Package: imageHTS
Version: 1.22.0
Title: Analysis of high-throughput microscopy-based screens
Author: Gregoire Pau, Xian Zhang, Michael Boutros, Wolfgang Huber
Maintainer: Joseph Barry <joseph.barry@embl.de>
Depends: R (>= 2.9.0), EBImage (>= 4.3.12), cellHTS2 (>= 2.10.0)
Imports: tools, Biobase, hwriter, methods, vsn, stats, utils, e1071
Description: imageHTS is an R package dedicated to the analysis of
high-throughput microscopy-based screens. The package provides
a modular and extensible framework to segment cells, extract
quantitative cell features, predict cell types and browse
screen data through web interfaces. Designed to operate in
distributed environments, imageHTS provides a standardized
access to remote data and facilitates the dissemination of
high-throughput microscopy-based datasets.
License: LGPL-2.1
Suggests: BiocStyle, MASS
biocViews: Software, CellBasedAssays, Preprocessing, Visualization
NeedsCompilation: no
Packaged: 2016-05-04 03:42:57 UTC; biocbuild
Package: HD2013SGI
Type: Package
Title: Mapping genetic interactions in human cancer cells with RNAi and
multiparametric phenotyping
Version: 1.12.0
Author: Bernd Fischer
Maintainer: Bernd Fischer <b.fischer@dkfz.de>
Description: This package contains the experimental data and a complete executable transcript (vignette) of the analysis of the HCT116 genetic interaction matrix presented in the paper "Mapping genetic interactions in human cancer cells with RNAi and multiparametric phenotyping" by C. Laufer, B. Fischer, M. Billmann, W. Huber, M. Boutros; Nature Methods (2013) 10:427-31. doi: 10.1038/nmeth.2436.
License: Artistic-2.0
LazyLoad: true
Depends: R (>= 2.10.0), RColorBrewer, gplots, geneplotter, splots, limma, vcd, LSD, EBImage
Suggests: BiocStyle
SystemRequirements: GNU make
biocViews: ExperimentData, CancerData, ColonCancerData,
MicrotitrePlateAssayData, CellCulture, Homo_sapiens_Data,
HighThroughputImagingData
NeedsCompilation: no
Packaged: 2016-05-07 20:40:24 UTC; biocbuild
Package: DonaPLLP2013
Type: Package
Title: Supplementary data package for Dona et al. (2013) containing
example images and tables
Version: 1.10.0
Date: 2013-06-27
Author: Erika Dona, Joseph D. Barry, Guillaume Valentin, Charlotte Quirin, Anton
Khmelinskii, Andreas Kunze, Sevi Durdu, Lionel R. Newton, Ana Fernandez-Minan, Wolfgang Huber, Michael Knop, Darren Gilmour
Maintainer: Joseph D. Barry <joseph.barry@embl.de>
Depends: EBImage, parallel
Description: An experiment data package associated with the publication Dona et
al. (2013). Package contains runnable vignettes showing an example image
segmentation for one posterior lateral line primordium, and also the data table
and code used to analyze tissue-scale lifetime-ratio statistics.
biocViews: ExperimentData, Tissue
License: Artistic-2.0
Packaged: 2016-05-07 20:45:54 UTC; biocbuild
NeedsCompilation: no
Package: PGPC
Type: Package
Title: Experimental data and analysis of the chemical-genetic
interaction screen in isogenic HCT116 cell lines
Version: 1.0.2
Author: Felix Klein
Maintainer: Felix Klein <felix.klein@embl.de>
Description: This package contains the experimental data and a vignette
guiding through the analysis of a chemical-genenetic
interaction screen in isogenic HCT116 cell lines. The code can
be executed to generate all results and figures for the
manuscript "A chemical-genetic interaction map of small molecules using
high-throughput imaging in cancer cells" accepted for publicaton at
Molecular Systems Biology. Data availability: Complementary views on
this dataset are available through different repositories. The image
data files are available from the BioStudies database at the European
Bioinformatics Institute (EMBL-EBI) under the accession S-BSMS-PGPC1
(http://wwwdev.ebi.ac.uk/biostudies/studies/S-BSMS-PGPC1)
An interactive front-end for exploration of the images is provided by
the IDR database http://dx.doi.org/10.17867/10000101.
