differential (empty) → 0.1.1.0
raw patch · 9 files changed
+1313/−0 lines, 9 filesdep +aesondep +basedep +bytestringsetup-changed
Dependencies added: aeson, base, bytestring, cassava, containers, deepseq, differential, foldl, inline-r, lens, lens-aeson, optparse-generic, scientific, sparse-linear-algebra, statistics, text, text-show, vector
Files
- LICENSE +674/−0
- Setup.hs +2/−0
- app/Main.hs +84/−0
- differential.cabal +59/−0
- src/Differential.hs +193/−0
- src/Load.hs +50/−0
- src/Plot.hs +91/−0
- src/Types.hs +76/−0
- src/Utility.hs +84/−0
+ LICENSE view
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+ Setup.hs view
@@ -0,0 +1,2 @@+import Distribution.Simple+main = defaultMain
+ app/Main.hs view
@@ -0,0 +1,84 @@+{- differential+Gregory W. Schwartz++Finds out whether an entity comes from different distributions (statuses).+-}++{-# LANGUAGE BangPatterns #-}+{-# LANGUAGE DataKinds #-}+{-# LANGUAGE DeriveGeneric #-}+{-# LANGUAGE OverloadedStrings #-}+{-# LANGUAGE TypeOperators #-}++module Main where++-- Standard+import Data.List+import Data.Maybe+import Data.Semigroup+import qualified Data.Map as Map+import qualified Data.Set as Set++-- Cabal+import qualified Data.Csv as CSV+import Options.Generic+import TextShow+import qualified Data.ByteString.Char8 as B+import qualified Data.ByteString.Lazy.Char8 as BL+import qualified Data.Text as T+import qualified Data.Vector as V++-- Local+import Types+import Load+import Differential++-- | Command line arguments+data Options = Options { nameCol :: Maybe T.Text+ <?> "([name] | COLUMN) The column containing the names of the entities."+ , statusCol :: Maybe T.Text+ <?> "([status] | COLUMN) The column containing the statuses of the entities."+ , valueCol :: Maybe T.Text+ <?> "([value] | COLUMN) The column containing the values of the entities."+ }+ deriving (Generic)++instance ParseRecord Options++main :: IO ()+main = do+ opts <- getRecord "differential, Gregory W. Schwartz.\+ \ Finds out whether an entity comes from\+ \ different distributions (statuses)."++ contents <- BL.getContents++ let nameCol' = NameCol . fromMaybe "name" . unHelpful . nameCol $ opts+ statusCol' =+ StatusCol . fromMaybe "status" . unHelpful . statusCol $ opts+ valueCol' = ValueCol . fromMaybe "value" . unHelpful . valueCol $ opts+ rows = either error snd+ $ (CSV.decodeByName contents :: Either String (CSV.Header, V.Vector (Map.Map T.Text T.Text)))+ entities = fmap (toEntity nameCol' statusCol' valueCol') rows+ nameMap = getNameMap entities+ outputMaps = getDifferentials nameMap+ comparisons = Set.toList+ . Set.fromList+ . concatMap (Map.keys . unOutputMap . snd)+ $ outputMaps+ outputHeader = V.fromList+ $ [B.pack . T.unpack . unNameCol $ nameCol']+ <> fmap (B.pack . T.unpack) comparisons+ outputBody =+ fmap ( (\ m -> foldl'+ (\acc x -> Map.insertWith (flip const) x "" acc)+ m+ comparisons+ )+ . (\ (!n, !m) -> Map.insert (unNameCol nameCol') (unName n)+ . unOutputMap+ $ m+ )+ )+ $ outputMaps+ BL.putStrLn . CSV.encodeByName outputHeader $ outputBody
+ differential.cabal view
@@ -0,0 +1,59 @@+name: differential+version: 0.1.1.0+synopsis: Finds out whether an entity comes from different distributions (statuses).+description: Uses statistical tests to find whether an entity comes from one or two distributions.