diff --git a/Setup.hs b/Setup.hs new file mode 100644 --- /dev/null +++ b/Setup.hs @@ -0,0 +1,3 @@ +#!/usr/bin/env runhaskell +import Distribution.Simple +main = defaultMain diff --git a/flowsim.cabal b/flowsim.cabal new file mode 100644 --- /dev/null +++ b/flowsim.cabal @@ -0,0 +1,35 @@ +Name: flowsim +Version: 0.2.6 +License: GPL + +Author: Ketil Malde +Maintainer: Ketil Malde + +Category: Bioinformatics +Synopsis: Simulate 454 pyrosequencing +Description: pyrosim - a simulator for 454 pyrosequencing data + Simulate shotgun sequencing with Roche's 454 sequencing technology. + . + The Darcs repository is at . + +HomePage: http://bhlog.malde.org/ +Build-Depends: bio >= 0.4.4, base >= 4 && <= 5, array >= 0.1, bytestring >= 0.9.1, random, MonadRandom, cmdargs, containers, directory +Build-Type: Simple +Tested-with: GHC==6.8.2 + + -- Data-files: README +Executable: flowsim +Main-Is: FlowSim.hs +Other-Modules: Statistics, Config, EmpFile + Generations.GenBase, Generations.GS20, + Generations.Titanium, Generations.Empirical +Hs-Source-Dirs: src + +Executable: hplc +Main-Is: HPLCount.hs +Ghc-Options: -main-is HPLCount +Hs-Source-Dirs: src + +Executable: clonesim +Main-Is: CloneSim.hs +Hs-Source-Dirs: src diff --git a/src/CloneSim.hs b/src/CloneSim.hs new file mode 100644 --- /dev/null +++ b/src/CloneSim.hs @@ -0,0 +1,82 @@ +{- | CloneSim - fragment a genome sequence to simulate cloning + Factored out from flowsim in order to separate clone generation + from flow simulation and base calling. +-} + +{-# Language DeriveDataTypeable #-} + +module Main where + +import Bio.Sequence hiding ((!)) +import Statistics + +import System.IO (stdin,stdout,stderr,hPutStrLn) +import Control.Monad (forM) +import qualified Data.ByteString.Lazy as B +import Data.Int (Int64) +import System.Console.CmdArgs +import Data.Array + +type Dist = String +data Conf = Conf + { lengths :: Dist + , count :: Int + , input :: [FilePath] + } deriving (Data,Typeable,Show) + +modes :: Mode Conf +modes = mode $ Conf { + lengths = "Uniform 400 800" &= text "model for clone lengths" & typ "DIST" + , count = 10 &= text "number of reads to generate" & typ "INT" + , input = def &= args & typFile + } &= prog "clonesim" + & text "simulate sequence cloning" + & helpSuffix ["Available distributions (DIST):" + ," Uniform a b, Normal mu sigma, LogNormal mu sigma"] + +version :: String +version = "clonesim v0.2.6, copyright 2010 Ketil Malde" + +data Dir = Fwd | Rev deriving (Eq,Enum,Bounded) + +instance Random Dir where + random g = let (b,g') = random g in (if b then Fwd else Rev,g') + randomR = error "randomR is undefined for Dir" + +main :: IO () +main = do + conf <- cmdArgs version [modes] + -- print conf + let inf = case input conf of + [] -> hPutStrLn stderr "clonesim: reading from stdin" >> hReadFasta stdin + [x] -> readFasta x + _ -> error "Please specify only a single input file" + ss <- map (defragSeq . castToNuc) `fmap` inf + let sa = listArray (0,length ss-1) ss + hWriteFasta stdout =<< evalRandIO (simulate conf sa) + +type SeqArray = Array Int (Sequence Nuc) + +-- | the real 'main' +simulate :: RandomGen g => Conf -> SeqArray -> Rand g [Sequence Nuc] +simulate conf sa = do + let ldist = read $ lengths conf + (_,asz) = bounds sa + forM [1..count conf] $ const + (do i <- floor `fmap` sample (Uniform 0 $ 1+fromIntegral asz) -- inclusive? + let s = sa!i + p <- round `fmap` sample (Uniform 0 $ fromIntegral (seqlength s-1)) + l <- round `fmap` sample ldist + dir <- getRandom + return (mkClone dir p l s)) + +mkClone :: Dir -> Int64 -> Int64 -> Sequence Nuc -> Sequence Nuc +mkClone dir pos len (Seq h s mq) = + Seq (fromStr (toStr h++" "++show pos++case dir of Fwd -> "+"; Rev -> "-")) + sd + qual + where sd = B.take len + . (case dir of Fwd -> snd; Rev -> revcompl' . fst) + . B.splitAt pos $ s + qual = B.take len `fmap` case dir of Fwd -> fst; Rev -> snd + `fmap` B.splitAt pos `fmap` mq diff --git a/src/Config.hs b/src/Config.hs new file mode 100644 --- /dev/null +++ b/src/Config.hs @@ -0,0 +1,147 @@ +{-| Module Config - replaces Options, use CmdArgs instead -} +{-# LANGUAGE DeriveDataTypeable #-} + +module Config (Config(..), mkconf + ,inform, whenLoud, whenNotQuiet) where + +import Data.Char (toLower) +import Data.List (isPrefixOf, intersperse) +import System.Console.CmdArgs +import System.Directory (doesFileExist) +import Control.Monad (when) +import System.IO (hPutStrLn, stderr, stdin) +import EmpFile + +import Bio.Sequence + +import Generations.GenBase +import Generations.GS20 +import Generations.Titanium +import Generations.Empirical + +version :: String +version = "flowsim v0.2.6, copyright 2010 Ketil Malde" + +-- data GenName = Titanium | FLX | GS20 deriving (Typeable, Data, Show, Eq) +type GenName = String +type Dist = String + +data Config = Conf { generation :: GenName + , degradation:: Dist + , model :: FilePath + , qualmethod :: GenName + , discardfilters :: [String] + , trimfilters :: [String] + , flowkey :: String + , hplinput :: FilePath + , flowlength :: Int + , flowcycle :: String + , inputs :: [FilePath] + , output :: FilePath + } deriving (Typeable, Data, Show, Read) + +modes :: Mode Config +modes = mode $ Conf + { generation = "Titanium" &= text "454 generation to simulate" & typ "GEN" & flag "G" + , degradation = def &= text "model for degradation of the flow model" & typ "DIST" + , model = def &= text "empirical distribution for flow generation" & typFile + , qualmethod = def &= text "method for calculating quality" & typ "STRING" + , discardfilters = def &= text "discarding filters to apply" & typ "DFILT" + , trimfilters = def &= text "trimming filters to apply" & typ "TFILT" + , flowkey = def &= text "sequence key to start each read (TCAG)" + , hplinput = def &= text "input genome for HPL count estimate" & typFile + , flowlength = def &= text "number of flow cycles to run" + , flowcycle = def &= text "sequence nucleotides in each flow cycle (TACG)" + , inputs = def &= args & typFile + , output = def &= text "output file" + } &= prog "flowsim" + & text "simulate 454 pyrosequencing." + & helpSuffix hs + where + hs = ["Generations (GEN): "++concat (intersperse ", " $ map fst generations) + , "Distributions (DIST): Uniform a b, Normal mu sigma, LogNormal mu sigma" + , "Discarding filters (DFILT): ...." + , "Trimming filters (TFILT): ...."] + +mkconf :: IO (Generation,IO [Sequence Nuc],HPLprob,FilePath) +mkconf = do + cf <- cmdArgs version [modes] + let inp = map castToNuc `fmap` if null (inputs cf) then hReadFasta stdin else concat `fmap` mapM readFasta (inputs cf) + gen <- mkgen cf + whenLoud $ inform ("Generation: "++generation cf ++ "\n" ++ show gen) + when (null $ output cf) $ error "Please specify an output file with -o" + hplc <- case hplinput cf of + [] -> return default_hplc + file -> (mkHPLprobs . freqtable . concatMap (hpls (f_cycle gen) . seqdata)) `fmap` readFasta file + return (gen, inp, hplc, output cf) + +default_hplc :: HPLprob +default_hplc _ l = 3/4**fromIntegral l + +generations :: [(GenName,Generation)] +generations = [("GS20", gs20), ("Titanium",titanium),("EmpTitanium",tiEmp)] + +lookupGen :: String -> Generation +lookupGen g = case map snd . filter (isPrefixOf (map toLower g) . map toLower . fst) $ generations of + [x] -> x + _ -> error ("Generation '"++g++"' is non-existing or ambigous\nAvailable generations are: "++show (map fst generations)) + +-- if non-null, pick field f from generation str, else pick it from the default +setFromGen :: Generation -> (Generation -> field) -> String -> field +setFromGen dflt f str = if null str then f dflt else f (lookupGen str) + +-- similar, but