r-bioc-megadepth
BioCOnductor BigWig and BAM related utilities
This package provides an R interface to Megadepth by Christopher
Wilks available at https://github.com/ChristopherWilks/megadepth. It is
particularly useful for computing the coverage of a set of genomic regions
across bigWig or BAM files. With this package, you can build base-pair
coverage matrices for regions or annotations of your choice from BigWig
files. Megadepth was used to create the raw files provided by
https://bioconductor.org/packages/recount3.
megadepth
computes coverage from BigWig and BAM sequencing files
A major concern for the interpretation of DNA and RNA (!) sequencing is
the number of reads that cover a particular area. This package
has interesting statistics for the distinction of coding and non-coding
parts of the genome and knows how to interpret transcripts that
span multiple exons.
python3-pyimagetool
Image Tool for multidimensional analysis (Python 3)
Python Image Tool can be used to visualise analysis of data in
microscopy (STM, SSM, optics), ARPES, XRD, or other multidimensional
datasets on regularly gridded coordinates.
libsstp-api-0
Connect to a Microsoft Windows 2008 server using SSTP VPN
A client implementation of Secure Socket Tunneling Protocol (SSTP) for
Linux / Mac OS-X that allows remote access via SSTP VPN to Microsoft
Windows 2008 Server. It does so by tunneling PPP data over SSL.
sstp-client
Connect to a Microsoft Windows 2008 server using SSTP VPN
A client implementation of Secure Socket Tunneling Protocol (SSTP) for
Linux / Mac OS-X that allows remote access via SSTP VPN to Microsoft
Windows 2008 Server. It does so by tunneling PPP data over SSL.
r-cran-cmdfun
GNI R framework for building interfaces to shell commands
Writing interfaces to command line software is cumbersome. 'cmdfun'
provides a framework for building function calls to seamlessly interface
with shell commands by allowing lazy evaluation of command line
arguments. 'cmdfun' also provides methods for handling user-specific
paths to tool installs or secrets like API keys. Its focus is to equally
serve package builders who wish to wrap command line software, and to
help analysts stay inside R when they might usually leave to execute non-
R software.