Phenofhy

Quickstart ​

Phenofhy helps you extract, process, and summarize OFH phenotype data inside the TRE, and also supports local testing on simulated data.

Prerequisites ​

  • You are running inside the OFH TRE with the dx toolkit available.
  • Phenofhy is installed in the notebook environment.
  • phenofhy.init() has been run once for the current DNAnexus project.
  • If you have not uploaded Phenofhy to the TRE yet, see the Installation page.

For local testing, you can skip TRE prerequisites and start with simulated data (see Simulating data locally).

Initialize Phenofhy ​

Run this once per DNAnexus project:

python
import phenofhy

phenofhy.init()

In later sessions, start with import phenofhy; the project configuration is downloaded automatically when needed.

Minimal workflow ​

python
from phenofhy import extract, process, calculate, profile, utils

# 1) Extract a small set of fields
extract.fields(
    output_file="outputs/raw/phenos.csv",
    fields=[
        "participant.registration_year",
        "participant.registration_month",
        "participant.birth_year",
        "participant.birth_month",
        "participant.demog_sex_2_1",
        "questionnaire.smoke_status_2_1",
    ],
)

# 2) Process participant data (derives age, sex, age_group)
df = process.participant_fields("outputs/raw/phenos.csv")

# 3) Summaries
summary = calculate.summary(
    df,
    traits=["derived.age_at_registration", "derived.sex"],
    stratify="derived.sex",
)

# 4) Profile report
report = profile.phenotype_profile(
    df,
    phenotype="derived.age_at_registration",
    output="outputs/reports/age_profile.pdf",
)

# 5) Upload your results
report = utils.upload_files(
   files="outputs/reports/age_profile.pdf",
   dx_target="results"
)

Next steps ​

  • Use calculate.prevalence() for prevalence tables.
  • Use icd.match_icd_traits() to match ICD codes to traits.
  • Use process.questionnaire_fields() or process.clinic_measurements_fields() to work by entity.

Local quick test (no TRE access required) ​

python
from phenofhy.simulate import simulate_phenotype_df
from phenofhy import process, calculate

df = simulate_phenotype_df(sample=1000, seed=42)
df = process.participant_fields(df)

summary = calculate.summary(
    df,
    traits=["derived.age_at_registration", "derived.sex"],
    stratify="derived.sex",
)