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biocLite("flowcatchR")
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flowcatchR
Tools to analyze in vivo microscopy imaging data focused on tracking flowing blood cells.
Bioconductor version: 3.0
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). The main novel contribution investigates 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.
Author: Federico Marini [aut, cre]
Maintainer: Federico Marini <marinif at uni-mainz.de>
Citation (from within R,
enter citation("flowcatchR")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("flowcatchR")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("flowcatchR")
| R Script | flowcatchR: tracking and analyzing cells in time lapse microscopy images | |
| Reference Manual | ||
| Text | NEWS | |
| Text | LICENSE |
Details
| biocViews | CellBiology, Classification, GUI, Infrastructure, Software, Visualization |
| Version | 1.0.3 |
| In Bioconductor since | BioC 3.0 (R-3.1) |
| License | BSD_3_clause + file LICENSE |
| Depends | R (>= 2.10), methods, EBImage |
| Imports | rgl, colorRamps, abind, BiocParallel |
| LinkingTo | |
| Suggests | BiocStyle, knitr, shiny |
| SystemRequirements | ImageMagick |
| Enhances | |
| URL | https://github.com/federicomarini/flowcatchR |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | flowcatchR_1.0.3.tar.gz |
| Windows Binary | flowcatchR_1.0.3.zip |
| Mac OS X 10.6 (Snow Leopard) | flowcatchR_1.0.3.tgz |
| Mac OS X 10.9 (Mavericks) | flowcatchR_1.0.3.tgz |
| Browse/checkout source | (username/password: readonly) |
| Package Downloads Report | Download Stats |
Common Bioconductor workflows include:
- Oligonucleotide Arrays
- High-throughput Sequencing
- Counting Reads for Differential Expression (parathyroideSE vignette)
- Annotation
- Annotating Variants
- Annotating Ranges
- Flow Cytometry and other assays
- Candidate Binding Sites for Known Transcription Factors
- Cloud-enabled cis-eQTL search and annotation
- RNA-Seq workflow: gene-level exploratory analysis and differential expression
- Changing genomic coordinate systems with rtracklayer::liftOver
- Mass spectrometry and proteomics data analysis
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