Showing 31 of total 31 results (show query)
bioc
GenomicRanges:Representation and manipulation of genomic intervals
The ability to efficiently represent and manipulate genomic annotations and alignments is playing a central role when it comes to analyzing high-throughput sequencing data (a.k.a. NGS data). The GenomicRanges package defines general purpose containers for storing and manipulating genomic intervals and variables defined along a genome. More specialized containers for representing and manipulating short alignments against a reference genome, or a matrix-like summarization of an experiment, are defined in the GenomicAlignments and SummarizedExperiment packages, respectively. Both packages build on top of the GenomicRanges infrastructure.
Maintained by Hervé Pagès. Last updated 4 months ago.
geneticsinfrastructuredatarepresentationsequencingannotationgenomeannotationcoveragebioconductor-packagecore-package
72.6 match 44 stars 17.75 score 13k scripts 1.3k 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
10.0 match 18 stars 6.47 score 41 scriptsbioc
multiHiCcompare:Normalize and detect differences between Hi-C datasets when replicates of each experimental condition are available
multiHiCcompare provides functions for joint normalization and difference detection in multiple Hi-C datasets. This extension of the original HiCcompare package now allows for Hi-C experiments with more than 2 groups and multiple samples per group. multiHiCcompare operates on processed Hi-C data in the form of sparse upper triangular matrices. It accepts four column (chromosome, region1, region2, IF) tab-separated text files storing chromatin interaction matrices. multiHiCcompare provides cyclic loess and fast loess (fastlo) methods adapted to jointly normalizing Hi-C data. Additionally, it provides a general linear model (GLM) framework adapting the edgeR package to detect differences in Hi-C data in a distance dependent manner.
Maintained by Mikhail Dozmorov. Last updated 5 months ago.
softwarehicsequencingnormalization
6.9 match 9 stars 7.30 score 37 scripts 2 dependentsbioc
plyranges:A fluent interface for manipulating GenomicRanges
A dplyr-like interface for interacting with the common Bioconductor classes Ranges and GenomicRanges. By providing a grammatical and consistent way of manipulating these classes their accessiblity for new Bioconductor users is hopefully increased.
Maintained by Michael Love. Last updated 5 months ago.
infrastructuredatarepresentationworkflowstepcoveragebioconductordata-analysisdplyrgenomic-rangesgenomicstidy-data
3.6 match 143 stars 12.60 score 1.9k scripts 20 dependentsbioc
genomation:Summary, annotation and visualization of genomic data
A package for summary and annotation of genomic intervals. Users can visualize and quantify genomic intervals over pre-defined functional regions, such as promoters, exons, introns, etc. The genomic intervals represent regions with a defined chromosome position, which may be associated with a score, such as aligned reads from HT-seq experiments, TF binding sites, methylation scores, etc. The package can use any tabular genomic feature data as long as it has minimal information on the locations of genomic intervals. In addition, It can use BAM or BigWig files as input.
Maintained by Altuna Akalin. Last updated 5 months ago.
annotationsequencingvisualizationcpgislandcpp
2.6 match 75 stars 11.09 score 738 scripts 5 dependentsbioc
GenomicDistributions:GenomicDistributions: fast analysis of genomic intervals with Bioconductor
If you have a set of genomic ranges, this package can help you with visualization and comparison. It produces several kinds of plots, for example: Chromosome distribution plots, which visualize how your regions are distributed over chromosomes; feature distance distribution plots, which visualizes how your regions are distributed relative to a feature of interest, like Transcription Start Sites (TSSs); genomic partition plots, which visualize how your regions overlap given genomic features such as promoters, introns, exons, or intergenic regions. It also makes it easy to compare one set of ranges to another.
Maintained by Kristyna Kupkova. Last updated 5 months ago.
softwaregenomeannotationgenomeassemblydatarepresentationsequencingcoveragefunctionalgenomicsvisualization
3.5 match 26 stars 7.44 score 25 scriptsbioc
oncoscanR:Secondary analyses of CNV data (HRD and more)
The software uses the copy number segments from a text file and identifies all chromosome arms that are globally altered and computes various genome-wide scores. The following HRD scores (characteristic of BRCA-mutated cancers) are included: LST, HR-LOH, nLST and gLOH. the package is tailored for the ThermoFisher Oncoscan assay analyzed with their Chromosome Alteration Suite (ChAS) but can be adapted to any input.
Maintained by Yann Christinat. Last updated 5 months ago.
copynumbervariationmicroarraysoftware
4.9 match 2 stars 4.60 score 6 scriptsbioc
OGRE:Calculate, visualize and analyse overlap between genomic regions
OGRE calculates overlap between user defined genomic region datasets. Any regions can be supplied i.e. genes, SNPs, or reads from sequencing experiments. Key numbers help analyse the extend of overlaps which can also be visualized at a genomic level.
