Showing 8 of total 8 results (show query)
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
53 stars 11.52 score 344 scripts 3 dependentsbioc
ORFik:Open Reading Frames in Genomics
R package for analysis of transcript and translation features through manipulation of sequence data and NGS data like Ribo-Seq, RNA-Seq, TCP-Seq and CAGE. It is generalized in the sense that any transcript region can be analysed, as the name hints to it was made with investigation of ribosomal patterns over Open Reading Frames (ORFs) as it's primary use case. ORFik is extremely fast through use of C++, data.table and GenomicRanges. Package allows to reassign starts of the transcripts with the use of CAGE-Seq data, automatic shifting of RiboSeq reads, finding of Open Reading Frames for whole genomes and much more.
Maintained by Haakon Tjeldnes. Last updated 1 months ago.
immunooncologysoftwaresequencingriboseqrnaseqfunctionalgenomicscoveragealignmentdataimportcpp
33 stars 10.56 score 115 scripts 2 dependentsbioc
RiboCrypt:Interactive visualization in genomics
R Package for interactive visualization and browsing NGS data. It contains a browser for both transcript and genomic coordinate view. In addition a QC and general metaplots are included, among others differential translation plots and gene expression plots. The package is still under development.
Maintained by Michal Swirski. Last updated 4 days ago.
softwaresequencingriboseqrnaseq
5 stars 7.08 score 22 scriptsbioc
ribosomeProfilingQC:Ribosome Profiling Quality Control
Ribo-Seq (also named ribosome profiling or footprinting) measures translatome (unlike RNA-Seq, which sequences the transcriptome) by direct quantification of the ribosome-protected fragments (RPFs). This package provides the tools for quality assessment of ribosome profiling. In addition, it can preprocess Ribo-Seq data for subsequent differential analysis.
Maintained by Jianhong Ou. Last updated 2 months ago.
riboseqsequencinggeneregulationqualitycontrolvisualizationcoverage
4.88 score 17 scriptsbioc
RiboDiPA:Differential pattern analysis for Ribo-seq data
This package performs differential pattern analysis for Ribo-seq data. It identifies genes with significantly different patterns in the ribosome footprint between two conditions. RiboDiPA contains five major components including bam file processing, P-site mapping, data binning, differential pattern analysis and footprint visualization.
Maintained by Ji-Ping Wang. Last updated 4 months ago.
riboseqgeneexpressiongeneregulationdifferentialexpressionsequencingcoveragealignmentrnaseqimmunooncologyqualitycontroldataimportsoftwarenormalizationcpp
4.30 score 1 scriptsbioc
RiboProfiling:Ribosome Profiling Data Analysis: from BAM to Data Representation and Interpretation
Starting with a BAM file, this package provides the necessary functions for quality assessment, read start position recalibration, the counting of reads on CDS, 3'UTR, and 5'UTR, plotting of count data: pairs, log fold-change, codon frequency and coverage assessment, principal component analysis on codon coverage.
Maintained by A. Popa. Last updated 5 months ago.
riboseqsequencingcoveragealignmentqualitycontrolsoftwareprincipalcomponent
4.30 score 10 scriptsbioc
riboSeqR:Analysis of sequencing data from ribosome profiling experiments
Plotting functions, frameshift detection and parsing of sequencing data from ribosome profiling experiments.
Maintained by Samuel Granjeaud. Last updated 5 months ago.
sequencinggeneticsvisualizationriboseq
1 stars 4.25 score 14 scriptsbioc
terapadog:Translational Efficiency Regulation Analysis using the PADOG Method
This package performs a Gene Set Analysis with the approach adopted by PADOG on the genes that are reported as translationally regulated (ie. exhibit a significant change in TE) by the DeltaTE package. It can be used on its own to see the impact of translation regulation on gene sets, but it is also integrated as an additional analysis method within ReactomeGSA, where results are further contextualised in terms of pathways and directionality of the change.
Maintained by Gionmattia Carancini. Last updated 27 days ago.
riboseqtranscriptomicsgenesetenrichmentgeneregulationreactomesoftware
3.90 score