diff --git a/LICENSE b/LICENSE new file mode 100644 --- /dev/null +++ b/LICENSE @@ -0,0 +1,340 @@ + GNU GENERAL PUBLIC LICENSE + Version 2, June 1991 + + Copyright (C) 1989, 1991 Free Software Foundation, Inc. + 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA + Everyone is permitted to copy and distribute verbatim copies + of this license document, but changing it is not allowed. + + Preamble + + The licenses for most software are designed to take away your +freedom to share and change it. By contrast, the GNU General Public +License is intended to guarantee your freedom to share and change free +software--to make sure the software is free for all its users. This +General Public License applies to most of the Free Software +Foundation's software and to any other program whose authors commit to +using it. (Some other Free Software Foundation software is covered by +the GNU Library General Public License instead.) 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If this is what you want to do, use the GNU Library General +Public License instead of this License. diff --git a/README b/README new file mode 100644 --- /dev/null +++ b/README @@ -0,0 +1,49 @@ + +SYNOPSIS + + rselect - select a random set of sequences from a FASTA file. + reps - extract exact k-word repeats based that occur in + sequences grouped in different clusters. + + +INSTALLATION + + You'll need GHC or possibly another Haskell system, and the + Haskell bioinformatics library. The Makefile should work to + build and install (by default to your home directory) the + executables. + +USAGE + + rselect n [m] input.seq + + Selects n sequences from the file input.seq. If the optional + m is given, this limits the selection to happen only from the first + m sequences in the file, which may be more efficient. + + The selected sequences are written to standard output, so you + probably want to redirect them to a file. + + reps k clustered.seq + + Generate a list of repeated k-words (or k-grams) found in the sequences. + The sequences are expected to be on UniGene format, i.e. a FASTA file + with #-initiated comments separating the clusters. + + A k-word is considered repeated if it is found in more than one of the + clusters. + + reps k clustering.lst sequences.seq + + As above, but take a separate input clustering (and ignore any #'s in the + sequences. The clustering should consist of one line per cluster, with each + line containing the sequence identifier (first word after the initial '>' + in the FASTA header). + +BUGS + + Do let me know about them, at ! + +HOMEPAGE + + http://malde.org/~ketil/ 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/estreps.cabal b/estreps.cabal new file mode 100644 --- /dev/null +++ b/estreps.cabal @@ -0,0 +1,34 @@ +Name: estreps +Version: 0.1 +License: GPL +License-file: LICENSE +Author: Ketil Malde +Maintainer: Ketil Malde +Stability: Beta +Category: Bioinformatics +Synopsis: Repeats from ESTs +Description: rselect - select a random set of sequences from a FASTA file. + reps - extract exact k-word repeats based that occur in + sequences grouped in different clusters. + . + The Darcs repository is at: . +Homepage: http://malde.org/~ketil/ + +Tested-With: GHC==6.8.2 +Build-Type: Simple +Cabal-Version: >= 1.2 + +Data-Files: README + +Executable rselect + Hs-source-dirs: src + Main-Is: RSelect.lhs + Build-Depends: base>3, random, containers, bio>=0.3.3, bytestring + ghc-options: -Wall + Other-Modules: Unigene + +Executable reps + Hs-source-dirs: src + Main-Is: Repeats.lhs + Other-Modules: Util + diff --git a/src/RSelect.lhs b/src/RSelect.lhs new file mode 100644 --- /dev/null +++ b/src/RSelect.lhs @@ -0,0 +1,79 @@ + +RSelect - randomly select a number of sequences from a FASTA file + +Usage: rselect m < file.seq # prints m random sequences to stdout + rselect m n < file.seq # print m of the first n seq.s (faster) + +\begin{code} + +module Main where + +import Data.Set +import System.Environment (getArgs) +import System.Random +import System.IO + +import Bio.Sequence.Fasta + +import Unigene + +main :: IO () +main = do + as <- getArgs + case as of [m,f] -> select (read m) Nothing f + [m,n,f] -> select (read m) (Just (read n)) f + _ -> error "Usage: rselect n [m] input.seq > output.seq" + +-- | Select m out of maybe n sequences from f +-- Not specifying a maximum increases memory consumption +select :: Integer -> Maybe Integer -> FilePath -> IO () +select m mn f = do + seed <- newStdGen + hPutStrLn stderr ("Random seed: "++show seed) + ss <- ugRead f + n <- case mn of Nothing -> do hPutStrLn stderr "Counting sequences..." + n' <- countSeqs f + return (fromIntegral n') + Just n' -> return n' + let ds = if m>n then error "rselect: m is larger than n, that won't work." + else if m==n then take (fromIntegral n) $ repeat 1 + else if m<=n `div` 2 then diffs $ pick m $ randomRs (1,n) seed + else diffs $ invert n 1 $ pick (n-m) $ randomRs (1,n) seed + out = Prelude.filter (not.Prelude.null) $ choose ds ss + n `seq` hPutStrLn stderr ("N = "++show n++", M = "++show m) + mapM_ (\o -> putStrLn "# cluster delimiter" >> hWriteFasta stdout o) out + +-- | choose elements according to a list of deltas +choose :: Show a => [Integer] -> [[a]] -> [[a]] +choose = choose' [] + +choose' :: Show a => [a] -> [Integer] -> [[a]] -> [[a]] +choose' acc [] _ = [reverse acc] +choose' acc (0:ds) xss = choose' acc ds xss +choose' acc (d:ds) (xs:xss) = let ys = drop (fromIntegral d-1) xs + in if not (Prelude.null ys) then choose' (head ys:acc) ds (tail ys:xss) + else reverse acc : choose' [] ((d-fromIntegral (length xs)):ds) xss +choose' _ _ [] = error "rselect: cannot choose from empty list.\nPerhaps you specified 'n' too large?" + +-- | convert indices to deltas +diffs :: [Integer] -> [Integer] +diffs xs = diffs' (0:xs) + where + diffs' (a:b:cs) = if b<=a then error ("diffs needs a monotonically increasing sequence"++show (take 10 (a:b:cs))) + else (b-a) : diffs' (b:cs) + diffs' [_] = [] + +-- | convert a list to the list of missing values +invert :: Integer -> Integer -> [Integer] -> [Integer] +invert n i (a:cs) = [i..a-1] ++ invert n (a+1) cs +invert n i [] = [i..n] + + +-- | pick m unique integers +pick :: Integer -> [Integer] -> [Integer] +pick = pick' empty + where pick' tmp 0 _ = elems tmp + pick' tmp m (i:is) = if member i tmp then pick' tmp m is + else pick' (insert i tmp) (m-1) is + +\end{code} diff --git a/src/Repeats.lhs b/src/Repeats.lhs new file mode 100644 --- /dev/null +++ b/src/Repeats.lhs @@ -0,0 +1,100 @@ + +Cluster all ESTs against the genome + +Construct the de-Bruijn graph for each cluster +(i.e. collect the set of all k-words in each cluster) +What about multiplicity? + +For each pair of clusters, calculate the intersection. +Repeat words = U (Ci /\ Cj) -- also keep count of each word. + +(Can we use a more sophisticated data structure? I.e. keep track of +longest common exact string?) + +Check each repeat word against: repbase, simple repeats, complexity + +Parameters: word length k, and file to read clusters from + +\begin{code} + +module Main where + +import qualified Data.Set as S +import qualified Data.Map as M + +import qualified Data.ByteString.Lazy.Char8 as B +import Bio.Sequence +import Bio.Sequence.HashWord + +import Unigene + +import Control.Monad (when) +import Data.List +import Data.Maybe +import System.Environment (getArgs) + +import Util + +-- type Word = Int + +main = do + args <- getArgs + when (length args < 2 || length args > 3) + (error "usage: reps k