Algorithms for High-Throughput Sequencing of Antigen-Specific T Cells

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Documentation for package ‘alphabetr’ version 0.2.2

• DESCRIPTION file.
• User guides, package vignettes and other documentation.

Help Pages

bagpipe	Identify candidate alpha/beta pairs.
chain_scores	Calculate association scores between alpha and beta chain pairs.
combine_freq_results	Combines the frequency estimation results from single TCR clones and dual TCR clones
create_clones	Create a synthetic set of clones with a specific underlying clonal structure
create_data	Simulate sequencing data obtained from the alphabetr approach with a specified clonal structure
create_data_singlecells	Simulate sequencing data obtained single-cell sequencing
dual_discrim_dual_likelihood	Calculate likelihood of two beta-sharing candidate alpha-beta pairs deriving from a dual clone
dual_discrim_shared_likelihood	Calculate likelihood of two beta-sharing candidate alpha-beta pairs deriving from a dual clone
dual_eval	Calculate dual depths and false dual rates for simulated alphabetr experiments
dual_tail	Discriminate between beta-sharing clones and dual-alpha TCR clones (optimized for rare clones)
dual_top	Discriminate between beta-sharing clones and dual-alpha TCR clones (optimized for common clones)
freq_estimate	Estimation of frequencies of clones identified by 'alphabetr'
freq_eval	Calculate the precision, CV, and accuracy of frequency estimates
likelihood_dual	Calculate likelihood curve of frequency estimates for a dual-alpha or dual-beta TCR clone
likelihood_dualdual	Calculate likelihood curve of frequency estimates for a dual-alpha and dual-beta TCR clone
likelihood_single	Calculate likelihood curve of frequency estimates for a single TCR clone
read_alphabetr	Read in alphabetr sequencing data into the binary matrix form needed by bagpipe()