synapsis
This is the released version of synapsis; for the devel version, see synapsis.
An R package to automate the analysis of double-strand break repair during meiosis
Bioconductor version: Release (3.23)
Synapsis is a Bioconductor software package for automated (unbiased and reproducible) analysis of meiotic immunofluorescence datasets. The primary functions of the software can i) identify cells in meiotic prophase that are labelled by a synaptonemal complex axis or central element protein, ii) isolate individual synaptonemal complexes and measure their physical length, iii) quantify foci and co-localise them with synaptonemal complexes, iv) measure interference between synaptonemal complex-associated foci. The software has applications that extend to multiple species and to the analysis of other proteins that label meiotic prophase chromosomes. The software converts meiotic immunofluorescence images into R data frames that are compatible with machine learning methods. Given a set of microscopy images of meiotic spread slides, synapsis crops images around individual single cells, counts colocalising foci on strands on a per cell basis, and measures the distance between foci on any given strand.
Author: Lucy McNeill [aut, cre, cph]
, Wayne Crismani [rev, ctb]
Maintainer: Lucy McNeill <luc.mcneill at gmail.com>
citation("synapsis")):
Huber W, Carey VJ, Gentleman R, Anders S, Carlson M, Carvalho BS, Bravo HC, Davis S, Gatto L, Girke T, Gottardo R, Hahne F, Hansen KD, Irizarry RA, Lawrence M, Love MI, MacDonald J, Obenchain V, Oleś AK, Pagès H, Reyes A, Shannon P, Smyth GK, Tenenbaum D, Waldron L, Morgan M (2015). "Orchestrating high-throughput genomic analysis with Bioconductor." Nature Methods, 12(2), 115–121. doi:10.1038/nmeth.3252.
Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, Ellis B, Gautier L, Ge Y, Gentry J, Hornik K, Hothorn T, Huber W, Iacus S, Irizarry R, Leisch F, Li C, Maechler M, Rossini AJ, Sawitzki G, Smith C, Smyth G, Tierney L, Yang JYH, Zhang J (2004). "Bioconductor: open software development for computational biology and bioinformatics." Genome Biology, 5(10), R80. doi:10.1186/gb-2004-5-10-r80.
Installation
To install this package, start R (version "4.6") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("synapsis")
For older versions of R, please refer to the appropriate Bioconductor release.
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("synapsis")| Using-synapsis | HTML | R Script |
| Reference Manual | ||
| NEWS | Text | |
| LICENSE | Text |
Details
| biocViews | SingleCell, Software |
| Version | 1.18.0 |
| In Bioconductor since | BioC 3.14 (R-4.1) (5 years) |
| License | MIT + file LICENSE |
| Depends | R (>= 4.1) |
| Imports | EBImage, stats, utils, graphics |
| System Requirements | |
| URL |
See More
| Suggests | knitr, rmarkdown, testthat (>= 3.0.0), ggplot2, tidyverse, BiocStyle |
| Linking To | |
| Enhances | |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Links To Me | |
| Build Report | Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Source Package | synapsis_1.18.0.tar.gz |
| Windows Binary (x86_64) | synapsis_1.18.0.zip |
| macOS Binary (big-sur-x86_64) | synapsis_1.18.0.tgz |
| macOS Binary (sonoma-arm64) | synapsis_1.18.0.tgz |
| Source Repository | git clone https://git.bioconductor.org/packages/synapsis |
| Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/synapsis |
| Bioc Package Browser | https://code.bioconductor.org/browse/synapsis/ |
| Package Short Url | https://bioconductor.org/packages/synapsis/ |
| Package Downloads Report | Download Stats |