clustertools-0.1.5: src/ClusterLibs.hs
-- clusterLibs
-- calculate clusters by library, using the lib table
-- read patterns from a table, first line is header
module Main where
import System.Environment (getArgs)
import Data.List (intersperse)
import Numeric (showFFloat)
import Statistics
import Formats (LibTable, Cluster
, readPatternTable, totalsByLib, readClusters, countClusters, classify)
main :: IO ()
main = do
[ps,cs] <- do [xs,ys] <- getArgs
return [xs,ys]
`catch` error "Usage: clusterlibs <libtable> <clusters>"
pat <- readPatternTable ps
counts <- totalsByLib pat cs
writeTable [("","sum":map snd pat++["significance"])]
writeTable . map (decorate counts) . countClusters pat =<< readClusters cs
-- | Using count by library, takes a cluster, calculates significance scores
-- and formats it for output.
decorate :: (String,[Int]) -> (String,[Int]) -> (String,[String])
decorate counts (x,ys) =
let fractions = [ fromIntegral x / fromIntegral (sum $ snd counts) | x <- snd counts]
clustersize = sum ys
significance = unwords $ zipWith isSignificant ys fractions
isSignificant obs frac = showFFloat (Just 3) (pvalue (1-frac) clustersize (clustersize-obs)) ""
in (x,map show (clustersize:ys) ++ [significance])
-- --------------------------------------------------
-- | Calculate the p value of observing k sequences
-- from a library, given an a priori background distribution.
pvalue :: Double -> Int -> Int -> Double
pvalue fraction tot obs = cumbin fraction tot obs
-- --------------------------------------------------
-- will need to match against all, to check for multiple matches
-- tag names with library
classClusters :: LibTable -> FilePath -> IO [Cluster]
classClusters ps f = return . map class1 =<< readClusters f
where class1 (l,ss) = (l, map (\s -> classify ps s++":"++s) ss)
-- | Output the clusters to stdout
writeTable :: [(String,[String])] -> IO ()
writeTable = putStrLn . unlines . map show1
where
show1 (name,stuff) = concat $ intersperse "\t" (name:stuff)