Showing 34 of total 34 results (show query)
bioc
GenomicFeatures:Query the gene models of a given organism/assembly
Extract the genomic locations of genes, transcripts, exons, introns, and CDS, for the gene models stored in a TxDb object. A TxDb object is a small database that contains the gene models of a given organism/assembly. Bioconductor provides a small collection of TxDb objects in the form of ready-to-install TxDb packages for the most commonly studied organisms. Additionally, the user can easily make a TxDb object (or package) for the organism/assembly of their choice by using the tools from the txdbmaker package.
Maintained by H. Pagès. Last updated 4 months ago.
geneticsinfrastructureannotationsequencinggenomeannotationbioconductor-packagecore-package
32.8 match 26 stars 15.34 score 5.3k scripts 339 dependentsbioc
txdbmaker:Tools for making TxDb objects from genomic annotations
A set of tools for making TxDb objects from genomic annotations from various sources (e.g. UCSC, Ensembl, and GFF files). These tools allow the user to download the genomic locations of transcripts, exons, and CDS, for a given assembly, and to import them in a TxDb object. TxDb objects are implemented in the GenomicFeatures package, together with flexible methods for extracting the desired features in convenient formats.
Maintained by H. Pagès. Last updated 4 months ago.
infrastructuredataimportannotationgenomeannotationgenomeassemblygeneticssequencingbioconductor-packagecore-package
22.3 match 3 stars 9.70 score 92 scripts 86 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 28 days ago.
immunooncologysoftwaresequencingriboseqrnaseqfunctionalgenomicscoveragealignmentdataimportcpp
10.5 match 33 stars 10.63 score 115 scripts 2 dependents
blaserlab
TxDb.Drerio.UCSC.danRer11.ensGene:Annotation package for TxDb object(s)
Exposes an annotation databases generated from UCSC by exposing these as TxDb objects
Maintained by Brad Blaser. Last updated 2 years ago.
annotationdatageneticstxdbdanio_rerio
48.2 match 1.70 scorebioc
OrganismDbi:Software to enable the smooth interfacing of different database packages
The package enables a simple unified interface to several annotation packages each of which has its own schema by taking advantage of the fact that each of these packages implements a select methods.
Maintained by Bioconductor Package Maintainer. Last updated 5 months ago.
8.1 match 7.45 score 34 scripts 35 dependentsbioc
annotatr:Annotation of Genomic Regions to Genomic Annotations
Given a set of genomic sites/regions (e.g. ChIP-seq peaks, CpGs, differentially methylated CpGs or regions, SNPs, etc.) it is often of interest to investigate the intersecting genomic annotations. Such annotations include those relating to gene models (promoters, 5'UTRs, exons, introns, and 3'UTRs), CpGs (CpG islands, CpG shores, CpG shelves), or regulatory sequences such as enhancers. The annotatr package provides an easy way to summarize and visualize the intersection of genomic sites/regions with genomic annotations.
Maintained by Raymond G. Cavalcante. Last updated 5 months ago.
softwareannotationgenomeannotationfunctionalgenomicsvisualizationgenome-annotation
5.2 match 26 stars 9.76 score 246 scripts 5 dependentsbioc
crisprDesign:Comprehensive design of CRISPR gRNAs for nucleases and base editors
Provides a comprehensive suite of functions to design and annotate CRISPR guide RNA (gRNAs) sequences. This includes on- and off-target search, on-target efficiency scoring, off-target scoring, full gene and TSS contextual annotations, and SNP annotation (human only). It currently support five types of CRISPR modalities (modes of perturbations): CRISPR knockout, CRISPR activation, CRISPR inhibition, CRISPR base editing, and CRISPR knockdown. All types of CRISPR nucleases are supported, including DNA- and RNA-target nucleases such as Cas9, Cas12a, and Cas13d. All types of base editors are also supported. gRNA design can be performed on reference genomes, transcriptomes, and custom DNA and RNA sequences. Both unpaired and paired gRNA designs are enabled.
