SCM

R Development Page

Contributed R Packages

Below is a list of all packages provided by project MotilityLab.

Important note for package binaries: R-Forge provides these binaries only for the most recent version of R, but not for older versions. In order to successfully install the packages provided on R-Forge, you have to switch to the most recent version of R or, alternatively, install from the package sources (.tar.gz).

Packages

EpitopePrediction

Predict Binding Between Peptides and MHC Molecules

  Predicts binding of 9-to 12-mer peptides to MHC class I molecules using the stabilized matrix method. Can predict binding for several alleles from humans (HLA A/B), mice (H-2), chimpanzees (Patr A/B), and rhesus macaques (Mamu A/B).
  Version: 0.1-2 | Last change: 2016-01-20 15:14:20+01 | Rev.: 79
  Download: linux(.tar.gz) | windows(.zip) | Build status: Current
  R install command: install.packages("EpitopePrediction", repos="http://R-Forge.R-project.org")
 
Logs:  
Package build: Source package (Linux x86_64) Windows binary (x86_64/i386)
Package check: Linux x86_64 (patched) | Linux x86_64 (devel) Windows (patched) | Windows (devel)


MotilityLab

Quantitative Analysis of Motion

  Statistics to quantify tracks of moving things (x-y-z-t data), such as cells, bacteria or animals. Available measures include mean square displacement, confinement ratio, autocorrelation, straightness, turning angle, and fractal dimension.
  Version: 0.2-4 | Last change: 2015-11-19 16:11:13+01 | Rev.: 66
  Download: linux(.tar.gz) | windows(.zip) | Build status: Current | Stable Release: Get MotilityLab 0.2-5 from CRAN
  R install command: install.packages("MotilityLab", repos="http://R-Forge.R-project.org")
 
Logs:  
Package build: Source package (Linux x86_64) Windows binary (x86_64/i386)
Package check: Linux x86_64 (patched) | Linux x86_64 (devel) Windows (patched) | Windows (devel)


dagitty

Graphical Analysis of Structural Causal Models

  A port of the web-based software DAGitty, available at , for analyzing structural causal models (also known as directed acyclic graphs or DAGs). This package computes covariate adjustment sets for estimating causal effects, enumerates instrumental variables, derives testable implications (d-separation and vanishing tetrads), generates equivalent models, and includes a simple facility for data simulation.
  Version: 0.2-2 | Last change: 2016-08-26 11:18:31+02 | Rev.: 88
  Download: linux(.tar.gz) | windows(.zip) | Build status: Current | Stable Release: Get dagitty 0.2-2 from CRAN
  R install command: install.packages("dagitty", repos="http://R-Forge.R-project.org")
 
Logs:  
Package build: Source package (Linux x86_64) Windows binary (x86_64/i386)
Package check: Linux x86_64 (patched) | Linux x86_64 (devel) Windows (patched) | Windows (devel)

 

Build status codes

0 - Current: the package is available for download. The corresponding package passed checks on the Linux and Windows platform without ERRORs.
1 - Scheduled for build: the package has been recognized by the build system and provided in the staging area.
2 - Building: the package has been sent to the build machines. It will be built and checked using the latest patched version of R. Note that it is included in a batch of several packages. Thus, this process will take some time to finish.
3 - Failed to build: the package failed to build or did not pass the checks on the Linux and/or Windows platform. It is not made available since it does not meet the policies.
4 - Conflicts: two or more packages of the same name exist. None of them will be built. Maintainers are asked to negotiate further actions.
5 - Offline: the package is not available. The build system may be offline or the package maintainer did not trigger a rebuild (done e.g., via committing to the package repository).

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