Package index
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run_pairing()experimental - Find TCRalpha/beta pairs from individual well read counts
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load_tirtlseq()experimental - Load data from TIRTLseq experiments
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add_metadata()experimental - Add metadata to a TIRTLseqDataSet object
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filter_dataset()experimental - Subset a TIRTLseqDataSet object
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reorder_samples()experimental - Re-order samples in a TIRTLseqDataSet object
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TIRTL_process()experimental - Run data processing functions on a TIRTLseqDataSet object
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add_single_chain_data()experimental - Add single-chain read counts/fractions to the paired TCR data
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clean_pairs()experimental - Remove excess pairs for individual single chains
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filter_duplicate_tcrs()experimental - Remove duplicate TCRs from a data frame
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filter_mait()experimental - Remove MAIT (Mucosal-Associated Invariant T cells) TCRs
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filter_nonfunctional_TCRs()experimental - Remove TCRs with nonfunctional CDR3 amino acid sequences
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filter_short_cdr3s()experimental - Remove TCRs with short CDR3 loops
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filter_v_alleles()experimental - Remove TCRs with unknown V-segments
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identify_non_functional_seqs()experimental - Identify TCRs that contain non-functional CDR3 sequences
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identify_paired()experimental - Identify which single chains were paired
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prep_for_tcrdist()experimental - Prepare paired TCRs for TCRdist calculation
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remove_duplicates()experimental - Removes duplicate paired TCRs
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get_all_tcrs()experimental - Returns all of the paired TCRs from all samples in a dataset
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get_pair_stats()experimental - Count the number of pairs called by each algorithm
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get_paired_by_read_fraction_range()experimental - Calculate the number and fraction of single chains that were paired by frequency
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plot_n_reads()experimental - Bar plot of the number of single-chain reads for each sample
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plot_num_partners()experimental - Stacked bar plot of the fraction of alpha/beta chains with different numbers of partners
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plot_paired()experimental - Stacked bar plot of the number of TCRs paired by each algorithm
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plot_paired_by_read_fraction_range()experimental - Bar plot of the fraction of paired single chains by frequency
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plot_paired_vs_rank()experimental - A step plot of the cumulative number of paired/unpaired alpha/beta chains among the most frequent chains
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plot_pairs_with_eachother()experimental - A connected point plot of read fraction vs. rank for the most frequent alpha/beta chains
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plot_ranks()rank_plot()experimental - Line plot of clonotype rank vs. read fraction for each sample
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plot_read_fraction_vs_pair_status()experimental - A point plot of read fraction vs. rank for the most frequent alpha/beta chains
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plot_sample_overlap()sample_overlap()experimental - Plot the overlap/agreement between samples (in terms of most frequent clones)
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summarize_data()experimental - Create a summary table with number of reads and unique alpha/beta chains
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TCRdist()experimental - GPU implementation of TCRdist, a distance/similarity metric for pairs of TCRs
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TCRdist_cpp()experimental - Parallelized C++ implementation of TCRdist (no GPU required)
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cluster_tcrs()experimental - Cluster TCRs (using the Leiden algorithm) based on their pairwise TCRdist values
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plot_clusters()experimental - Plot clusters of similar TCRs
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plot_clone_size_across_samples()experimental - Line plot of clone read fraction across multiple samples
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plot_sample_vs_sample()experimental - Scatterplot of TCR clone read fraction of clones between two samples
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calculate_diversity()diversity()experimental - Calculate TCR repertoire diversity metrics
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get_all_div_metrics()experimental - Returns all diversity metric options for
calculate_diversity() -
plot_clonotype_indices()experimental - Stacked bar chart with fractions of reads attributed to the most frequent clonotypes
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plot_diversity()experimental - Bar plot of clonal diversity metrics
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create_thimble_df()experimental - Convert paired TCRs to a "thimble" data frame for Stitchr
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write_stitchr_tsv()experimental - Write a tab-separated "thimble" text file for use with Stitchr
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choose_pair_manual()experimental - Choose a partner manually for an input chain using T-SHELL
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get_well_subset()experimental - Get well names from numerical rows and columns
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get_wells_from_edges()experimental - Get well names from the top left and bottom right wells
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load_well_counts_binary()experimental - Load well-level data written to binary format
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plot_tshell()experimental - Calculate and plot read fraction correlation across wells (T-SHELL)
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write_well_data_to_binary()experimental - Convert individual well .tsv files to faster loading binary format