Maintained by Jean-Philippe Fortin. Last updated 12 days ago.
crisprfunctionalgenomicsgenetargetbioconductorbioconductor-packagecrispr-cas9crispr-designcrispr-targetgenomics-analysisgrnagrna-sequencegrna-sequencessgrnasgrna-design
5.5 match 22 stars 8.28 score 80 scripts 3 dependents
huanglabumn
oncoPredict:Drug Response Modeling and Biomarker Discovery
Allows for building drug response models using screening data between bulk RNA-Seq and a drug response metric and two additional tools for biomarker discovery that have been developed by the Huang Laboratory at University of Minnesota. There are 3 main functions within this package. (1) calcPhenotype is used to build drug response models on RNA-Seq data and impute them on any other RNA-Seq dataset given to the model. (2) GLDS is used to calculate the general level of drug sensitivity, which can improve biomarker discovery. (3) IDWAS can take the results from calcPhenotype and link the imputed response back to available genomic (mutation and CNV alterations) to identify biomarkers. Each of these functions comes from a paper from the Huang research laboratory. Below gives the relevant paper for each function. calcPhenotype - Geeleher et al, Clinical drug response can be predicted using baseline gene expression levels and in vitro drug sensitivity in cell lines. GLDS - Geeleher et al, Cancer biomarker discovery is improved by accounting for variability in general levels of drug sensitivity in pre-clinical models. IDWAS - Geeleher et al, Discovering novel pharmacogenomic biomarkers by imputing drug response in cancer patients from large genomics studies.
Maintained by Robert Gruener. Last updated 12 months ago.
svapreprocesscorestringrbiomartgenefilterorg.hs.eg.dbgenomicfeaturestxdb.hsapiens.ucsc.hg19.knowngenetcgabiolinksbiocgenericsgenomicrangesirangess4vectors
6.0 match 18 stars 6.47 score 41 scriptsbioc
trackViewer:A R/Bioconductor package with web interface for drawing elegant interactive tracks or lollipop plot to facilitate integrated analysis of multi-omics data
Visualize mapped reads along with annotation as track layers for NGS dataset such as ChIP-seq, RNA-seq, miRNA-seq, DNA-seq, SNPs and methylation data.
Maintained by Jianhong Ou. Last updated 2 months ago.
4.0 match 8.71 score 145 scripts 2 dependentsbioc
tximeta:Transcript Quantification Import with Automatic Metadata
Transcript quantification import from Salmon and other quantifiers with automatic attachment of transcript ranges and release information, and other associated metadata. De novo transcriptomes can be linked to the appropriate sources with linkedTxomes and shared for computational reproducibility.
Maintained by Michael Love. Last updated 2 months ago.
annotationgenomeannotationdataimportpreprocessingrnaseqsinglecelltranscriptomicstranscriptiongeneexpressionfunctionalgenomicsreproducibleresearchreportwritingimmunooncology
3.1 match 67 stars 10.58 score 466 scripts 1 dependentsbioc
InPAS:Identify Novel Alternative PolyAdenylation Sites (PAS) from RNA-seq data
Alternative polyadenylation (APA) is one of the important post- transcriptional regulation mechanisms which occurs in most human genes. InPAS facilitates the discovery of novel APA sites and the differential usage of APA sites from RNA-Seq data. It leverages cleanUpdTSeq to fine tune identified APA sites by removing false sites.
Maintained by Jianhong Ou. Last updated 2 months ago.
alternative polyadenylationdifferential polyadenylation site usagerna-seqgene regulationtranscription
7.1 match 4.30 score 1 scriptsbioc
compEpiTools:Tools for computational epigenomics
Tools for computational epigenomics developed for the analysis, integration and simultaneous visualization of various (epi)genomics data types across multiple genomic regions in multiple samples.
Maintained by Mattia Furlan. Last updated 5 months ago.
geneexpressionsequencingvisualizationgenomeannotationcoverage
6.9 match 4.30 score 6 scriptsbioc
GenomicPlot:Plot profiles of next generation sequencing data in genomic features
Visualization of next generation sequencing (NGS) data is essential for interpreting high-throughput genomics experiment results. 'GenomicPlot' facilitates plotting of NGS data in various formats (bam, bed, wig and bigwig); both coverage and enrichment over input can be computed and displayed with respect to genomic features (such as UTR, CDS, enhancer), and user defined genomic loci or regions. Statistical tests on signal intensity within user defined regions of interest can be performed and represented as boxplots or bar graphs. Parallel processing is used to speed up computation on multicore platforms. In addition to genomic plots which is suitable for displaying of coverage of genomic DNA (such as ChIPseq data), metagenomic (without introns) plots can also be made for RNAseq or CLIPseq data as well.
