r-bioc-scran
BioConductor methods for single-cell RNA-Seq data analysis
Implements functions for low-level analyses of single-cell RNA-seq data.
Methods are provided for normalization of cell-specific biases,
assignment of cell cycle phase, detection of highly variable and
significantly correlated genes, identification of marker genes, and
other common tasks in routine single-cell analysis workflows.
srain
graphical IRC client based on GTK+
Srain is a modern IRC client with a GTK+ GUI that is:
* Fully open source
* RFC 1459, 2812 compatible
* Partial IRCv3 support
* Multi-platform support (Linux, Windows, macOS and BSD)
Capabilities of a modern graphical IRC client:
* Convenient connection panel
* Interactive channel search
* Forward message in one click
* URL preview
* Desktop notification
* Special optimization for bridge/relay bot
Power-user capabilities:
* Anything can be done via commands
* Fine-grained configuration with hot update support
* Regex based message render and filter mechanisms
r-bioc-shortread
GNU R classes and methods for high-throughput short-read sequencing data
This BioConductor module is a package for input, quality assessment,
manipulation and output of high-throughput sequencing data. ShortRead is
provided in the R and Bioconductor environments, allowing ready access
to additional facilities for advanced statistical analysis, data
transformation, visualization and integration with diverse genomic
resources.
r-bioc-tfbstools
GNU R Transcription Factor Binding Site (TFBS) Analysis
TFBSTools is a package for the analysis and manipulation of
transcription factor binding sites. It includes matrices conversion
between Position Frequency Matirx (PFM), Position Weight Matirx (PWM)
and Information Content Matrix (ICM). It can also scan putative TFBS
from sequence/alignment, query JASPAR database and provides a wrapper of
de novo motif discovery software.
r-bioc-titancna
Subclonal copy number and LOH prediction from whole genome sequencing
Hidden Markov model to segment and predict regions of
subclonal copy number alterations (CNA) and loss of
heterozygosity (LOH), and estimate cellular prevalence of
clonal clusters in tumour whole genome sequencing data.