dataset (reference_covariate_data.csv). For each risk factor, the provided metadata includes information such as— the data type (type; either "continuous" or "discrete"), a list of categories if the variable is discrete (levels), and optionally the reference category of the discrete variable (ref). If a reference category is not provided for a discrete variable, the first listed category under (levels) is assumed to be the reference value.

• bc_model_formula.txt: a patsy formula, which is a symbolic description of the covariate model to be fitted. Patsy is a Python substitute for R's formula class objects. If you are an R programmer, please read the patsy manual since it is not a perfect drop-in replacement for R's formula syntax.

• bc_72_snps.csv: published SNP information (odds ratios and SNP frequencies). Reference: Michailidou, Kyriaki, et al. "Association analysis identifies 65 new breast cancer risk loci." Nature 551.7678 (2017): 92-94..

• bc_model_log_odds_ratios.json:

• reference_covariate_data.csv:

Variable name	Description	Value encoding
id	Subject ID	A unique identifier for each individual.
famhist	Family history (of breast cancer among first degree relatives)	{0: "absence" (reference), 1: "presence"}
menarche_dec	Age at menarche (years)	{1: <=11 (reference), 2: 11-11.5, 3: 11.5-12, 5: 12-13, 8: 13-14, 9: 14-15, 10: >=15}
parity	Parity (number of full-term pregnancies)	{0: nulliparous (reference), 1: 1, 2: 2, 3: 3, 4: >=4}
birth_dec	Age at first child birth (years)	{1: <=19 (reference), 2: 19-22, 3: 22-23, 4: 23-25, 7: 25-27, 8: 27-30, 9: 30-34, 10: 34-38, 11: >=38}
agemeno_dec	Age at menopause (years)	{1: <=40 (reference), 2: 40-45, 3: 45-47, 4: 47-48, 5: 48-50, 6: 50-51, 7: 51-52, 8: 52-53, 9: 53-55, 10: >=55}
height_dec	Height (meters)	{1: <=1.55 (reference), 2: 1.55-1.57, 3: 1.57-1.60, 4: 1.60-1.61, 5: 1.61-1.63, 6: 1.63-1.65, 7: 1.65-1.66, 8: 1.66-1.68, 9: 1.68-1.71, 10: >=1.71}
bmi_dec	Body mass index (kg/m2)	{1: <=21.5 (reference), 2: 21.5-23, 3: 23-24.2, 4: 24.2-25.3, 5: 25.3-26.5, 6: 26.5-27.8, 7: 27.8-29.3, 8: 29.3-31.4, 9: 31.4-34.6, 10: >=34.6}
rd_menohrt	Use of Hormone Replacement Therapy (HRT)	{0: "pre-menopausal" (reference), 1: "post-menopausal and never HRT user", 2: "post-menopausal and ever HRT user"}
rd2_everhrt_e	Use of estrogen-only therapy	{0: "otherwise" (reference), 1: "post-menopausal and ever user of estrogen-only therapy"}
rd2_everhrt_c	Use of estrogen + progesterone combined therapy	{0: "otherwise" (reference), 1: "post-menopausal and ever user of combined therapy"}
rd2_currhrt	Current use of HRT	{0: "otherwise" (reference), 1: "post-menopausal and current HRT user"}
alcoholdweek_dec	Alcohol (drinks/week)	{1: "none" (reference), 4: 0-0.4, 5: 0.4-0.8, 6: 0.8-1.5, 7: 1.5-3.2, 8: 3.2-5.7, 9: 5.7-9.8, 10: >9.8}
ever_smoke	Smoking status	{0: "never" (reference), 1: "ever"}

• new_covariates_profile.csv: a test dataset specifying the risk factors (same variables as in the reference covariate dataset reference_covariate_data.csv) of three hypothetical individuals.

• new_snp_profile.csv: a test dataset specifying the allele dosages for the breast cancer-associated SNPs (same SNPs as in the bc_72_snps.csv file) of three hypothetical individuals. Note that some of the SNPs for some individuals are missing.

• validation_cohort_data.csv: a simulated dataset of a full cohort study of 50,000 individuals. This dataset helps illustrate the model validation capabilities of iCARE. The variables in this dataset are as follows.

Variable name	Description	Value encoding
study_entry_age	Age at study entry (years)	continuous (integer)
study_exit_age	Age at study exit (years)	continuous (integer)
observed_outcome	Disease status	{0: "normal", 1: "case"}
time_of_onset	Time (in years) from study entry to the development of the disease. Set to Inf if the subject did not develop the disease during the follow-up period.	continuous (float)
observed_followup	Number of years that the subject was followed-up in the study i.e. the difference between the age at study entry and the age at study exit.	continuous (integer)

• validation_nested_case_control_data.csv: a simulated dataset of a case-control study of 5,285, nested within a cohort study. Inclusion?