ugfile\n or: reps k clusterfile sequencefile") + (k,rs,rl) <- initialize args + if (k>16) + then putStrLn (myshow k rl) + else putStrLn (myshow k rs) + +myshow k = unlines . map show1 + where show1 (key,count) = ">" ++ show key ++ " " ++ show count ++ "\n" ++ B.unpack (k2n k key) ++ "\n" + +initialize args = do + let k = case reads (head args) of [(k',"")] -> k' + _ -> error "k must be a positive integer" + case tail args of [csfile,sqsfile] -> do + cs <- {- countIO 10 "clusters: " . -} return . filter (not.null) . map words . lines =<< readFile csfile + sqs <- readFasta sqsfile + let rs = repeats k $ clusters cs sqs :: [(Int,Int)] + rl = repeats k $ clusters cs sqs :: [(Integer,Int)] + return (k,rs,rl) + [ugfile] -> do + ugdata <- {- countIO 10 "clusters: " =<< -} ugRead ugfile + let rs = repeats k ugdata :: [(Int,Int)] + rl = repeats k ugdata :: [(Integer,Int)] + return (k,rs,rl) + +-- build clusters from [[Label]] and [Seq Label sdata] +clusters :: [[String]] -> [Sequence] -> [[Sequence]] +clusters labels seqs = map (map mylookup) labels + where smap = M.fromListWith (error "duplicate sequences in input!") $ + map (\s -> (B.dropWhile (=='>') $ seqlabel s,s)) seqs + mylookup s = case (flip M.lookup $ smap) . B.pack $ s of + Nothing -> error ("sequence '"++s++"' in the clustering is not found in data set") + Just x -> x + +-- extract words from clusters +debruijn :: Integral w => Int -> [Sequence] -> S.Set w +debruijn k = foldl1' S.union . map (S.fromList . keys k . seqdata) +-- slightly faster than: "foldl' (flip S.insert) S.empty . concatMap (keys k)" + +keys k = map fst . hashes (rcontig k) + +-- calculate word counts +freqs :: Integral w => [S.Set w] -> M.Map w Int +freqs = foldl' union M.empty + where union :: Integral w => M.Map w Int -> S.Set w -> M.Map w Int + union a b = foldl' insert a $ S.toList b + insert a k = case M.lookup k a of + Just x -> let v' = x+1 in v' `seq` M.insert k v' a + Nothing -> M.insert k 1 a + +-- inefficient? +toMap :: Integral w => S.Set w -> M.Map w Int +toMap = M.fromList . map (\x -> (x,1)) . S.toList + +-- given word length k, calculate repeats from clusters +repeats :: Integral w => Int -> [[Sequence]] -> [(w,Int)] +repeats k = filter ((>1).snd) . M.toList . freqs . map (debruijn k) + +\end{code} diff --git a/src/Unigene.hs b/src/Unigene.hs new file mode 100644 --- /dev/null +++ b/src/Unigene.hs @@ -0,0 +1,25 @@ +-- read a clustering on Unigene format +-- each cluster separated by '^#.*$' + +module Unigene (ugRead) where + +import Control.Monad +import System.IO +import qualified Data.ByteString.Lazy.Char8 as B + +import Bio.Sequence (Sequence(..)) +import Bio.Sequence.Fasta (mkSeqs) +import Data.List (groupBy) + +-- Isn't this lazy? +ugRead :: FilePath -> IO [[Sequence]] +ugRead f = do + s <- B.readFile f + let ls = dropWhile B.null $ B.lines $ s + when (B.head (head ls) /= '#') (hPutStrLn stderr ("Warning: '"++f++"' does not look like Unigene format")) + return (clusters $ ls) + +clusters :: [B.ByteString] -> [[Sequence]] +clusters (l:ls) = let ls' = if B.head l == '#' then (l:ls) else (B.pack "# dummy UG hdr" :l:ls) + ss = groupBy (const (('#' /=) . B.head)) $ filter (not . B.null) ls' + in map (mkSeqs . tail) ss diff --git a/src/Util.hs b/src/Util.hs new file mode 100644 --- /dev/null +++ b/src/Util.hs @@ -0,0 +1,12 @@ +module Util where + +import System.IO +import System.IO.Unsafe + +countIO step msg xs = sequence $ map unsafeInterleaveIO $ ct 0 xs + where ct s xs = let (a,b) = splitAt (step-1) xs + next = s+step + output c = hPutStr stderr ((take (length (show c)+2+length msg) $ repeat ' ')++'\r':msg++show c) >> hFlush stderr + in if null b then map return a ++ [] + else map return a ++ [output next >> return (head b)] + ++ ct next (tail b)