## Information about packages

### show installed packages

- show just the names of the installed packages (ordered)

sort(row.names(installed.packages()))

[1] "abind" "acepack" "AER" "akima" [5] "anchors" "ape" "base" "bdsmatrix" [9] "biglm" "Biobase" "BiocInstaller" "bitops" [13] "boot" "car" "CarbonEL" "caTools" [17] "chron" "class" "cluster" "coda" [21] "coda" "codetools" "coin" "colorspace" [25] "compiler" "CompQuadForm" "cubature" "DAAG" [29] "datasets" "DBI" "Deducer" "DeducerExtras" [33] "degreenet" "Design" "digest" "diptest" [37] "doMC" "doSNOW" "dynlm" "e1071" [41] "Ecdat" "effects" "ellipse" "ergm" [45] "fBasics" "fCalendar" "fEcofin" "flexmix" ...

- the command
*installed.packages()*provides much more information:

colnames(installed.packages())

[1] "Package" "LibPath" "Version" "Priority" "Depends" "Imports" [7] "LinkingTo" "Suggests" "Enhances" "OS_type" "License" "Built"

- so if you want to know the package and its version

installed.packages()[,c("Package","Version")] # you can also use the col numbers c(1,3)

Package Version Biobase "Biobase" "2.14.0" BiocInstaller "BiocInstaller" "1.2.1" GenABEL "GenABEL" "1.6-9" multtest "multtest" "2.10.0" abind "abind" "1.3-0" acepack "acepack" "1.3-3.0" AER "AER" "1.1-7" akima "akima" "0.5-4" anchors "anchors" "3.0-7" ape "ape" "2.7-1" bdsmatrix "bdsmatrix" "1.0" ...

- show information about a package

packageDescription("multtest")

Package: multtest Title: Resampling-based multiple hypothesis testing Version: 2.10.0 Author: Katherine S. Pollard, Houston N. Gilbert, Yongchao Ge, Sandra Taylor, Sandrine Dudoit Description: Non-parametric bootstrap and permutation resampling-based multiple testing procedures (including empirical Bayes methods) for controlling the family-wise error rate (FWER), generalized family-wise error rate (gFWER), tail probability of the proportion of false positives (TPPFP), and false discovery rate (FDR). Several choices of bootstrap-based null distribution are implemented (centered, centered and scaled, quantile-transformed). Single-step and step-wise methods are available. Tests based on a variety of t- and F-statistics (including t-statistics based on regression parameters from linear and survival models as well as those based on correlation parameters) are included. When probing hypotheses with t-statistics, users may also select a potentially faster null distribution which is multivariate normal with mean zero and variance covariance matrix derived from the vector influence function. Results are reported in terms of adjusted p-values, confidence regions and test statistic cutoffs. The procedures are directly applicable to identifying differentially expressed genes in DNA microarray experiments. Maintainer: Katherine S. Pollard <kpollard@gladstone.ucsf.edu> Depends: R (>= 2.9.0), methods, Biobase Imports: survival, MASS Suggests: snow License: LGPL biocViews: Microarray, DifferentialExpression, MultipleComparisons LazyLoad: yes Packaged: 2011-11-01 04:28:05 UTC; biocbuild Built: R 2.14.0; i686-pc-linux-gnu; 2011-11-11 10:32:24 UTC; unix -- File: /home/mandy/R/i686-pc-linux-gnu-library/2.14/multtest/Meta/package.rds

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