use Read to parse the string +setFromStr :: (Read a) => Generation -> (Generation -> a) -> String -> a +setFromStr dflt f str = if null str then f dflt else read str + +mkgen :: Config -> IO Generation +mkgen (Conf g deg fm qm df tf fk hpl fl fc _inputs _output) = do + let gen = lookupGen g + setG = setFromGen gen + setD = setFromStr gen + setF fs | null fs = disc_filters gen + | otherwise = concatMap (maybe [] id) $ map (flip lookup filterlist) fs + setT fs | null fs = trim_filters gen + | otherwise = concatMap (maybe [] id) $ map (flip lookup trimlist) fs + my_qcall = if null qm then qcall gen + else case qm of + "gs20tab" -> qual_gs20_tab + "dexact" -> qual_exact_decreasing + "fexact" -> qual_exact_fixed + _ -> error ("No such quality call method:"++show qm + ++"\nAvailable methods: gs20tab, dexact, fexact.") + my_model <- if null fm then return (models gen) + else do + f <- doesFileExist fm + ms <- if f then readPdf fm else return (parse_models fm) + return $ combine_models (models gen) ms + return $ gen + { qcall = my_qcall + , degrade = setD degrade deg + , models = my_model + , disc_filters = setF df + , trim_filters = setT tf + , f_key = setG f_key fk + , f_len = if fl > 0 then fl else f_len gen + , f_cycle = setG f_cycle fc + } + +parse_models :: String -> [Distribution] +parse_models str = read ("["++str++"]") + +-- filterlist :: [DiscardFilter] +filterlist = [] -- todo: export from SFF_filters + +-- trimlist :: [Trimfilter] +trimlist = [] + +-- Logging +inform :: String -> IO () +inform = hPutStrLn stderr + +whenLoud, whenNotQuiet :: IO () -> IO () +whenLoud action = flip when action =<< isLoud +-- note that isQuiet = return False in CmdArgs! +whenNotQuiet action = do n <- isNormal + l <- isLoud + when (n || l) action diff --git a/src/EmpFile.hs b/src/EmpFile.hs new file mode 100644 --- /dev/null +++ b/src/EmpFile.hs @@ -0,0 +1,25 @@ +module EmpFile where + +import Statistics +import Control.Monad (when) + +readPdf :: FilePath -> IO [Distribution] +readPdf f = do + cs <- lines `fmap` readFile f + return (parsePdf ("file '"++f++"'") cs) + +parsePdf :: String -> [String] -> [Distribution] +parsePdf f cs = + let (_:fs:vss) = transpose (map words cs) + in if (or $ zipWith (/=) [0..] (map read fs)) + then error ("Flow index from "++f++" isn't [0..]!") + else map (fromPdf 0 0.01 . map (P . read)) vss + +transpose xs = let r0 = map head xs + rest = map tail xs + in if any null rest then [r0] else r0 : transpose rest + +-- currently this only works for a single model +combine_models :: [Int -> Distribution] -> [Distribution] -> [Int -> Distribution] +combine_models [f] ds = [\i -> if i < length ds then ds!!i else f i] +combine_models _ _ = error "Can't combine multiple models" diff --git a/src/FlowSim.hs b/src/FlowSim.hs new file mode 100644 --- /dev/null +++ b/src/FlowSim.hs @@ -0,0 +1,186 @@ +{- | FlowSim - simulate 454 flowgrams from a reference genome + + Flow values are modelled from a log-normal noise, and a sequence of + normal distributions, one for each homopolymer length. These distributions + can be estimated from real data. + + Todo: + * Paired ends models B-linker-A + * Support multiple sequences: + - scan seqs + lenghts + - gen n numbers (0..total length), transform to deltas (cf. rselect) + - sort and generate + +-} +{-# options -XParallelListComp #-} + +module Main where + +import Bio.Sequence +import Bio.Sequence.SFF + +import qualified Data.ByteString.Lazy.Char8 as B +import qualified Data.ByteString.Lazy as BL +import qualified Data.ByteString.Char8 as BS +import qualified Data.ByteString as BS2 + +import Data.Char (toUpper) +import Data.Int + +import Statistics +import Generations.GenBase +import Config + +import Control.Monad (when) + +-- ------------------------------------------------------------ +-- picking random