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bioc

systemPipeR:systemPipeR: Workflow Environment for Data Analysis and Report Generation

systemPipeR is a multipurpose data analysis workflow environment that unifies R with command-line tools. It enables scientists to analyze many types of large- or small-scale data on local or distributed computer systems with a high level of reproducibility, scalability and portability. At its core is a command-line interface (CLI) that adopts the Common Workflow Language (CWL). This design allows users to choose for each analysis step the optimal R or command-line software. It supports both end-to-end and partial execution of workflows with built-in restart functionalities. Efficient management of complex analysis tasks is accomplished by a flexible workflow control container class. Handling of large numbers of input samples and experimental designs is facilitated by consistent sample annotation mechanisms. As a multi-purpose workflow toolkit, systemPipeR enables users to run existing workflows, customize them or design entirely new ones while taking advantage of widely adopted data structures within the Bioconductor ecosystem. Another important core functionality is the generation of reproducible scientific analysis and technical reports. For result interpretation, systemPipeR offers a wide range of plotting functionality, while an associated Shiny App offers many useful functionalities for interactive result exploration. The vignettes linked from this page include (1) a general introduction, (2) a description of technical details, and (3) a collection of workflow templates.

Maintained by Thomas Girke. Last updated 5 months ago.

geneticsinfrastructuredataimportsequencingrnaseqriboseqchipseqmethylseqsnpgeneexpressioncoveragegenesetenrichmentalignmentqualitycontrolimmunooncologyreportwritingworkflowstepworkflowmanagement

15.7 match 53 stars 11.56 score 344 scripts 3 dependents

docopt

docopt:Command-Line Interface Specification Language

Define a command-line interface by just giving it a description in the specific format.

Maintained by Edwin de Jonge. Last updated 4 years ago.

14.2 match 213 stars 11.29 score 1.5k scripts 19 dependents

henrikbengtsson

R.utils:Various Programming Utilities

Utility functions useful when programming and developing R packages.

Maintained by Henrik Bengtsson. Last updated 1 years ago.

7.0 match 63 stars 13.74 score 5.7k scripts 814 dependents

hugheylab

seeker:Simplified Fetching and Processing of Microarray and RNA-Seq Data

Wrapper around various existing tools and command-line interfaces, providing a standard interface, simple parallelization, and detailed logging. For microarray data, maps probe sets to standard gene IDs, building on 'GEOquery' Davis and Meltzer (2007) <doi:10.1093/bioinformatics/btm254>, 'ArrayExpress' Kauffmann et al. (2009) <doi:10.1093/bioinformatics/btp354>, Robust multi-array average 'RMA' Irizarry et al. (2003) <doi:10.1093/biostatistics/4.2.249>, and 'BrainArray' Dai et al. (2005) <doi:10.1093/nar/gni179>. For RNA-seq data, fetches metadata and raw reads from National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA), performs standard adapter and quality trimming using 'TrimGalore' Krueger <https://github.com/FelixKrueger/TrimGalore>, performs quality control checks using 'FastQC' Andrews <https://github.com/s-andrews/FastQC>, quantifies transcript abundances using 'salmon' Patro et al. (2017) <doi:10.1038/nmeth.4197> and potentially 'refgenie' Stolarczyk et al. (2020) <doi:10.1093/gigascience/giz149>, aggregates the results using 'MultiQC' Ewels et al. (2016) <doi:10.1093/bioinformatics/btw354>, maps transcripts to genes using 'biomaRt' Durinkck et al. (2009) <doi:10.1038/nprot.2009.97>, and summarizes transcript-level quantifications for gene-level analyses using 'tximport' Soneson et al. (2015) <doi:10.12688/f1000research.7563.2>.

Maintained by Jake Hughey. Last updated 7 months ago.

4.6 match 3 stars 4.78 score 1 scripts

tiledb-inc

tiledbcloud:TileDB Cloud Platform R Client Package

The TileDB Cloud Platform API Client Package offers access to the TileDB Cloud service.

Maintained by John Kerl. Last updated 8 months ago.

2.7 match 1 stars 5.22 score 92 scripts

piecepackr

ppn:Portable Piecepack Notation Parser

Parse "Portable Piecepack Notation" files. This allows you to visualize the moves for over one hundred board games.

Maintained by Trevor L. Davis. Last updated 3 days ago.

3.6 match 2.65 score 2 scripts 1 dependents

ropensci

virtuoso:Interface to 'Virtuoso' using 'ODBC'

Provides users with a simple and convenient mechanism to manage and query a 'Virtuoso' database using the 'DBI' (Data-Base Interface) compatible 'ODBC' (Open Database Connectivity) interface. 'Virtuoso' is a high-performance "universal server," which can act as both a relational database, supporting standard Structured Query Language ('SQL') queries, while also supporting data following the Resource Description Framework ('RDF') model for Linked Data. 'RDF' data can be queried using 'SPARQL' ('SPARQL' Protocol and 'RDF' Query Language) queries, a graph-based query that supports semantic reasoning. This allows users to leverage the performance of local or remote 'Virtuoso' servers using popular 'R' packages such as 'DBI' and 'dplyr', while also providing a high-performance solution for working with large 'RDF' 'triplestores' from 'R.' The package also provides helper routines to install, launch, and manage a 'Virtuoso' server locally on 'Mac', 'Windows' and 'Linux' platforms using the standard interactive installers from the 'R' command-line. By automatically handling these setup steps, the package can make using 'Virtuoso' considerably faster and easier for a most users to deploy in a local environment. Managing the bulk import of triples from common serializations with a single intuitive command is another key feature of this package. Bulk import performance can be tens to hundreds of times faster than the comparable imports using existing 'R' tools, including 'rdflib' and 'redland' packages.

Maintained by Carl Boettiger. Last updated 11 months ago.

1.3 match 9 stars 5.61 score 15 scripts