+homepage: http://github.com/GregorySchwartz/differential#readme+license: GPL-3+license-file: LICENSE+author: Gregory W. Schwartz+maintainer: gsch@mail.med.upenn.edu+copyright: Copyright: (c) 2018 Gregory W. Schwartz+category: Bioinformatics+build-type: Simple+-- extra-source-files:+cabal-version: >=1.10++library+ hs-source-dirs: src+ exposed-modules: Types+ , Load+ , Differential+ , Plot+ , Utility+ build-depends: base >= 4.7 && < 5+ , aeson+ , bytestring+ , containers+ , deepseq+ , foldl+ , inline-r+ , lens+ , lens-aeson+ , scientific+ , sparse-linear-algebra+ , statistics+ , text+ , text-show+ , vector+ ghc-options: -O2+ default-language: Haskell2010++executable differential+ hs-source-dirs: app+ main-is: Main.hs+ ghc-options: -threaded -rtsopts -O2+ build-depends: base+ , differential+ , bytestring+ , cassava+ , containers+ , inline-r+ , optparse-generic+ , text+ , text-show+ , vector+ default-language: Haskell2010++source-repository head+ type: git+ location: https://github.com/GregorySchwartz/differential
+ src/Differential.hs view
@@ -0,0 +1,193 @@+{- Differential+Gregory W. Schwartz++Collects the functions pertaining to finding the differential between groups for+each entity.+-}++{-# LANGUAGE BangPatterns #-}+{-# LANGUAGE OverloadedStrings #-}+{-# LANGUAGE QuasiQuotes #-}+{-# LANGUAGE TupleSections #-}++module Differential+ ( getDifferentials+ , differentialMatrixObsRow+ , differentialMatrixFeatRow+ , getDifferential+ , edgeR+ ) where++-- Standard+import Control.Monad (guard)+import Data.Int (Int32)+import Data.List+import Data.Semigroup+import TextShow (showt)+import qualified Control.Foldl as Fold+import qualified Control.Lens as L+import qualified Data.Aeson.Lens as L+import qualified Data.Foldable as F+import qualified Data.Map.Strict as Map+import qualified Data.Set as Set+import qualified Data.Scientific as Scientific+import qualified Data.Sequence as Seq+import qualified Data.Sparse.Common as S+import qualified Data.Text as T+import qualified Data.Vector.Unboxed as V+import qualified H.Prelude as H+import qualified Statistics.Test.KruskalWallis as Stat+import qualified Statistics.Types as Stat++-- Cabal++import Language.R as R+import Language.R.Instance as R+import Language.R.Literal as R+import Language.R.QQ++-- Local+import Types+import Utility++-- | Get unique pairings of a list. From+-- http://stackoverflow.com/questions/34044366/how-to-extract-all-unique-pairs-of-a-list-in-haskell+pairs :: [a] -> [(a, a)]+pairs l = [(x,y) | (x:ys) <- tails l, y <- ys]++-- | Find the p-value of two samples.+differential :: [Double] -> [Double] -> R s (Maybe PValue)+differential xs ys = [r| suppressWarnings(wilcox.test(xs_hs, ys_hs))$p.value |]+ >>= (\x -> return . Just . PValue $ ((R.fromSomeSEXP x) :: Double))++-- | Find the p-value of two samples using the Kruskal-Wallis test.+differentialKW :: [Double] -> [Double] -> Maybe PValue+differentialKW xs ys = do+ guard ((> 1) . Set.size . Set.fromList $ xs <> ys) -- Ensure not everything is the same rank+ res <- Stat.kruskalWallisTest [V.fromList xs, V.fromList ys]+ return . PValue . Stat.pValue . Stat.testSignificance $ res++-- | For two lists, xs and ys, find the log2 fold change as mean ys / mean xs.+getLog2Diff :: [Double] -> [Double] -> Log2Diff+getLog2Diff xs ys = Log2Diff . logBase 2 $ getMean ys / getMean xs+ where+ getMean = Fold.fold Fold.mean++-- | Get a comparison using the Kruskal-Wallis test.+getDifferential :: Status+ -> Status+ -> [Double]+ -> [Double]+ -> (Comparison, Log2Diff, Maybe PValue)+getDifferential (Status !s1) (Status !s2) !l1 !l2 = (comp, diff, pVal)+ where+ pVal = differentialKW l1 l2+ diff = getLog2Diff l1 l2+ comp = Comparison (s2 <> "/" <> s1)++-- | Get all comparisons of a Name.+getNameDifferentials :: Map.Map Status (Seq.Seq Double) -> ComparisonMap+getNameDifferentials m = ComparisonMap . Map.fromList . fmap comp $ comparisons+ where+ comparisons = pairs . Map.keys $ m+ comp (!s1, !s2) = (\(x, _, z) -> (x, z))+ $ getDifferential+ s1+ s2+ (F.toList . (Map.!) m $ s1)+ (F.toList . (Map.!) m $ s2)++-- | Convert a ComparisonMap to an OutputMap.