Package index • qSIP2

qSIP Data Objects

qsip_data(): qSIP master data class
qsip_source_data(): qSIP source data class
qsip_sample_data(): qSIP sample data class
qsip_feature_data(): qSIP feature table class

qSIP2 EAF Workflow

get_comparison_groups(): Get comparison groups
run_feature_filter(): Filter features in a qSIP data object
run_resampling(): Resample WAD values
run_EAF_calculations(): Calculate EAF values
summarize_EAF_values(): Summarize the observed and resampled EAF values
run_comparison_groups(): Run comparison groups

qSIP2 Growth Workflow

get_N_total_it(): Calculate total abundances at timepoint t
run_growth_calculations(): Run growth calculations
summarize_growth_values(): Summarize growth values

Helper Functions

infer_source_data(): Generate a source data frame from a sample data frame
add_isotopolog_label(): Add isotopolog_label to source data
remove_isotopolog_label(): Remove isotopolog_label from "MISIPified" data
get_all_by_isotope(): Get source_mat_ids meeting certain isotope conditions
get_dataframe: Return the original dataframe from a qsip_feature_data object
get_resample_counts(): Get counts of successful resampling
get_resample_data(): Get dataframe of resampled data
get_feature_ids(): Return the feature_ids in a qsip object
get_filtered_feature_summary(): Return filtering info for a specific feature ID
get_source_mat_ids(): Return the source_mat_ids in a qsip object
get_growth_data(): Get dataframe of resampled growth data
get_filter_results(): Tabular output summarizing filtering
get_EAF_data(): Get EAF value for a qSIP object
resample_seed(): Seed used in resampling
n_resamples(): Number of resamples
add_gradient_pos_rel_amt(): Add gradient_pos_rel_amt to data
add_taxonomy(): Add a taxonomy table to qSIP abundance data
correct_gradient_pos_density(): Correct sample density values using gradient position information
get_unshared_ids(): Show missing source_mat_ids and sample_ids
is_qsip_data(): Check object is qsip_data type
is_qsip_data_list(): Validate a multi-qsip list object
is_qsip_filtered(): Validate a qsip object has been filtered
is_qsip_resampled(): Validate a qsip object has been resampled
is_qsip_EAF(): Validate a qsip object has EAF values
is_qsip_growth(): Validate a qsip object has been run through growth workflow
qsip_object_size(): Return the size of qsip data objects or each slot
qsip_clean(): Clean large data from qSIP object

WAD Corrections

correct_gpd_bootstrap(): Correct gradient position density (gpd) values using bootstrapped features
correct_gpd_rlm(): Correct gradient position density (gpd) values using linear regression approach
plot_corrected_curves(): Plot curves of corrected sample curves versus reference
plot_correction_stats(): Plot the correction statistics
plot_difference_to_mean(): Plot difference between feature WAD and WAD reference
get_correction_compression(): Get compression values from a rlm correction
plot_correction_compression(): Plot correction compression

Plots and Visualizations

plot_sample_curves(): Plot qSIP sample data density curves
plot_source_wads(): Plot the source WADs by isotope
plot_density_outliers(): Cook's outlier detection on gradient positions vs densities
plot_feature_curves(): Plot qSIP feature data density curves
plot_filter_results(): Plot the results of filtering features
plot_feature_occurrence(): Plot occurrence of features in samples
plot_successful_resamples(): Plot the number of successful resamples for each feature_id
plot_feature_resamplings(): Plot the resampled EAFs for each feature
plot_EAF_values(): Plot EAF and confidence intervals
plot_growth_values(): Plot growth values

Spike-In Controls

jgi_source_df(): Make a source dataframe from JGI proposal file
jgi_sample_df(): Make a sample dataframe from JGI proposal file
jgi_feature_df(): Make a feature dataframe from a JGI coverage file
jgi_normalize_features(): Normalize feature coverages according to spike-in controls with a known ratio
get_normalized_features(): Get normalized features from jgi_normalize_features
get_normalized_controls(): Get normalized controls from jgi_normalize_features

Datasets

example_source_df: Example Source Dataframe
example_sample_df: Example Sample Dataframe
example_feature_df: Example Feature Abundance Dataframe
example_source_object: Example qSIP Source Object
example_sample_object: Example qSIP Sample Object
example_feature_object: Example qSIP Feature Object
example_qsip_object: Example qSIP Object
example_group_dataframe: Example data frame for run_comparison_groups()
example_qsip_growth_object: Example qSIP Growth Object
example_qsip_growth_t0: Example qSIP Time Zero Growth Dataframe
isotope_palette: Color palettes for isotopes
source_palette: An expanding color palette
jgi_mixes: JGI control sequences
valid_isotope_names: Valid isotope names