/fingerprint/man/bitspec.Rd
Unknown | 46 lines | 44 code | 2 blank | 0 comment | 0 complexity | d839bab10da6f334946a447b19f4b559 MD5 | raw file
1\name{bit.spectrum} 2\alias{bit.spectrum} 3\title{ 4 Generate a Bit Spectrum from a List of Fingerprints 5} 6\description{ 7The idea of comparing datasets using fingerprints was described in 8Guha \& Schurer (2008). The idea is that one can summarize the dataset 9by counting the frequency of occurrence of each bit position. The 10frequency is normalized by the number of fingerprints considered. Thus a 11collection of N fingerprints can be converted to a single vector of 12numbers highlighting the most frequent bits with respect to a given 13dataset. A plot of this vector looks like a traditional spectrum and 14hence the name. 15 16The bit spectra for two datasets (assuming that the same types of 17fingerprints have been used) allows one to compare the similarity of 18the datasets, without having to do a full pairwise similarity 19calculation. The difference between the structural features of the 20datasets can be quantified by evaluating the distance between the two 21bit spectra. 22} 23\usage{ 24bit.spectrum(fplist) 25} 26\arguments{ 27 \item{fplist}{ 28 A list structure with each element being an object of class 29 \code{fingerprint}. These will can be constructed by hand or 30 read from disk via \code{\link{fp.read}}. 31 32 All fingerprints in the list should be of the same length. 33 } 34} 35\value{ 36A numeric vector of length equal to the size of the fingerprints. 37} 38\seealso{ 39 \code{\link{distance}}, \code{\link{fp.read}} 40} 41\references{ 42Guha, R.; Schurer, S.; \emph{J. Comp. Aid. Molec. Des.}, \bold{2008}, 43 \emph{22}, 367-384. 44} 45\keyword{programming} 46\author{Rajarshi Guha \email{rajarshi.guha@gmail.com}}