Inverse Optimal Transport for Single-Cell Trajectory Analysis

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Documentation for package ‘bioIOT’ version 0.2.2

• DESCRIPTION file
• User guides, package vignettes and other documentation
• Package NEWS
• Package README

Help Pages

build_state_features	Transition matrix, pseudotime and state features
collapse_probes	Collapse a probe-level expression matrix to gene level
demo_iot_states	Bundled bioIOT demo dataset
find_platform_file	Inspect a GEO RAW tar without extracting
fit_iot	Fit inverse optimal transport feature weights
gsm_id	Extract GSM ids from CEL filenames
has_cel_file	Inspect a GEO RAW tar without extracting
make_cost	Cost construction, likelihood and feature standardization
pathway_markers	IOT pathway marker genes (8 pathways)
plot_pathway_trend	bioIOT visualisation
plot_theta	bioIOT visualisation
plot_transition_flow	bioIOT visualisation
plot_transition_heatmap	bioIOT visualisation
print.bioIOT_fit	Fit inverse optimal transport feature weights
pseudotime_from_transition	Transition matrix, pseudotime and state features
row_ce_loss	Cost construction, likelihood and feature standardization
row_conditional	Semi-relaxed OT solver and row-conditional transitions
runIOT	Run IOT on a single-cell object
runIOT.default	Run IOT on a single-cell object
runIOT.matrix	Run IOT on a single-cell object
runIOT.Seurat	Run IOT on a single-cell object
runIOT.SingleCellExperiment	Run IOT on a single-cell object
score_pathways	Score bulk-cohort samples on the 8 IOT pathways
simulate_iot_states	Simulate single-cell state-transition data for bioIOT
soft_sinkhorn	Semi-relaxed OT solver and row-conditional transitions
summary.bioIOT_fit	Fit inverse optimal transport feature weights
transition_matrix	Transition matrix, pseudotime and state features
zscore_phi	Cost construction, likelihood and feature standardization