## ----style, echo = FALSE, results = 'asis'-------------------------------------------------------- BiocStyle::markdown() options(width=100, max.print=1000) knitr::opts_chunk$set( eval=as.logical(Sys.getenv("KNITR_EVAL", "TRUE")), cache=as.logical(Sys.getenv("KNITR_CACHE", "TRUE"))) ## ----setup, echo=FALSE, messages=FALSE, warnings=FALSE-------------------------------------------- suppressPackageStartupMessages({ library(ChemmineR) library(fmcsR) }) ## ----eval=FALSE----------------------------------------------------------------------------------- # if (!requireNamespace("BiocManager", quietly=TRUE)) # install.packages("BiocManager") # BiocManager::install("fmcsR") ## ----quicktest1, eval=TRUE, fig=TRUE,fig.scap="Structures depictions of sample data."------------- library(fmcsR) data(fmcstest) plot(fmcstest[1:3], print=FALSE) ## ----quicktest2, eval=TRUE, fig=TRUE-------------------------------------------------------------- test <- fmcs(fmcstest[1], fmcstest[2], au=2, bu=1) plotMCS(test,regenCoords=TRUE) ## ----eval=TRUE, keep.source=TRUE------------------------------------------------------------------ library("fmcsR") # Loads the package ## ----eval=FALSE, keep.source=TRUE----------------------------------------------------------------- # library(help="fmcsR") # Lists functions/classes provided by fmcsR # library(help="ChemmineR") # Lists functions/classes from ChemmineR # vignette("fmcsR") # Opens this PDF manual # vignette("ChemmineR") # Opens ChemmineR PDF manual ## ----eval=FALSE, keep.source=TRUE----------------------------------------------------------------- # ?fmcs # ?"MCS-class" # ?"SDFset-class" ## ----eval=TRUE, keep.source=TRUE------------------------------------------------------------------ data(fmcstest) sdfset <- fmcstest sdfset ## ----eval=FALSE, keep.source=TRUE----------------------------------------------------------------- # write.SDF(sdfset, file="sdfset.sdf") # mysdf <- read.SDFset(file="sdfset.sdf") ## ----eval=TRUE, keep.source=TRUE------------------------------------------------------------------ mcsa <- fmcs(sdfset[[1]], sdfset[[2]]) mcsa mcsb <- fmcs(sdfset[[1]], sdfset[[3]]) mcsb ## ----eval=TRUE, keep.source=TRUE------------------------------------------------------------------ fmcs(sdfset[1], sdfset[2], fast=TRUE) ## ----eval=TRUE, keep.source=TRUE------------------------------------------------------------------ slotNames(mcsa) ## ----eval=TRUE, keep.source=TRUE------------------------------------------------------------------ stats(mcsa) # or mcsa[["stats"]] mcsa1 <- mcs1(mcsa) # or mcsa[["mcs1"]] mcsa2 <- mcs2(mcsa) # or mcsa[["mcs2"]] mcsa1[1] # returns SDFset component mcsa1[[2]][1:2] # return first two index vectors ## ----eval=TRUE, fig=TRUE, keep.source=TRUE-------------------------------------------------------- mcstosdfset <- mcs2sdfset(mcsa, type="new") plot(mcstosdfset[[1]], print=FALSE) ## ----eval=TRUE, keep.source=TRUE------------------------------------------------------------------ mylist <- list(stats=stats(mcsa), mcs1=mcs1(mcsa), mcs2=mcs2(mcsa)) as(mylist, "MCS") ## ----au0bu0, eval=TRUE, fig=TRUE------------------------------------------------------------------ plotMCS(fmcs(sdfset[1], sdfset[2], au=0, bu=0)) ## ----au1bu1, eval=TRUE, fig=TRUE------------------------------------------------------------------ plotMCS(fmcs(sdfset[1], sdfset[2], au=1, bu=1)) ## ----au2bu2, eval=TRUE, fig=TRUE------------------------------------------------------------------ plotMCS(fmcs(sdfset[1], sdfset[2], au=2, bu=2)) ## ----au0bu013, eval=TRUE, fig=TRUE---------------------------------------------------------------- plotMCS(fmcs(sdfset[1], sdfset[3], au=0, bu=0)) ## ----eval=TRUE, keep.source=TRUE------------------------------------------------------------------ data(sdfsample) # Loads larger sample data set sdf <- sdfsample fmcsBatch(sdf[1], sdf[1:30], au=0, bu=0) ## ----tree, eval=TRUE, fig=TRUE-------------------------------------------------------------------- sdf <- sdf[1:7] d <- sapply(cid(sdf), function(x) fmcsBatch(sdf[x], sdf, au=0, bu=0, matching.mode="aromatic")[,"Overlap_Coefficient"]) d hc <- hclust(as.dist(1-d), method="complete") plot(as.dendrogram(hc), edgePar=list(col=4, lwd=2), horiz=TRUE) ## ----au0bu024, eval=TRUE, fig=TRUE---------------------------------------------------------------- plotMCS(fmcs(sdf[3], sdf[7], au=0, bu=0, matching.mode="aromatic")) ## ----sessionInfo, print=TRUE--------------------------------------------------------------------- sessionInfo()