postions/directions for reads + +data Dir = Fwd | Rev deriving (Eq,Enum,Bounded) + +instance Random Dir where + random g = let (b,g') = random g in (if b then Fwd else Rev,g') + randomR = error "randomR is undefined for Dir" + +main :: IO () +main = do + (gen,is,hplc,o) <- mkconf + + ss <- is + case ss of [] -> error ("Input appears to be empty?") + _ -> return () + sff <- evalRandIO $ sim454 gen hplc ss + n <- writeSFF' o sff + whenLoud $ inform ("Wrote "++show n++" reads to '"++o++"'.") + +-- testing +test_s :: Sequence Nuc +test_s = Seq (fromStr "foo") (fromStr "aacacattcgtggtnagctacggaacacattcgtggtnagctacggaacacattcgtggtnagctacggaacacattcgtggtnagctacgg") Nothing + +-- | Heavy lifting. Building an SFF file from the specified information +sim454 :: RandomGen g => Generation -> HPLprob -> [Sequence Nuc] -> Rand g SFF +sim454 gen hplc ss = do + let ch = makeCommonHeader gen + tf r = foldr ($) r $ trim_filters gen + df r = and $ zipWith ($) (disc_filters gen) (repeat r) + rbs <- map tf `fmap` filter df `fmap` mapM (\s -> makeReadBlock gen hplc s ch) ss + return (SFF ch rbs) + +-- Generate a sequence of models +-- The generation specifies a series of initial models, this function +-- uses these with the degradation to generate a progression of models to use +makeModels :: RandomGen g => Generation -> Rand g [Model] +makeModels gen = case models gen of + [m] -> iterativeWorsen (f_len gen) (degrade gen) m + im@(_:_) -> do + let ns = f_len gen `div` length im + return $ concat $ map (replicate ns) im + +iterativeWorsen :: RandomGen g => Int -> Distribution -> Model -> Rand g [Model] +iterativeWorsen 0 _ _ = return [] +iterativeWorsen count deg m = do + ps <- perturbs 1 count + return $ zipWith (fmap . worsen) ps $ replicate count m + where perturbs _ 0 = return [] + perturbs cur n = do + w <- sample deg + let new = cur+w + rest <- perturbs new (n-1) + return (new : rest) + +-- -------------------------------------------------- +-- Generate the flow values + +-- generate the "absolute" flow values from the cycle and the origin sequence data +makeFlows :: [Char] -> SeqData -> [(Char,Int)] +makeFlows c s | B.null s = [] + | otherwise = let (c1,s1) = makeCycle [] (take 4 c) s + s2 = case B.uncons s1 of Just (x,_) -> if not (toUpper x `elem` "ACGT") then B.tail s1 else s1; _ -> s1 + in c1 ++ makeFlows c s2 + +makeCycle :: [(Char,Int)] -> [Char] -> SeqData -> ([(Char,Int)],SeqData) +makeCycle acc [] s = (reverse acc, s) +makeCycle acc (c:cs) s = let (this,rest) = B.span ((==toUpper c).toUpper) s + in makeCycle ((c,fromIntegral $ B.length this):acc) cs rest + +-- | Takes a sequence of flows with exact homopolymer lengths, +-- permutes and calls them. Next step is prepareData +permuteAndCall :: RandomGen g => Generation -> HPLprob -> [(Char,Int)] -> + Rand g [(Flow,[Char],[Qual])] +permuteAndCall gen hplc fs = do + -- when (trace (show fs) False) (return ()) + let n = fromIntegral $ f_len gen + flow_cont = drop (length fs `mod` length (f_cycle gen)) $ cycle (f_cycle gen) + xs = fs ++ zip flow_cont (replicate (n-length fs) 0) + ms <- makeModels gen + -- if and $ zipWith (==) (map fst xs) (cycle $ f_cycle gen) then return () + -- else error (map fst xs ++ "\n don't cycle: "++f_cycle gen) + sequence $ take n $ zipWith (my_call (qcall gen) hplc) ms xs + +-- Titanium base/quality calling +my_call :: RandomGen g => QualMethod -> HPLprob -> Model -> (Char,Int) -> + Rand g (Flow,[Char],[Qual]) +my_call qm ft md (c,hpl) = do + f <- sample (md hpl) + let fi = max 0 . round . (100*) $ f + n = fromIntegral ((fi+50) `div` 100) + cs = replicate n c + qs = qm ft md (c,fi) + when (length qs /= n) $ error ("Qual mismatch: "++show (f,fi,n,cs,qs)) + return (fi, cs, qs) + +-- | Somewhat advanced unzip, calculating the index in the process. +-- Also replace three consequtive