Maintained by Shuye Pu. Last updated 2 months ago.
alternativesplicingchipseqcoveragegeneexpressionrnaseqsequencingsoftwaretranscriptionvisualizationannotation
5.2 match 3 stars 5.62 score 4 scriptsbioc
BUSpaRse:kallisto | bustools R utilities
The kallisto | bustools pipeline is a fast and modular set of tools to convert single cell RNA-seq reads in fastq files into gene count or transcript compatibility counts (TCC) matrices for downstream analysis. Central to this pipeline is the barcode, UMI, and set (BUS) file format. This package serves the following purposes: First, this package allows users to manipulate BUS format files as data frames in R and then convert them into gene count or TCC matrices. Furthermore, since R and Rcpp code is easier to handle than pure C++ code, users are encouraged to tweak the source code of this package to experiment with new uses of BUS format and different ways to convert the BUS file into gene count matrix. Second, this package can conveniently generate files required to generate gene count matrices for spliced and unspliced transcripts for RNA velocity. Here biotypes can be filtered and scaffolds and haplotypes can be removed, and the filtered transcriptome can be extracted and written to disk. Third, this package implements utility functions to get transcripts and associated genes required to convert BUS files to gene count matrices, to write the transcript to gene information in the format required by bustools, and to read output of bustools into R as sparses matrices.
Maintained by Lambda Moses. Last updated 5 months ago.
singlecellrnaseqworkflowstepcpp
3.8 match 9 stars 7.35 score 165 scriptsbioc
txcutr:Transcriptome CUTteR
Various mRNA sequencing library preparation methods generate sequencing reads specifically from the transcript ends. Analyses that focus on quantification of isoform usage from such data can be aided by using truncated versions of transcriptome annotations, both at the alignment or pseudo-alignment stage, as well as in downstream analysis. This package implements some convenience methods for readily generating such truncated annotations and their corresponding sequences.
Maintained by Mervin Fansler. Last updated 5 months ago.
alignmentannotationrnaseqsequencingtranscriptomics
6.0 match 4.30 score 9 scriptsbioc
Organism.dplyr:dplyr-based Access to Bioconductor Annotation Resources
This package provides an alternative interface to Bioconductor 'annotation' resources, in particular the gene identifier mapping functionality of the 'org' packages (e.g., org.Hs.eg.db) and the genome coordinate functionality of the 'TxDb' packages (e.g., TxDb.Hsapiens.UCSC.hg38.knownGene).
Maintained by Martin Morgan. Last updated 5 months ago.
annotationsequencinggenomeannotationbioconductor-packagecore-package
3.7 match 3 stars 6.77 score 63 scripts 1 dependentsbioc
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
1.9 match 53 stars 11.56 score 344 scripts 3 dependentsbioc
wiggleplotr:Make read coverage plots from BigWig files
Tools to visualise read coverage from sequencing experiments together with genomic annotations (genes, transcripts, peaks). Introns of long transcripts can be rescaled to a fixed length for better visualisation of exonic read coverage.
Maintained by Kaur Alasoo. Last updated 5 months ago.
immunooncologycoveragernaseqchipseqsequencingvisualizationgeneexpressiontranscriptionalternativesplicing
3.4 match 5.97 score 26 scripts 3 dependentsbioc
plotgardener:Coordinate-Based Genomic Visualization Package for R
Coordinate-based genomic visualization package for R. It grants users the ability to programmatically produce complex, multi-paneled figures. Tailored for genomics, plotgardener allows users to visualize large complex genomic datasets and provides exquisite control over how plots are placed and arranged on a page.
Maintained by Nicole Kramer. Last updated 5 months ago.
visualizationgenomeannotationfunctionalgenomicsgenomeassemblyhiccpp
1.7 match 308 stars 10.16 score 167 scripts 3 dependentsbioc
AnnotationHub:Client to access AnnotationHub resources
This package provides a client for the Bioconductor AnnotationHub web resource. The AnnotationHub web resource provides a central location where genomic files (e.g., VCF, bed, wig) and other resources from standard locations (e.g., UCSC, Ensembl) can be discovered. The resource includes metadata about each resource, e.g., a textual description, tags, and date of modification. The client creates and manages a local cache of files retrieved by the user, helping with quick and reproducible access.