Maintained by Sven Berres. Last updated 5 months ago.
softwareworkflowstepbiologicalquestionannotationmetagenomicsvisualizationsequencing
4.6 match 2 stars 4.60 score 4 scriptsbioc
MultiAssayExperiment:Software for the integration of multi-omics experiments in Bioconductor
Harmonize data management of multiple experimental assays performed on an overlapping set of specimens. It provides a familiar Bioconductor user experience by extending concepts from SummarizedExperiment, supporting an open-ended mix of standard data classes for individual assays, and allowing subsetting by genomic ranges or rownames. Facilities are provided for reshaping data into wide and long formats for adaptability to graphing and downstream analysis.
Maintained by Marcel Ramos. Last updated 2 months ago.
infrastructuredatarepresentationbioconductorbioconductor-packagegenomicsnci-itcrtcgau24ca289073
1.3 match 71 stars 14.95 score 670 scripts 127 dependentsbioc
MouseFM:In-silico methods for genetic finemapping in inbred mice
This package provides methods for genetic finemapping in inbred mice by taking advantage of their very high homozygosity rate (>95%).
Maintained by Matthias Munz. Last updated 5 months ago.
geneticssnpgenetargetvariantannotationgenomicvariationmultiplecomparisonsystemsbiologymathematicalbiologypatternlogicgenepredictionbiomedicalinformaticsfunctionalgenomicsfinemapgene-candidatesinbred-miceinbred-strainsmouseqtlqtl-mapping
3.6 match 5.13 score 5 scriptsbioc
scPipe:Pipeline for single cell multi-omic data pre-processing
A preprocessing pipeline for single cell RNA-seq/ATAC-seq data that starts from the fastq files and produces a feature count matrix with associated quality control information. It can process fastq data generated by CEL-seq, MARS-seq, Drop-seq, Chromium 10x and SMART-seq protocols.
Maintained by Shian Su. Last updated 3 months ago.
immunooncologysoftwaresequencingrnaseqgeneexpressionsinglecellvisualizationsequencematchingpreprocessingqualitycontrolgenomeannotationdataimportcurlbzip2xz-utilszlibcpp
1.7 match 68 stars 9.02 score 84 scriptsbioc
crisprShiny:Exploring curated CRISPR gRNAs via Shiny
Provides means to interactively visualize guide RNAs (gRNAs) in GuideSet objects via Shiny application. This GUI can be self-contained or as a module within a larger Shiny app. The content of the app reflects the annotations present in the passed GuideSet object, and includes intuitive tools to examine, filter, and export gRNAs, thereby making gRNA design more user-friendly.
Maintained by Jean-Philippe Fortin. Last updated 5 months ago.
crisprfunctionalgenomicsgenetargetguicrispr-analysiscrispr-designshiny
3.3 match 2 stars 4.48 score 8 scriptsbioc
biovizBase:Basic graphic utilities for visualization of genomic data.
The biovizBase package is designed to provide a set of utilities, color schemes and conventions for genomic data. It serves as the base for various high-level packages for biological data visualization. This saves development effort and encourages consistency.
Maintained by Michael Lawrence. Last updated 5 months ago.
infrastructurevisualizationpreprocessing
1.8 match 8.04 score 273 scripts 75 dependentsbioc
MultiDataSet:Implementation of MultiDataSet and ResultSet
Implementation of the BRGE's (Bioinformatic Research Group in Epidemiology from Center for Research in Environmental Epidemiology) MultiDataSet and ResultSet. MultiDataSet is designed for integrating multi omics data sets and ResultSet is a container for omics results. This package contains base classes for MEAL and rexposome packages.
Maintained by Xavier Escribà Montagut. Last updated 5 months ago.
2.0 match 6.48 score 28 scripts 10 dependentsbioc
AlphaMissenseR:Accessing AlphaMissense Data Resources in R
The AlphaMissense publication <https://www.science.org/doi/epdf/10.1126/science.adg7492> outlines how a variant of AlphaFold / DeepMind was used to predict missense variant pathogenicity. Supporting data on Zenodo <https://zenodo.org/record/10813168> include, for instance, 71M variants across hg19 and hg38 genome builds. The 'AlphaMissenseR' package allows ready access to the data, downloading individual files to DuckDB databases for exploration and integration into *R* and *Bioconductor* workflows.
Maintained by Martin Morgan. Last updated 5 months ago.
snpannotationfunctionalgenomicsstructuralpredictiontranscriptomicsvariantannotationgenepredictionimmunooncology
1.8 match 8 stars 6.86 score 10 scriptsbioc
GenomicFiles:Distributed computing by file or by range
This package provides infrastructure for parallel computations distributed 'by file' or 'by range'. User defined MAPPER and REDUCER functions provide added flexibility for data combination and manipulation.