+comparisonMapToOutputMap :: ComparisonMap -> OutputMap+comparisonMapToOutputMap = OutputMap+ . Map.map (maybe "NA" (showt . unPValue))+ . Map.mapKeys unComparison+ . unComparisonMap++-- | Get all p-values in all relevant combinations.+getDifferentials :: NameMap -> [(Name, OutputMap)]+getDifferentials (NameMap nameMap) =+ Map.elems+ . Map.mapWithKey (\ !k -> (k,)+ . comparisonMapToOutputMap+ . getNameDifferentials+ )+ $ nameMap++-- | Get differentials between columns (features) of select rows (observations)+-- of bs / as, where as and bs are lists of row indices.+differentialMatrixObsRow :: [Int] -- ^ as+ -> [Int] -- ^ bs+ -> S.SpMatrix Double+ -> [(Log2Diff, Maybe PValue, Maybe FDR)]+differentialMatrixObsRow as bs = differentialMatrixFeatRow as bs . S.transpose++-- | Get differentials between columns (observations) of select rows (features)+-- of bs / as, where as and bs are lists of row indices.+differentialMatrixFeatRow :: [Int] -- ^ as+ -> [Int] -- ^ bs+ -> S.SpMatrix Double+ -> [(Log2Diff, Maybe PValue, Maybe FDR)]+differentialMatrixFeatRow as bs = withFDR . fmap obsToDiff . S.toRowsL+ where+ withFDR xs = zipWith (\(!l, !p) fdr -> (l, p, fdr)) xs+ . getFDR 0.05+ . fmap snd+ $ xs+ obsToDiff vec = (\(_, !l, !p) -> (l, p))+ . getDifferential+ (Status "A")+ (Status "B")+ (obsToVals vec as)+ $ (obsToVals vec bs)+ obsToVals features = fmap (flip S.lookupDenseSV features)++-- | Get edgeR differential expression from a two dimensional matrix.+edgeR :: Int -> TwoDMat -> R s [(Name, Double, PValue, FDR)]+edgeR topN mat = do+ let ss = fmap (T.unpack . unStatus) . _colStatus $ mat+ topN32 = fromIntegral topN :: Int32++ rMat <- fmap unRMat $ twoDMatToRMat mat++ resR <- [r| library(edgeR)++ group = factor(ss_hs)+ y = DGEList(counts = rMat_hs, group = group)+ # Keep genes with at least 1 count per million (cpm) in at least two samples.+ countsPerMillion = cpm(y)+ countCheck = countsPerMillion > 1+ keep = which(rowSums(countCheck) >= 2)+ y = y[keep,]+ # Normalize+ y = calcNormFactors(y)+ design = model.matrix(~ group)+ y = estimateDisp(y, design)+ fit = glmFit(y, design)+ lrt = glmLRT(fit, coef = 2)+ res = topTags(lrt, n = topN32_hs)$table++ # return(jsonlite::toJSON(res))+ return(res)+ |]++ -- let df = R.fromSomeSEXP resR :: String+ -- genes = fmap Name $ df L.^.. L.values . L.key "_row" . L._String+ -- vals = fmap Scientific.toRealFloat+ -- $ df L.^.. L.values . L.key "logFC" . L._Number+ -- pVals = fmap (PValue . Scientific.toRealFloat)+ -- $ df L.^.. L.values . L.key "PValue" . L._Number+ -- fdrs = fmap (FDR . Scientific.toRealFloat)+ -- $ df L.^.. L.values . L.key "FDR" . L._Number++ genesR <- [r| row.names(resR_hs) |]+ valsR <- [r| resR_hs$logFC |]+ pValsR <- [r| resR_hs$PValue |]+ fdrsR <- [r| resR_hs$FDR |]++ let genes = fmap (Name . T.pack) (R.dynSEXP genesR :: [String])+ vals = R.dynSEXP valsR :: [Double]+ pVals = fmap PValue (R.dynSEXP pValsR :: [Double])+ fdrs = fmap FDR (R.dynSEXP fdrsR :: [Double])++ return . zip4 genes vals pVals $ fdrs
+ src/Load.hs view
