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Of course, your program's commands +might be different; for a GUI interface, you would use an "about box". + + You should also get your employer (if you work as a programmer) or school, +if any, to sign a "copyright disclaimer" for the program, if necessary. +For more information on this, and how to apply and follow the GNU GPL, see +. + + The GNU General Public License does not permit incorporating your program +into proprietary programs. If your program is a subroutine library, you +may consider it more useful to permit linking proprietary applications with +the library. If this is what you want to do, use the GNU Lesser General +Public License instead of this License. But first, please read +. diff --git a/Setup.hs b/Setup.hs new file mode 100644 --- /dev/null +++ b/Setup.hs @@ -0,0 +1,2 @@ +import Distribution.Simple +main = defaultMain diff --git a/app/Main.hs b/app/Main.hs new file mode 100644 --- /dev/null +++ b/app/Main.hs @@ -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 diff --git a/differential.cabal b/differential.cabal new file mode 100644 --- /dev/null +++ b/differential.cabal @@ -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 diff --git a/src/Differential.hs b/src/Differential.hs new file mode 100644 --- /dev/null +++ b/src/Differential.hs @@ -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 diff --git a/src/Load.hs b/src/Load.hs new file mode 100644 --- /dev/null +++ b/src/Load.hs @@ -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 diff --git a/src/Plot.hs b/src/Plot.hs new file mode 100644 --- /dev/null +++ b/src/Plot.hs @@ -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) + |] diff --git a/src/Types.hs b/src/Types.hs new file mode 100644 --- /dev/null +++ b/src/Types.hs @@ -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 } diff --git a/src/Utility.hs b/src/Utility.hs new file mode 100644 --- /dev/null +++ b/src/Utility.hs @@ -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)