Package index

Data

Create and manipulate lineage frequency data

lfq_data()

Create a lineage frequency data object

is_lfq_data()

Test if an object is an lfq_data object

as_lfq_data()

Coerce to lfq_data

as.data.frame(<lfq_data>)

Convert lfq_data to long-format tibble

read_lineage_counts()

Read lineage count data from a CSV file

simulate_dynamics()

Simulate lineage frequency dynamics

collapse_lineages()

Collapse rare lineages into an aggregate group

filter_sparse()

Filter sparse time points and lineages

Modeling

Fit frequency dynamics models

fit_model()

Fit a lineage frequency model

lfq_engines()

List available modeling engines

register_engine()

Register a custom modeling engine

unregister_engine()

Remove a registered engine

Pipe API

Tidyverse-style chaining

lfq_fit()

Pipe-friendly model fitting

lfq_advantage()

Pipe-friendly growth advantage extraction

lfq_forecast()

Pipe-friendly forecasting

lfq_score()

Pipe-friendly backtesting + scoring

lfq_summary()

Convert lfq_fit results to a summary tibble

Inference

Extract growth advantages and forecasts

growth_advantage()

Extract growth advantage estimates

forecast()

Forecast lineage frequencies (generic)

forecast(<lfq_fit>)

Forecast lineage frequencies

summarize_emerging()

Summarize emerging lineages

sequencing_power()

Sequencing power analysis

Calibration & Uncertainty

Assess and correct prediction interval calibration

calibrate()

Calibration diagnostics for lineage frequency forecasts

conformal_forecast()

Conformal prediction intervals for lineage frequencies

recalibrate()

Recalibrate prediction intervals

plot(<calibration_report>)

Plot calibration diagnostics

Fitness & Immunity

Decompose growth advantage into transmissibility and immune escape

fitness_decomposition()

Decompose variant fitness into transmissibility and immune escape

immune_landscape()

Construct a population immunity landscape

fit_dms_prior()

Fit model with Deep Mutational Scanning priors

selective_pressure()

Population-level selective pressure from variant dynamics

plot(<fitness_decomposition>)

Plot fitness decomposition

plot(<immune_landscape>)

Plot population immunity landscape

tidy.fitness_decomposition()

Tidy a fitness decomposition

Surveillance Optimization

Information-theoretic resource allocation and emergence detection

surveillance_value()

Expected Value of Information for genomic surveillance

adaptive_design()

Adaptive sequencing allocation via Thompson sampling

alert_threshold()

Sequential detection of emerging variants

detection_horizon()

Detection horizon for an emerging variant

surveillance_dashboard()

Comprehensive surveillance quality dashboard

plot(<adaptive_allocation>)

Plot adaptive allocation

plot(<evoi>)

Plot EVOI curve

Backtesting

Evaluate forecast accuracy

backtest()

Rolling-origin backtesting of lineage frequency models

score_forecasts()

Score backtest forecast accuracy

compare_models()

Compare model engines from backtest scores

Visualization

Publication-ready plots

autoplot(<lfq_fit>)

Plot lineage frequency model results

autoplot(<lfq_forecast>)

Plot a lineage frequency forecast

plot_backtest()

Plot backtest scores

S3 Methods

Standard R model interface

print(<lfq_fit>)

Print a lineage frequency model

summary(<lfq_fit>)

Summarise a lineage frequency model

coef(<lfq_fit>)

Extract coefficients from a lineage frequency model

tidy.lfq_fit()

Tidy an lfq_fit object

glance.lfq_fit()

Glance at an lfq_fit object

augment.lfq_fit()

Augment data with fitted values from an lfq_fit object

Utilities

lfq_stan_available()

Check if 'CmdStan' backend is available

lfq_version()

Package version and system information

Datasets

Built-in example datasets

sarscov2_us_2022

Simulated SARS-CoV-2 variant frequency data (US, 2022)

cdc_ba2_transition

CDC SARS-CoV-2 variant proportions: BA.1 to BA.2 transition (US, 2022)

cdc_sarscov2_jn1

CDC SARS-CoV-2 variant proportions: JN.1 emergence (US, 2023-2024)

influenza_h3n2

Simulated influenza A/H3N2 clade frequency data