Package index • iceqream

All functions

show(<IQFeature>): IQFeature class

initialize(<IQFeatureGroup>) show(<IQFeatureGroup>): IQFeatureGroup class

show(<IQSeqFeature>): IQSeqFeature class

show(<IQmodel>): IQmodel class

show(<PBM>): PBM Class

show(<TrajectoryModel>): TrajectoryModel Class

show(<TrajectoryModelMulti>): TrajectoryModelMulti Class

add_features_r2(): Add Features R^2

add_interactions(): Add interactions to a trajectory model

add_motif_models_to_traj(): Add motif models to trajectory model

compute_motif_directional_hits(): Compute motif directional hits

compute_motif_energies(): Compute Motif Energies

compute_tracks_q(): Compute tracks quantiles

compute_traj_model_spatial_freq(): Compute spatial frequency of motifs in trajectory model

create_default_additional_features(): Create Default Additional Features

create_dinuc_feature_group(): Create Dinucleotide Feature Group

create_dinuc_features(): Create Dinucleotide Features

create_iq_model(): Create an IQmodel from a trajectory model

create_iq_seq_feature(): Create an IQSeqFeature from a trajectory model

create_logist_features(): Create Logistic Features

create_sequence_features(): Create Sequence Features

distill_traj_model(): Distill trajectory model

distill_traj_model_multi(): Distills multiple trajectory models

filter_multi_traj_model(): Filter multi-trajectory model

filter_multi_traj_model_by_beta(): Filter multi-trajectory model by beta

filter_traj_model(): Filter a trajectory model using punctuated regression.

filter_traj_model_intervals(): Filter trajectory model intervals

homogenize_pssm_models(): Homogenize a list of PSSM models

infer_trajectory_motifs(): Infer trajectory motifs using a pre-trained trajectory model

infer_trajectory_motifs_multi(): Infer trajectory motifs for a multi-trajectory model

initialize(<IQSeqFeature>): Initialize an IQSeqFeature object

iq_feature.compute_response(): Compute the IQ feature response

iq_feature_group.compute(): Compute features for an IQFeatureGroup

iq_feature_list.compute(): Compute features for a list of IQFeature and IQFeatureGroup objects

iq_feature_list.compute_response(): Compute IQ feature list response

iq_regression(): Perform IQ regression on peak intervals

iq_seq_feature.compute(): Compute the IQSeqFeature

learn_traj_prego(): Learn 'prego' models for ATAC difference of a trajectory

logist(): Logistic Function

match_traj_model_motif_names(): Match trajectory model motif names

merge_trajectory_motifs(): Merge Trajectory Motifs

motif_db: Motif Database

motif_db_scenic_clusters: SCENIC Motif Clusters

norm01(): Normalize Values to the 0-1 Range

norm0q(): Normalize a vector to a specified quantile

norm_energy(): Normalize Energy Values of a Vector

norm_energy_matrix(): Normalize Energy Matrix

normalize_const(): Normalize ATAC data using constitutive peaks

normalize_regional(): Normalize regional ATAC data using punctured windows

normalize_to_prob(): Convert normalized ATAC data to probability-like values

normalize_with_db_quantiles(): Normalize motif energies using pre-computed quantiles

pbm.compute(): Compute energies / response for a PBM on given sequences

pbm.compute_local(): Compute local PBM scores / response

pbm.gextract(): Extract PBM scores for genomic intervals

pbm.gextract_local(): Extract local PBM scores / response

pbm.normalize_energies(): Normalize energies for a PBM

pbm.normalize_energies_local(): Normalize energies locally for a PBM

pbm.trim_pssm(): Trim a PBM

pbm_list.compute(): Compute energies / response for a list of PBMs on given sequences

pbm_list.compute_local(): Extract local PBM scores / response for a list of PBMs given sequences

pbm_list.gextract(): Extract PBM scores / response for a list of PBMs

pbm_list.gextract_local(): Extract local PBM scores / response for a list of PBMs

pbm_list.multi_traj.compute_energy(): Compute energy for a list of pbm lists (multiple trajectories)

pbm_list.multi_traj.gextract_energy(): Extract energy for a list of pbm lists (multiple trajectories)

pbm_list.trim_pssm(): Trim a list of PBMs

plot_cell_type_normalization_scatter(): Create comparison scatter plots showing normalization effects between two cell types

plot_iq_locus(): Plot IQ Locus

plot_motif_energy_vs_response_boxplot(): Plot Motif Energy vs Response Boxplot

plot_motif_spatial_freq(): Plot motif spatial frequency

plot_multi_traj_model_report(): Plot multi-trajectory model report

plot_normalization_scatters(): Generate and save normalization visualization plots

plot_partial_response(): Plot Partial Response

plot_prediction_boxplot(): Plot a boxplot of observed vs predicted ATAC differences

plot_prediction_scatter(): Plot scatter plot of observed vs predicted ATAC difference

plot_traj_model_clusters_report(): Plot trajectory model clusters report

plot_traj_model_report(): Plot a report of trajectory motifs

plot_variable_vs_response(): Plot scatter of a variable vs ATAC difference

predict(<IQmodel>): Predict method for IQmodel

predict(<TrajectoryModel>): Predict TrajectoryModel on new data

preprocess_data(): Preprocess and normalize ATAC-seq data

regress_trajectory_motifs(): Perform motif regression on ATAC trajectories.

regress_trajectory_motifs_manifold(): Regress trajectory motifs of a full manifold (multiple trajectories)

relearn_traj_model(): Relearn Trajectory Model

remove_motif_models_from_traj(): Remove motif models from trajectory model

rename_motif_models(): Rename motif models in a trajectory model

rescale(): Rescale Values Based on Original Scale Factors

split_traj_model_to_train_test(): Split a trajectory model into train and test sets

traj_model_to_iq_feature_list(): Convert trajectory model to IQ feature list

traj_model_to_pbm_list(): Convert a trajectory model to a list of PBM objects

traj_model_variable_response(): Compute Partial Response for Trajectory Model