{- Edge.Correlation Gregory W. Schwartz Collections the functions pertaining to the generation of edges in a similarity matrix using different kinds of correlations as weights. -} {-# LANGUAGE BangPatterns #-} {-# LANGUAGE TupleSections #-} {-# LANGUAGE QuasiQuotes #-} {-# LANGUAGE GADTs #-} module Edge.Correlation ( getSimMatCorrelation , correlate ) where -- Standard import Control.Monad import Data.Bool import Data.List import Data.Maybe import qualified Data.Foldable as F import qualified Data.IntMap.Strict as IMap import qualified Data.Map.Strict as Map import qualified Data.Sequence as Seq import qualified Data.Set as Set -- Cabal import Control.Monad.Trans import Data.Graph.Inductive import Statistics.Correlation import Statistics.Distribution import Statistics.Distribution.StudentT import qualified Control.Foldl as Fold import qualified Control.Lens as L import qualified Data.Vector.Unboxed as VU import qualified Numeric.LinearAlgebra as N -- Local import Types import Utility getSimMatCorrelation :: EdgeMethod -> StandardLevel -> EdgeSimMatrix getSimMatCorrelation edgeMethod (StandardLevel level) = do EdgeSimMatrix . Fold.fold (Fold.Fold step begin extract) . pairs (,) . fmap (L.over L._2 F.toList) . Map.toList \$ level where n = fromIntegral . Map.size \$ level step acc x = case uncurry getCorr x of ((_, _), Nothing) -> acc ((!idx1, !idx2), (Just !val)) -> alterMap idx1 idx2 val . alterMap idx2 idx1 val \$ acc begin = IMap.empty extract = id alterMap new query val = IMap.alter ( maybe (Just . IMap.singleton new \$ val) (Just . IMap.insert new val) ) query getCorr ((!id1, !idx1), !x) ((!id2, !idx2), !y) = ((idx1, idx2), correlateEntities edgeMethod x y) -- | Correlate two groups of entities, where each group is a collection of -- measurements (specifically for a single type of entity, for instance -- a single protein). correlateEntities :: EdgeMethod -> [Maybe Entity] -> [Maybe Entity] -> Maybe Double correlateEntities edgeMethod e1 e2 = do let joined = VU.fromList . catMaybes . zipWith groupDataSets e1 \$ e2 guard \$ (VU.length joined > 2) && (not . VU.all (== (fst . VU.head \$ joined)) . VU.map fst \$ joined) && (not . VU.all (== (snd . VU.head \$ joined)) . VU.map snd \$ joined) let (Rho !coeff, P !pVal) = correlate edgeMethod joined guard \$ pVal < 0.05 return coeff -- | Correlate two lists with p values. correlate :: EdgeMethod -> VU.Vector (Double, Double) -> (Rho, P) correlate method xs = (Rho (coeff method), P (pVal s)) where n = fromIntegral . VU.length \$ xs coeff SpearmanCorrelation = spearman xs coeff PearsonCorrelation = pearson xs s = coeff method * ((sqrt (n - 2)) / (1 - (coeff method ^ 2))) pVal stat = 2 * (complCumulative (studentT (fromIntegral \$ VU.length xs - 2)) . abs \$ stat)