empty lists with Ns +convertCalls :: [(Flow,[Char],[Qual])] -> ([Flow],[Char],[Qual],[Int]) +convertCalls = go 0 . addDots + where go _ [] = ([],[],[],[]) + go p ((f,cs,qs):fs) + | null cs = let (f',c',q',i') = go (p+1) fs + in (f:f',c',q',i') + | otherwise = let (f',c',q',i') = go 0 fs + in (f:f',cs++c',qs++q',(p+1):replicate (length cs-1) 0 ++ i') + + addDots ((f1,cs1,qs1):(f2,cs2,qs2):(f3,cs3,qs3):(f4,cs4,qs4):rest) + | null cs1 && null cs2 && null cs3 && not (null cs4) = (f1,cs1,qs1):(f2,cs2,qs2):(f3,"N",[0]):addDots ((f4,cs4,qs4):rest) + | otherwise = (f1,cs1,qs1) : addDots ((f2,cs2,qs2):(f3,cs3,qs3):(f4,cs4,qs4):rest) + addDots fewerThanThree = fewerThanThree + +-- | Generate a ReadBlock +-- direction and position chosen at random, and encoded in the read name +makeReadBlock :: RandomGen g => Generation -> HPLprob -> Sequence Nuc -> CommonHeader -> Rand g ReadBlock +makeReadBlock g hplc sq ch = do + let sdata = seqdata sq + rn = BS.concat $ BL.toChunks $ seqlabel sq + fs = makeFlows (BS.unpack $ flow ch) $ BL.concat [BL.fromChunks [key ch], {- B.take (floor cl) $ -} sdata] + (pfs,cs,qs,is) <- convertCalls `fmap` permuteAndCall g hplc fs + return $ verifyRB (flow_length ch) $ ReadBlock { + read_header = ReadHeader { + name_length = fromIntegral $ BS.length rn -- :: Int16 + , num_bases = fromIntegral $ length cs -- :: Int32 + , clip_qual_left = 5 -- :: Int16 + , clip_qual_right = fromIntegral $ length cs -- :: Int16 + , clip_adapter_left = 0 -- :: Int16 + , clip_adapter_right = 0 -- :: Int16 + , read_name = rn -- :: ByteString + } + -- The data block + , flow_data = packFlows pfs -- :: [Flow] + , flow_index = BS2.pack $ map fromIntegral is -- :: ByteString + , bases = fromStr cs -- :: SeqData + , quality = BL.pack qs -- :: QualData + } + +-- | Consistency check on generated ReadBlocks. +verifyRB :: Int16 -> ReadBlock -> ReadBlock +verifyRB fl rb + | name_length rh == 0 = err "name_length is zero" + | num_bases rh == 0 = err "num_bases is zero" +-- | clip_qual_left rh > clip_qual_right rh = err "clipping gives negative sequence" + | BS2.length (read_name rh) /= (fromIntegral $ name_length rh) = err "read_name has incorrect length" + | BS.length (flow_data rb) `div` 2 /= fromIntegral fl = err ("Number of flows ("++show (BS.length (flow_data rb) `div` 2)++")do not match flow_length of "++show fl++" in CommonHeader") + | BS.length (flow_data rb) `div` 2 < (fromIntegral $ sum $ BS2.unpack $ flow_index rb) = err "flow_index longer than flows" + | B.length (bases rb) /= (fromIntegral $ BS.length $ flow_index rb) = err ("bases ("++show (B.length (bases rb))++") and flow_index ("++show (BS.length $ flow_index rb)++") have different lengths") + | B.length (quality rb) /= (fromIntegral $ BS.length $ flow_index rb) = err ("quality ("++show (B.length (quality rb))++") and flow_index ("++show (BS.length $ flow_index rb)++") have different lengths") + | otherwise = rb + where rh = read_header rb + err str = error (str ++ "\n" ++ show rb) diff --git a/src/Generations/Empirical.hs b/src/Generations/Empirical.hs new file mode 100644 # file too large to diff: src/Generations/Empirical.hs diff --git a/src/Generations/GS20.hs b/src/Generations/GS20.hs new file mode 100644 --- /dev/null +++ b/src/Generations/GS20.hs @@ -0,0 +1,157 @@ +module Generations.GS20 where + +import Generations.GenBase + +import Data.Array +import qualified Data.ByteString.Char8 as BC +import qualified Data.ByteString as B +import Control.Monad (when) + +type QualTable = Array Flow B.ByteString + +-- | Wrapper around 'array' that interpolates missing values +-- Todo: make this more sophisticated! +mkQualTable :: (Flow,Flow) -> [(Flow,B.ByteString)] -> QualTable +mkQualTable is = array is . map extend . interpolate + +interpolate :: [(Flow,B.ByteString)] -> [(Flow,B.ByteString)] +interpolate ((x1,y1):(x2,y2):rest) + = [(x,y1) | x <- [x1..x2-1]]++interpolate ((x2,y2):rest) +interpolate xs = xs + +extend :: (Flow,B.ByteString)-> (Flow,B.ByteString) +extend (x,y) = let delta = ((x+50) `div` 100) - fromIntegral (B.length y) + in (x,B.concat [y,B.replicate (fromIntegral delta) 1]) + +gs20 :: Generation +gs20 = Gen { + name = "GS20" + , models = [\h -> let h' = fromIntegral h + in if h == 0 then LogNormal (negate 2.5) 0.2 else Normal h' (0.04+0.06*h')] + , qcall = qual_gs20_tab + , degrade = Normal 0.005 0.002 + , disc_filters = [filter_key,filter_empty] + , trim_filters = [] + + , f_key = "TCAG" + , f_len = 168 -- :: Int16 + , f_cycle = "TACG" + } + + +qual_gs20_tab :: QualMethod +qual_gs20_tab _ _ (_,fi) = B.unpack (gs20qt!fi) + +gs20qt :: QualTable +gs20qt = mkQualTable (0,3100) $ map (\(x,y) -> (x,BC.pack y)) [ + 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its own distribution of flow values + +type QualMethod = HPLprob -> Model -> (Char,Flow) -> [Qual] + +data Generation = Gen { + name :: String + , qcall :: QualMethod -- ^ use the current model and hpl lenght to generate qual data + , models :: [Model] -- ^ a progression of initial models for the sequence of flows + , degrade :: Distribution -- the amount to increase a stdev multiplier each position + , disc_filters :: [DiscardFilter] + , trim_filters :: [TrimFilter] + -- stuff to build the commonheader from + , f_key :: String + , f_len :: Int + , f_cycle :: String + -- readblock :: [ReadBlock] ? + } + +instance Show Generation where + show g = "Config:\n" ++ unlines (map (" "++) + ["key: "++f_key g + ,"flowlength: "++show (f_len g), "flow cycle: "++show (f_cycle g) + ]) +-- ,"flow distributions:"]) +-- ++ unlines [" "++show i++": "++show (model g i) | i <- [0..6]] + +-- | Calculate exact qualities from model using Bayes' theorem +-- This should emulate Marguiles et al.'s method. +qual_exact_decreasing :: HPLprob -> Model -> (Char,Flow) -> [Qual] +qual_exact_decreasing ft m (c,flow) = + let f = fromIntegral flow / 100 + prob hpl | hpl > 20 = error "can't handle hpls > 20" + | otherwise = ft c hpl * pdf (m hpl) f / sum [pdf (m x) f * ft c x | x <- [0..20]] + probs = drop 1 $ scanl (+) 0 $ map prob [0..20] + quals = map (round . max 0 . min 60 . ((-10)*) . logBase 10) $ probs + in -- trace ("#"++show (c,flow) ++"\n"++show probs ++"\n"++show quals) $ + take (fromIntegral $ (flow+50) `div` 100) $ quals + +-- | Using Bayes, but only calculating the probablity of the call lenght +-- being correct. Should be similar to Titanium (but is it?) +qual_exact_fixed :: HPLprob -> Model -> (Char,Flow) -> [Qual] +qual_exact_fixed ft m (c,flow) = + let f = fromIntegral flow / 100 + hpl = fromIntegral $ (flow+50) `div` 100 + prob = ft c hpl * pdf (m hpl) f / sum [pdf (m x) f * ft c x | x <- [0..20]] + in replicate hpl (round $ max 0 . min 60 $ (-10) * logBase 10 (1-prob)) + +-- -------------------------------------------------- +-- Putting it together +makeCommonHeader :: Generation -> CommonHeader +makeCommonHeader g = CommonHeader + { index_offset = 0 + , index_length = 0 + , key_length = fromIntegral $ length $ f_key g + , flowgram_fmt = 1 + , key = BC.pack $ f_key g + + , num_reads = 0 -- fromIntegral $ n_reads g + , flow_length = fromIntegral $ f_len g + , flow = BC.pack $ concat $ replicate (f_len g `div` (length $ f_cycle g)) $ f_cycle g + } diff --git a/src/Generations/Titanium.hs b/src/Generations/Titanium.hs new file mode 100644 --- /dev/null +++ b/src/Generations/Titanium.hs @@ -0,0 +1,16 @@ +module Generations.Titanium where +import Generations.GenBase + +titanium :: Generation +titanium = Gen + { name = "Titanium" + , qcall = qual_exact_fixed + , models = [\h -> let h' = fromIntegral h + in if h == 0 then LogNormal (negate 2.5) 0.2 else Normal h' (0.04+0.05*h')] + , degrade = Normal 0.001 0.001 + , disc_filters = [filter_key,filter_empty] + , trim_filters = [] + , f_key = "TCAG" + , f_len = 800 -- :: Int16 + , f_cycle = "TACG" + } diff --git a/src/HPLCount.hs b/src/HPLCount.hs new file mode 100644 --- /dev/null +++ b/src/HPLCount.hs @@ -0,0 +1,44 @@ +-- count homopolymer distributions in a fasta file +module HPLCount where + +import Bio.Sequence +import qualified Data.ByteString.Lazy.Char8 as B +import qualified Data.Map as M +import Text.Printf +import Data.Char (toUpper) +import Data.List (intersperse) +import Data.Maybe (fromJust) +import System.Environment + +type HPLprob = Char -> Int -> Double + +-- lookup and return probability of this hpl length for this letter +mkHPLprobs :: M.Map (Char,Int) Int -> HPLprob +mkHPLprobs ft = let totals = [(c, fromIntegral $ sum [M.findWithDefault 0 (c,x) ft | x <- [0..50]]) | c <- "ACGT" ] + in \ch n -> fromIntegral (M.findWithDefault 0 (ch,n) ft) / fromJust (lookup ch totals) + +main = do + [f] <- getArgs + display "tacg" . freqtable . concatMap (hpls "tacg" . seqdata) =<< readFasta f + +display :: [Char] -> M.Map (Char,Int) Int -> IO () +display fs m = let imax = maximum $ map snd $ M.keys m + header = concat ("len\t " : intersperse "\t " (map (return . toUpper) fs)) + in putStrLn $ unlines (header : [ printf "%3d" i ++ concat [ printf "\t%5d" (M.findWithDefault 0 (c,i) m) | c <- map toUpper fs ] | i <- [0..imax]]) + +freqtable :: [(Char,Int)] -> M.Map (Char,Int) Int +freqtable = go M.empty + where + go m [] = m + go m (i:is) = let v = M.findWithDefault 0 i m + v' = v+1 + m' = M.insert i v' m + in v' `seq` m' `seq` go m' is + +hpls :: [Char] -> SeqData -> [(Char,Int)] +hpls xs = go (cycle xs') + where xs' = map toUpper xs + go (f:fs) sd | B.null sd = [] + | not (elem (toUpper $ B.head sd) xs') = go (f:fs) (B.tail sd) + | otherwise = let (this,rest) = B.span ((==f).toUpper) sd + in (f,fromIntegral (B.length this)) : go fs rest diff --git a/src/Statistics.hs b/src/Statistics.hs new file mode 100644 --- /dev/null +++ b/src/Statistics.hs @@ -0,0 +1,154 @@ +{-# LANGUAGE ForeignFunctionInterface #-} + +-- | Yet another simple module for implementing statistics stuff. +module Statistics (sample, samples, normal, normals + , stdnormal, stdnormals, Distribution(..), Prob(..) + , pdf, pvalue, fromPdf, invcum, worsen + , module Control.Monad.Random + ) where + +import Control.Monad.Random +import Data.Array.Unboxed + +foreign import ccall "erf" erf :: Double -> Double + +newtype Prob = P Double deriving Show + +instance Random Prob where + random g = let (a,g') = randomR (0,1) g in (P a,g') + randomR = error "Specifying a range for a probability makes no sense." + +-- Todo: implement +data Distribution = Normal Double Double -- ^ mu and sigma + | LogNormal Double Double -- ^ mu and sigma + | Uniform Double Double -- ^ from/to inclusive + | Empirical Double Double (UArray Int Double) + -- ^ Stores a cumulative distribution, centered on first + -- param (ref. 'worsen'), and second param is step size + deriving (Show,Read) + -- add more: StudentsT, SkewNormal, SkewT + +-- dummy to make deriving Read work +instance Read (UArray i d) where + +-- | Build an empirical probablility distribution by mapping the given probabilities +-- to uniformly spaced points starting at 'start' with 'step' points per unit. +-- Automatically center on pvalue = 50. +fromPdf :: Double -> Double -> [Prob] -> Distribution +fromPdf start h ps = let ps' = acc 0 $ map ((/scale) . unprob) $ ps + mu = start+(fromIntegral . length . takeWhile (<0.5)) ps'*h-h/2 + a = floor ((start-mu)/h) + b = a+length ps' + scale = sum [ x | P x <- ps] + unprob (P x) = x + acc _ [] = [1] + acc c (x:xs) = let v = c+x + in if v >= 1 then [1] else v : acc v xs + in Empirical mu h $ listArray (a,b) (0:ps') + +invcum :: Distribution -> Prob -> Double +invcum (Normal mu sigma) (P z) = invcumnorm mu sigma z +invcum (LogNormal mu sigma) (P z) = exp $ invcum (Normal mu sigma) (P z) +invcum (Uniform a b) (P z) = a+(b-a)*z +invcum (Empirical mu h cd) (P z) = let (a,b) = bounds cd in mu+bisect ((cd!).round) (fromIntegral a) (fromIntegral b) z * h + + +-- | Calculate probability of sampling less than x +-- (i.e. the cumulative distribution's value in x) +pvalue :: Distribution -> Double -> Prob +pvalue (Normal mu sigma) x = P (cumnorm mu sigma x) +pvalue (Uniform a b) x | x <= a = P 0 + | x >= b = P 1 + | otherwise = P ((x-a)/(b-a)) +pvalue (LogNormal mu sigma) x | x<1e-10 = P 0 -- not sufficient! + | otherwise = P (cumlognorm mu sigma x) +pvalue (Empirical mu h cd) x = let (a,b) = bounds cd + x' = (x-mu)/h + in if x' < fromIntegral a then P 0 + else if x' >= fromIntegral b then P 1 + else let x1 = floor x' + x2 = x1+1 + y1 = cd!x1 + y2 = cd!x2 + in P (y1 + (y2-y1)*(x'-fromIntegral x1)) + +-- general functions for sampling + +sample :: RandomGen g => Distribution -> Rand g Double +sample d = invcum d `fmap` getRandom + +-- sample (Uniform a b) = getRandomR (a,b) +-- todo: replace with general function: +samples :: RandomGen g => Distribution -> Rand g [Double] +samples (Normal mu sigma) = normals mu sigma +samples (LogNormal mu sigma) = map exp `fmap` samples (Normal mu sigma) +samples (Uniform a b) = getRandomRs (a,b) +samples (Empirical _mu _h _cds) = error "todo: implement 'samples' for Empirical distributions" + +-- | The probability density function +pdf :: Distribution -> Double -> Double -- Prob? +pdf (Normal mu sigma) x = exp(negate(square (x-mu)/(2*square sigma)))/(sigma*sqrt(2*pi)) +pdf (LogNormal mu sigma) x + | x>0 = exp(negate(square (log x-mu)/(2*square sigma)))/(x*sigma*sqrt(2*pi)) + | otherwise = 0 +pdf (Uniform a b) x + | x= a = 1/(b-a) -- interval is open on the right, to work correctly with empirical below + | otherwise = 0 +pdf (Empirical mu h cd) x = let (a,b) = bounds cd + x' = (x-mu)/h + in if x' < fromIntegral a then 0 + else if x' >= fromIntegral b then 0 + else let x1 = floor x' + x2 = x1+1 + y1 = cd!x1 + y2 = cd!x2 + in (y2-y1)/h +-- ------------------------------ +-- Specifics +-- ------------------------------ +square :: Double -> Double +square x = x * x + +stdnormal :: RandomGen g => Rand g Double +stdnormal = normal 0 1 + +stdnormals :: RandomGen g => Rand g [Double] +stdnormals = normals 0 1 + +normal :: RandomGen g => Double -> Double -> Rand g Double +normal mu sigma = do x <- getRandomR (0,1) + return (invcumnorm mu sigma x) + +normals :: RandomGen g => Double -> Double -> Rand g [Double] +normals mu sigma = do x <- normal mu sigma + xs <- normals mu sigma + return (x : xs) + +-- support +invcumnorm :: Double -> Double -> Double -> Double +invcumnorm mu sigma z = mu + bisect (cumnorm 0 sigma) (-limit*sigma) (limit*sigma) z + +bisect :: (Double -> Double) -> Double -> Double -> Double -> Double +bisect f a b z = let c = (a+b)/2 + cn = f c + in if abs (z - cn) < 10*epsilon || abs (a-b) < epsilon then c + else if cn > z then bisect f a c z + else bisect f c b z + +cumnorm :: Double -> Double -> Double -> Double +cumnorm mu sigma x = 0.5*(1+erf((x-mu)/(sigma*sqrt 2))) + +cumlognorm :: Double -> Double -> Double -> Double +cumlognorm mu sigma x = 0.5+0.5*erf ((log x-mu)/(sigma*sqrt 2)) + +epsilon, limit :: Double +epsilon = 0.0000000001 +limit = 4.4 + +-- | Make a distribution wider by expanding (or contracting, if less than 1) +-- its stdev by some factor +worsen :: Double -> Distribution -> Distribution +worsen d (Normal mu sigma) = Normal mu (sigma*d) +worsen d (LogNormal mu sigma) = LogNormal mu (sigma*d) +worsen d (Uniform a b) = Uniform (a*(1-d)) (b*d) -- assumption alert? +worsen d (Empirical mu h ds) = Empirical mu (h*d) ds