@@ -0,0 +1,50 @@+{- Load+Gregory W. Schwartz++Collects the functions pertaining to loading the input data.+-}++{-# LANGUAGE BangPatterns #-}+{-# LANGUAGE QuasiQuotes #-}++module Load+ ( toEntity+ , getNameMap+ ) where++-- Standard+import Data.Semigroup+import qualified Data.Map.Strict as Map++-- Cabal+import qualified Data.Sequence as Seq+import qualified Data.Text as T+import qualified Data.Text.Read as T+import qualified Data.Vector as V+import qualified Data.Vector.Unboxed as VU++-- Local+import Types++-- | Convert a row to an Entity.+toEntity :: NameCol -> StatusCol -> ValueCol -> Map.Map T.Text T.Text -> Entity+toEntity (NameCol nameCol) (StatusCol statusCol) (ValueCol valueCol) m =+ Entity { _name = Name . lookupWithErr nameCol $ m+ , _status = Status . lookupWithErr statusCol $ m+ , _value = either error fst . T.double . lookupWithErr valueCol $ m+ }+ where+ lookupWithErr k =+ Map.findWithDefault (error $ "Cannot find column: " <> show k) k++-- | Gather Entity's, where each entity sharing a name is from a different+-- Status.+getNameMap :: V.Vector Entity -> NameMap+getNameMap =+ NameMap+ . Map.fromListWith (Map.unionWith (Seq.><))+ . fmap (\ !x -> ( _name x+ , Map.singleton (_status x) (Seq.singleton . _value $ x)+ )+ )+ . V.toList
+ src/Plot.hs view
@@ -0,0 +1,91 @@+{- Plot+Gregory W. Schwartz++Collects the functions pertaining to plotting the differential between groups for+each entity.+-}++{-# LANGUAGE OverloadedStrings #-}+{-# LANGUAGE QuasiQuotes #-}++module Plot+ ( plotDiff+ , plotSingleDiff+ ) where++-- Standard++-- Cabal+import qualified Data.Aeson as A+import qualified Data.ByteString.Lazy.Char8 as B++import Language.R.QQ (r)+import qualified Foreign.R.Internal as R+import qualified Language.R.Instance as R+import qualified Language.R.Literal as R++-- Local+import Types++-- | Plot the input values as a scatterplot with designated cutoffs for the fold+-- change (>=) and p-value (<) respectively.+plotDiff :: Double -> PValue -> [Double] -> [PValue] -> R.R s (R.SomeSEXP s)+plotDiff valCut pCut vals ps = do+ let pCutR = unPValue pCut+ psR = fmap unPValue ps++ [r| suppressMessages(library(ggplot2))+ suppressMessages(library(cowplot))++ df = data.frame( x = vals_hs+ , y = psR_hs+ , significant = as.character(((vals_hs >= valCut_hs) & (psR_hs < pCutR_hs)))+ )++ p = ggplot(df, aes(x = x, y = y)) ++ geom_point(aes(color = significant)) ++ scale_color_manual(values = c("FALSE" = "gray", "TRUE" = "red"))++ return(p)+ |]++-- | Plot the difference between groups for all features. Here, Name refers+-- to the feature while Status refers to the differential group. Choose whether+-- to normalize by the maximum value for a name.+plotSingleDiff :: Bool -> [Entity] -> R.R s (R.SomeSEXP s)+plotSingleDiff normalizeBool vals = do+ let jsonR = B.unpack $ A.encode vals+ normalize = if normalizeBool then 1 else 0 :: Double++ [r| suppressMessages(library(ggplot2))+ suppressMessages(library(plyr))+ suppressMessages(library(cowplot))+ suppressMessages(library(jsonlite))+ suppressMessages(library(RColorBrewer))++ df = fromJSON(jsonR_hs)++ if(normalize_hs) {+ df = ddply(df, "name", transform, value = value / max(value))+ }++ p = ggplot(df, aes(x = name, y = value, fill = status)) ++ geom_violin(alpha = 0.5, draw_quantiles = c(0.25, 0.5, 0.75), scale = "width") ++ scale_fill_brewer(palette = "Set1") ++ xlab("Feature") ++ theme_classic() ++ theme( axis.text = element_text(color = "black")+ , panel.grid.major.y = element_blank()+ , axis.ticks.x = element_blank()+ , axis.ticks.y = element_line(color = "black")+ , axis.text.x = element_text(angle=315, hjust=0)+ )++ if(normalize_hs) {+ p = p + ylab("Normalized abundance")+ } else {+ p = p + ylab("Abundance")+ }++ return(p)+ |]
+ src/Types.hs view
