ConvergentSelector

Identifies "public antibodies" shared across independent repertoires, implementing the concept of convergent selection from TCR/BCR immunology as a biologically-motivated ensemble method.

Details

In real immunity, certain immune receptor sequences appear across multiple individuals (public clones), suggesting they are driven by common selection pressures. Similarly, antibodies that appear across multiple independent bHIVE runs represent the most robust patterns in the data.

Public fields

tolerance

Distance tolerance for matching antibodies across repertoires.

min_appearances

Minimum number of repertoires an antibody must appear in to be considered "public".

public_antibodies

The identified public antibodies.

Methods

Public methods

• ConvergentSelector$new()

• ConvergentSelector$find_public()

• ConvergentSelector$from_results()

• ConvergentSelector$print()

• ConvergentSelector$clone()

---

Method new()

Create a new ConvergentSelector.

Usage

ConvergentSelector$new(tolerance = 0.5, min_appearances = 2)

Arguments

tolerance

Numeric. Maximum distance for two antibodies to be considered the same across repertoires.

min_appearances

Integer. Minimum repertoires for an antibody to be public.

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Method find_public()

Find public antibodies shared across multiple repertoires.

Usage

ConvergentSelector$find_public(repertoires, distFunc = "euclidean")

Arguments

repertoires

List of ImmuneRepertoire objects or list of antibody matrices.

distFunc

Character. Distance function for matching.

Returns

Numeric matrix of public (consensus) antibodies.

---

Method from_results()

Run convergent selection from multiple bHIVE results.

Usage

ConvergentSelector$from_results(results, distFunc = "euclidean")

Arguments

results

List of bHIVE result objects (each with $antibodies).

distFunc

Character. Distance function.

Returns

Numeric matrix of consensus antibodies.

---

Method print()

Print summary.

Usage

ConvergentSelector$print(...)

Arguments

...

Not used.

---

Method clone()

The objects of this class are cloneable with this method.

Usage

ConvergentSelector$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

# Find public antibodies across multiple runs
data(iris)
X <- as.matrix(iris[, 1:4])
results <- lapply(1:3, function(i) {
  m <- AINet$new(nAntibodies = 15, maxIter = 5, verbose = FALSE)
  m$fit(X, task = "clustering")
  m$result
})
conv <- ConvergentSelector$new(tolerance = 1.0, min_appearances = 2)
public <- conv$from_results(results)
nrow(public)  # consensus antibodies
#> [1] 13