Maintained by Bioconductor Package Maintainer. Last updated 5 months ago.
infrastructuredataimportguithirdpartyclientcore-packageu24ca289073
1.1 match 17 stars 13.89 score 2.7k scripts 102 dependentsbioc
CAGEfightR:Analysis of Cap Analysis of Gene Expression (CAGE) data using Bioconductor
CAGE is a widely used high throughput assay for measuring transcription start site (TSS) activity. CAGEfightR is an R/Bioconductor package for performing a wide range of common data analysis tasks for CAGE and 5'-end data in general. Core functionality includes: import of CAGE TSSs (CTSSs), tag (or unidirectional) clustering for TSS identification, bidirectional clustering for enhancer identification, annotation with transcript and gene models, correlation of TSS and enhancer expression, calculation of TSS shapes, quantification of CAGE expression as expression matrices and genome brower visualization.
Maintained by Malte Thodberg. Last updated 5 months ago.
softwaretranscriptioncoveragegeneexpressiongeneregulationpeakdetectiondataimportdatarepresentationtranscriptomicssequencingannotationgenomebrowsersnormalizationpreprocessingvisualization
1.8 match 8 stars 7.46 score 67 scripts 1 dependentsbioc
proActiv:Estimate Promoter Activity from RNA-Seq data
Most human genes have multiple promoters that control the expression of different isoforms. The use of these alternative promoters enables the regulation of isoform expression pre-transcriptionally. Alternative promoters have been found to be important in a wide number of cell types and diseases. proActiv is an R package that enables the analysis of promoters from RNA-seq data. proActiv uses aligned reads as input, and generates counts and normalized promoter activity estimates for each annotated promoter. In particular, proActiv accepts junction files from TopHat2 or STAR or BAM files as inputs. These estimates can then be used to identify which promoter is active, which promoter is inactive, and which promoters change their activity across conditions. proActiv also allows visualization of promoter activity across conditions.
Maintained by Joseph Lee. Last updated 5 months ago.
rnaseqgeneexpressiontranscriptionalternativesplicinggeneregulationdifferentialsplicingfunctionalgenomicsepigeneticstranscriptomicspreprocessingalternative-promotersgenomicspromoter-activitypromoter-annotationrna-seq-data
1.8 match 51 stars 6.66 score 15 scriptsbioc
bambu:Context-Aware Transcript Quantification from Long Read RNA-Seq data
bambu is a R package for multi-sample transcript discovery and quantification using long read RNA-Seq data. You can use bambu after read alignment to obtain expression estimates for known and novel transcripts and genes. The output from bambu can directly be used for visualisation and downstream analysis such as differential gene expression or transcript usage.
Maintained by Ying Chen. Last updated 1 months ago.
alignmentcoveragedifferentialexpressionfeatureextractiongeneexpressiongenomeannotationgenomeassemblyimmunooncologylongreadmultiplecomparisonnormalizationrnaseqregressionsequencingsoftwaretranscriptiontranscriptomicsbambubioconductorlong-readsnanoporenanopore-sequencingrna-seqrna-seq-analysistranscript-quantificationtranscript-reconstructioncpp
1.1 match 197 stars 9.03 score 91 scripts 1 dependentsbioc
ProteoDisco:Generation of customized protein variant databases from genomic variants, splice-junctions and manual sequences
ProteoDisco is an R package to facilitate proteogenomics studies. It houses functions to create customized (variant) protein databases based on user-submitted genomic variants, splice-junctions, fusion genes and manual transcript sequences. The flexible workflow can be adopted to suit a myriad of research and experimental settings.
Maintained by Job van Riet. Last updated 5 months ago.
softwareproteomicsrnaseqsnpsequencingvariantannotationdataimport
1.8 match 5 stars 5.30 score 4 scriptsbioc
scanMiRApp:scanMiR shiny application
A shiny interface to the scanMiR package. The application enables the scanning of transcripts and custom sequences for miRNA binding sites, the visualization of KdModels and binding results, as well as browsing predicted repression data. In addition contains the IndexedFst class for fast indexed reading of large GenomicRanges or data.frames, and some utilities for facilitating scans and identifying enriched miRNA-target pairs.