@@ -0,0 +1,76 @@+{- Types+Gregory W. Schwartz++Collects the types used in the program+-}++{-# LANGUAGE StrictData #-}+{-# LANGUAGE DeriveGeneric #-}+{-# LANGUAGE GeneralizedNewtypeDeriving #-}++module Types where++-- Remote+import Control.DeepSeq (NFData (..))+import Foreign.R.Internal as R+import Language.R.Instance as R+import Language.R.Literal as R+import Language.R.QQ+import GHC.Generics+import qualified Data.Aeson as A+import qualified Data.Map.Strict as Map+import qualified Data.Sequence as Seq+import qualified Data.Text as T++-- Local+++-- Basic+newtype NameCol = NameCol+ { unNameCol :: T.Text+ } deriving (Eq,Ord,Read,Show)+newtype StatusCol = StatusCol T.Text+newtype ValueCol = ValueCol T.Text+newtype PValue = PValue+ { unPValue :: Double+ } deriving (Eq,Ord,Read,Show,Generic)+newtype Log2Diff = Log2Diff+ { unLog2Diff :: Double+ } deriving (Eq,Ord,Read,Show,Generic)+newtype FDR = FDR+ { unFDR :: Double+ } deriving (Eq,Ord,Read,Show,Generic)+newtype Name = Name { unName :: T.Text } deriving (Eq, Ord, Read, Show, A.ToJSON,Generic)+newtype Status = Status+ { unStatus :: T.Text+ } deriving (Eq,Ord,Read,Show, A.ToJSON)+newtype Comparison = Comparison { unComparison :: T.Text } deriving (Eq, Ord)+newtype NameMap = NameMap (Map.Map Name (Map.Map Status (Seq.Seq Double)))+newtype RMat s = RMat { unRMat :: R.SomeSEXP s }++instance NFData Log2Diff+instance NFData PValue+instance NFData FDR+instance NFData Name++-- Advanced+data Entity = Entity { _name :: Name+ , _status :: Status+ , _value :: Double+ }+ deriving (Read, Show, Generic)++instance A.ToJSON Entity where+ toJSON = A.genericToJSON A.defaultOptions{ A.fieldLabelModifier = drop 1 }++data TwoDMat = TwoDMat { _rowNames :: [Name]+ , _colNames :: [Name]+ , _colStatus :: [Status]+ , _numRows :: Int+ , _numCols :: Int+ , _matrix :: [(Int, Int, Double)]+ }+++newtype ComparisonMap = ComparisonMap { unComparisonMap :: Map.Map Comparison (Maybe PValue) }+newtype OutputMap = OutputMap { unOutputMap :: Map.Map T.Text T.Text }
+ src/Utility.hs view
@@ -0,0 +1,84 @@+{- Utility+Gregory W. Schwartz++Collects the miscellaneous functions of the program.+-}++{-# LANGUAGE QuasiQuotes #-}+{-# LANGUAGE BangPatterns #-}++module Utility+ ( twoDMatToRMat+ , getFDR+ ) where++-- Standard++-- Cabal++import Data.Function (on)+import Data.List (sortBy, genericLength)+import Data.Maybe (catMaybes)+import Data.Int (Int32)+import Language.R.Instance as R+import Language.R.Literal as R+import Language.R.QQ+import qualified Control.Lens as L+import qualified Data.Text as T++-- Local+import Types++-- | Convert the two dimensional matrix to an R sparse matrix. Assumes 0 indexed+-- to 1 indexed.+twoDMatToRMat :: TwoDMat -> R s (RMat s)+twoDMatToRMat mat = do+ let (is, js, vs) =+ unzip3+ . fmap ( L.over L._2 ((+ 1) . toInt32)+ . L.over L._1 ((+ 1) . toInt32)+ )+ . _matrix+ $ mat+ rNames = fmap (T.unpack . unName) . _rowNames $ mat+ cNames = fmap (T.unpack . unName) . _colNames $ mat+ nRows = toInt32 . _numRows $ mat+ nCols = toInt32 . _numCols $ mat++ rMat <- [r| library(Matrix)++ mat = sparseMatrix( i = is_hs+ , j = js_hs+ , x = vs_hs+ , dims = c(nRows_hs, nCols_hs)+ )+ rownames(mat) = rNames_hs+ colnames(mat) = cNames_hs++ return(mat)+ |]++ return . RMat $ rMat++-- | Convert an Int to and Int32.+toInt32 :: Int -> Int32+toInt32 x = fromIntegral x :: Int32++-- | Convert p-values to FDR using the Benjamini-Hochberg procedure.+getFDR :: Double -> [Maybe PValue] -> [Maybe FDR]+getFDR alpha xs =+ fmap snd+ . sortBy (compare `on` fst)+ . fmap (\(!r, (!o, !p)) -> (o, getFDR r p))+ . drop 1 -- Get rid of starting value+ . scanl scanFunc (0, (-1, Nothing))+ . sortBy (compare `on` snd)+ . zip ([1..] :: [Int])+ $ xs+ where+ m = genericLength . catMaybes $ xs+ scanFunc (!r, (_, !prev)) x@(_, Nothing) = (r, x)+ scanFunc (!r, (_, !prev)) !x =+ if snd x == prev then (r, x) else (r + 1, x) -- Handle ties+ getFDR _ Nothing = Nothing+ getFDR rank (Just _) = Just . FDR $ alpha * (rank / m)