ggca 1.0.0

Computes efficiently the correlation (Pearson, Spearman or Kendall) and the p-value (two-sided) between all the pairs from two datasets
Documentation
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use crate::correlation::CorResult;

pub type VecOfResults = Vec<CorResult>;
// A tuple with Gene/GEM, Cpg Site ID (optional), and a vec of values
pub type TupleExpressionValues = (String, Option<String>, Vec<f64>);
pub type LazyMatrixInner = Box<dyn Iterator<Item = TupleExpressionValues>>;
pub type CollectedMatrix = Vec<TupleExpressionValues>;