Maintained by Pierre-Luc Germain. Last updated 5 months ago.
mirnasequencematchingguishinyapps
1.9 match 4.88 score 19 scriptsbioc
AnnotationHubData:Transform public data resources into Bioconductor Data Structures
These recipes convert a wide variety and a growing number of public bioinformatic data sets into easily-used standard Bioconductor data structures.
Maintained by Bioconductor Package Maintainer. Last updated 6 days ago.
1.7 match 5.02 score 22 scripts 4 dependentsbioc
IVAS:Identification of genetic Variants affecting Alternative Splicing
Identification of genetic variants affecting alternative splicing.
Maintained by Seonggyun Han. Last updated 5 months ago.
immunooncologyalternativesplicingdifferentialexpressiondifferentialsplicinggeneexpressiongeneregulationregressionrnaseqsequencingsnpsoftwaretranscription
1.8 match 4.78 score 1 scripts 1 dependentsbioc
Damsel:Damsel: an end to end analysis of DamID
Damsel provides an end to end analysis of DamID data. Damsel takes bam files from Dam-only control and fusion samples and counts the reads matching to each GATC region. edgeR is utilised to identify regions of enrichment in the fusion relative to the control. Enriched regions are combined into peaks, and are associated with nearby genes. Damsel allows for IGV style plots to be built as the results build, inspired by ggcoverage, and using the functionality and layering ability of ggplot2. Damsel also conducts gene ontology testing with bias correction through goseq, and future versions of Damsel will also incorporate motif enrichment analysis. Overall, Damsel is the first package allowing for an end to end analysis with visual capabilities. The goal of Damsel was to bring all the analysis into one place, and allow for exploratory analysis within R.
Maintained by Caitlin Page. Last updated 5 months ago.
differentialmethylationpeakdetectiongenepredictiongenesetenrichment
1.5 match 5.34 score 20 scriptsbioc
ensembldb:Utilities to create and use Ensembl-based annotation databases
The package provides functions to create and use transcript centric annotation databases/packages. The annotation for the databases are directly fetched from Ensembl using their Perl API. The functionality and data is similar to that of the TxDb packages from the GenomicFeatures package, but, in addition to retrieve all gene/transcript models and annotations from the database, ensembldb provides a filter framework allowing to retrieve annotations for specific entries like genes encoded on a chromosome region or transcript models of lincRNA genes. EnsDb databases built with ensembldb contain also protein annotations and mappings between proteins and their encoding transcripts. Finally, ensembldb provides functions to map between genomic, transcript and protein coordinates.
Maintained by Johannes Rainer. Last updated 5 months ago.
geneticsannotationdatasequencingcoverageannotationbioconductorbioconductor-packagesensembl
0.5 match 35 stars 14.08 score 892 scripts 108 dependentsbioc
BiocFileCache:Manage Files Across Sessions
This package creates a persistent on-disk cache of files that the user can add, update, and retrieve. It is useful for managing resources (such as custom Txdb objects) that are costly or difficult to create, web resources, and data files used across sessions.
Maintained by Lori Shepherd. Last updated 2 months ago.
dataimportcore-packageu24ca289073
0.5 match 13 stars 13.76 score 486 scripts 429 dependentsbioc
tidyCoverage:Extract and aggregate genomic coverage over features of interest
`tidyCoverage` framework enables tidy manipulation of collections of genomic tracks and features using `tidySummarizedExperiment` methods. It facilitates the extraction, aggregation and visualization of genomic coverage over individual or thousands of genomic loci, relying on `CoverageExperiment` and `AggregatedCoverage` classes. This accelerates the integration of genomic track data in genomic analysis workflows.
Maintained by Jacques Serizay. Last updated 5 months ago.
1.2 match 21 stars 5.80 score 6 scriptsbioc
DominoEffect:Identification and Annotation of Protein Hotspot Residues
The functions support identification and annotation of hotspot residues in proteins. These are individual amino acids that accumulate mutations at a much higher rate than their surrounding regions.
Maintained by Marija Buljan. Last updated 5 months ago.
softwaresomaticmutationproteomicssequencematchingalignment
1.7 match 3.48 score 1 scripts
