Introduction | Input | Novel allele detection | Inferring genotypes | Frequency genotyping approach | Bayesian genotyping approach | Correcting allele calls | Evidence | References

Introduction | Example data | Cells with multiple heavy chains in single cell data | Identifying clones by sequence identity | Identifying clones by hierarchical clustering | Identifying clones by spectral clustering

Example data | Load quality scores | Mask low quality positions

Identify clonal clusters | Obtain IMGT-gapped sequences | Construct clonal germlines

Reading AIRR Rearrangement sequencing data files | scRepertoire and Dowser compatability | Saving and loading Dowser objects in AIRR Clone JSON format | Saving and loading Dowser objects as RDS | Exporting trees in Newick format | Exporting and reading sequences as FASTA | Making and saving tree plots

Building Time Trees | Requirements | For Mac and Windows machines, we recommend: | For Linux machines, we recommend running: | Download and set up XML templates | Setting up data | Estimating the GC clock rate | Run getTimeTreesIterate with a TyCHE template | Visualize the results

Resolve light chains | Reconstruct germlines | Format clones | Building trees

Date randomization test | Set up data structures and trees | Perform date randomization test | Plot trees

Removing partial sequences | Removing "comb" artifacts | Simulating a comb artifact | Removing comb artifacts | Choosing parameters | Recommended order

Simulate mutations in a single sequence | Simulate mutations in a lineage tree

Example data | Generate a clonal abundance curve | Generate a diversity curve | View diversity tests at a fixed diversity order

Format clones | Build maximum parsimony trees | Build maximum likelihood trees | Build IgPhyML B cell trees | Building maximum likelihood trees with multiple partitions

Example data | Calculate the properties of amino acid sequences | Obtaining properties individually | Using user defined scales | Getting vectors of individual properties | Default scales

Example data | Tabulate V(D)J allele, gene or family usage by sample | Tabulating gene abundance using additional groupings

Discrete trait statistics | Caveats and interpreting results | Setting up IgPhyML | Set up data structures and trees | Visualize maximum parsimony trait reconstruction | Discrete trait analysis with fixed trees | Accounting for uncertainty in tree topology | Within and between lineage permutations | Controlling false positive rate through downsampling | Incorporating switching constraints

Saving sequences to a file

Example data | Calculating nearest neighbor distances (heavy chain sequences) | Calculating nearest neighbor distances (single-cell paired heavy and light chain sequences) | Using nearest neighbor distances to determine clonal assignment thresholds | Threshold determination by manual inspection | Automated threshold detection via smoothed density | Automated threshold detection via a mixture model | Calculating nearest neighbor distances independently for subsets of data | Calculating nearest neighbor distances across groups rather than within a groups | Speeding up pairwise-distance-matrix calculations with subsampling

Example data | Preprocessing | Constructing clonal consensus sequences | Incorporating lineage information | Calculate selection PDFs for individual sequences | Calculating selection in multiple steps | Calculating selection in one step | Using alternative mutation definitions and models | Group and convolve individual selection distributions | Grouping by a single annotation | Subsetting and grouping by multiple annotations | Convolving variables at multiple levels | Testing the difference in selection PDFs between groups | Plot and compare selection scores for groups | Editing a field in a Baseline object

Example data | Infer targeting model (substitution and mutability) | Visualize targeting model | Calculate targeting distance matrix

Basic plotting | Plotting metadata | Using ggtree and ggplot functions | Editing all trees at once | Saving trees to a file

Example data | Calculate the counts and frequencies of mutations over the entire sequence | Calculate mutations within subregions | Use amino acid physicochemical properties to define mutations

Reading data | Writing data