The authors are hosting an interactive webpage to browse images and
interaction profiles at http://dedomena.embl.de/PGPC.
License: Artistic-2.0
LazyLoad: true
Depends: R (>= 3.0), EBImage, imageHTS, SearchTrees, limma, RColorBrewer, gplots, splots, ggplot2, geneplotter, ChemmineR, reshape2, plyr
VignetteBuilder: knitr
Suggests: BiocStyle, knitr
biocViews: CancerData, ColonCancerData, ExperimentData
NeedsCompilation: no
Packaged: 2016-05-28 15:50:08 UTC; biocbuild
Package: FISHalyseR
Type: Package
Title: FISHalyseR a package for automated FISH quantification
Version: 1.6.2
Date: 2015-04-08
Author: Karesh Arunakirinathan <akaresh88@gmail.com>, Andreas Heindl
<andreas.heindl@icr.ac.uk>
Maintainer: Karesh Arunakirinathan <akaresh88@gmail.com>, Andreas
Heindl <andreas.heindl@icr.ac.uk>
Description: FISHalyseR provides functionality to process and analyse
digital cell culture images, in particular to quantify FISH
probes within nuclei. Furthermore, it extract the spatial
location of each nucleus as well as each probe enabling spatial
co-localisation analysis.
VignetteBuilder: knitr
License: Artistic-2.0
Depends: EBImage, abind
Suggests: knitr
biocViews: CellBiology
NeedsCompilation: no
Packaged: 2016-05-16 05:22:13 UTC; biocbuild
Package: flowcatchR
Type: Package
Title: Tools to analyze in vivo microscopy imaging data focused on
tracking flowing blood cells
Version: 1.6.2
Date: 2015-10-08
Authors@R: person("Federico", "Marini", email = "marinif@uni-mainz.de",
role = c("aut", "cre"))
Maintainer: Federico Marini <marinif@uni-mainz.de>
Description: flowcatchR is a set of tools to analyze in vivo microscopy imaging
data, focused on tracking flowing blood cells. It guides the steps from
segmentation to calculation of features, filtering out particles not of
interest, providing also a set of utilities to help checking the quality of
the performed operations (e.g. how good the segmentation was). It allows investigating the
issue of tracking flowing cells such as in blood vessels, to categorize the particles in
flowing, rolling and adherent. This classification is applied in the study of phenomena such as
hemostasis and study of thrombosis development. Moreover, flowcatchR presents an integrated
workflow solution, based on the integration with a Shiny App and Jupyter notebooks, which is
delivered alongside the package, and can enable fully reproducible bioimage analysis in the
R environment.
License: BSD_3_clause + file LICENSE
VignetteBuilder: knitr
Suggests: BiocStyle, knitr, shiny
Depends: R (>= 2.10), methods, EBImage
Imports: rgl, colorRamps, abind, BiocParallel
SystemRequirements: ImageMagick
LazyData: true
URL: https://github.com/federicomarini/flowcatchR
BugReports: https://github.com/federicomarini/flowcatchR/issues
biocViews: Software, Visualization, CellBiology, Classification,
Infrastructure, GUI
NeedsCompilation: no
Packaged: 2016-05-16 04:56:52 UTC; biocbuild
Author: Federico Marini [aut, cre]
Package: furrowSeg
Type: Package
Title: Furrow Segmentation
Version: 1.0.2
Date: 2015-15-10
Author: Joseph Barry
Maintainer: Joseph Barry <joseph.barry@embl.de>
Depends: R (>= 3.3), EBImage
Suggests: BiocStyle, ggplot2, knitr
VignetteBuilder: knitr
Imports: abind, dplyr, locfit, tiff
Description: Image feature data and analysis codes for the Guglielmi,
Barry et al. paper describing the application of an
optogenetics tools to disrupt Drosophila embryo furrowing.
biocViews: ExperimentData, Drosophila_melanogaster_Data, Tissue,
ReproducibleResearch
License: Artistic-2.0
NeedsCompilation: no
Packaged: 2016-05-28 16:05:55 UTC; biocbuild
providing 
.