Maintained by Bioconductor Package Maintainer. Last updated 5 months ago.
geneticsinfrastructuredataimportsequencingcoverage
1.7 match 6.86 score 89 scripts 16 dependentsbioc
easyRNASeq:Count summarization and normalization for RNA-Seq data
Calculates the coverage of high-throughput short-reads against a genome of reference and summarizes it per feature of interest (e.g. exon, gene, transcript). The data can be normalized as 'RPKM' or by the 'DESeq' or 'edgeR' package.
Maintained by Nicolas Delhomme. Last updated 5 months ago.
geneexpressionrnaseqgeneticspreprocessingimmunooncology
2.0 match 5.43 score 15 scripts 1 dependents
yeyuan98
gsAnalysis:Miscellaneous tools for genomic sequence analysis
A miscellaneous toolbox for various genomic sequence analysis tasks. Refer to package vignettes for different topics covered in this package. Part of the y3628 analysis suite.
Maintained by Ye Yuan. Last updated 2 months ago.
3.7 match 2.70 score 1 scriptsbioc
ChromSCape:Analysis of single-cell epigenomics datasets with a Shiny App
ChromSCape - Chromatin landscape profiling for Single Cells - is a ready-to-launch user-friendly Shiny Application for the analysis of single-cell epigenomics datasets (scChIP-seq, scATAC-seq, scCUT&Tag, ...) from aligned data to differential analysis & gene set enrichment analysis. It is highly interactive, enables users to save their analysis and covers a wide range of analytical steps: QC, preprocessing, filtering, batch correction, dimensionality reduction, vizualisation, clustering, differential analysis and gene set analysis.
Maintained by Pacome Prompsy. Last updated 5 months ago.
shinyappssoftwaresinglecellchipseqatacseqmethylseqclassificationclusteringepigeneticsprincipalcomponentannotationbatcheffectmultiplecomparisonnormalizationpathwayspreprocessingqualitycontrolreportwritingvisualizationgenesetenrichmentdifferentialpeakcallingepigenomicsshinysingle-cellcpp
1.6 match 14 stars 5.83 score 16 scriptsbioc
regutools:regutools: an R package for data extraction from RegulonDB
RegulonDB has collected, harmonized and centralized data from hundreds of experiments for nearly two decades and is considered a point of reference for transcriptional regulation in Escherichia coli K12. Here, we present the regutools R package to facilitate programmatic access to RegulonDB data in computational biology. regutools provides researchers with the possibility of writing reproducible workflows with automated queries to RegulonDB. The regutools package serves as a bridge between RegulonDB data and the Bioconductor ecosystem by reusing the data structures and statistical methods powered by other Bioconductor packages. We demonstrate the integration of regutools with Bioconductor by analyzing transcription factor DNA binding sites and transcriptional regulatory networks from RegulonDB. We anticipate that regutools will serve as a useful building block in our progress to further our understanding of gene regulatory networks.
Maintained by Joselyn Chavez. Last updated 3 months ago.
generegulationgeneexpressionsystemsbiologynetworknetworkinferencevisualizationtranscriptionbioconductorcdsbregulondb
1.7 match 4 stars 5.20 score 6 scriptsbioc
groHMM:GRO-seq Analysis Pipeline
A pipeline for the analysis of GRO-seq data.
Maintained by Tulip Nandu. Last updated 2 days ago.
1.7 match 1 stars 4.48 score 25 scriptsbioc
factR:Functional Annotation of Custom Transcriptomes
factR contain tools to process and interact with custom-assembled transcriptomes (GTF). At its core, factR constructs CDS information on custom transcripts and subsequently predicts its functional output. In addition, factR has tools capable of plotting transcripts, correcting chromosome and gene information and shortlisting new transcripts.
Maintained by Fursham Hamid. Last updated 5 months ago.
alternativesplicingfunctionalpredictiongenepredictioncustom-transcriptomesfunctional-annotationgtfrna-seq-analysis
1.8 match 1 stars 4.00 score 5 scriptsyeyuan98
Rabe:Adenine base editor analysis
Base editors are emerging molecular sensors for protein-RNA interaction. This package implements a workflow for analysis of adenine base editor datasets. With minimal adjustment it can be used for systematic inquiry of any known single base-pair mutagenesis patterns. Part of the y3628 analysis suite.
Maintained by Ye Yuan. Last updated 7 months ago.
3.4 match 2.00 score 1 scriptsbioc
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
0.5 match 33 stars 10.63 score 115 scripts 2 dependentsbioc
Rmmquant:RNA-Seq multi-mapping Reads Quantification Tool
RNA-Seq is currently used routinely, and it provides accurate information on gene transcription. However, the method cannot accurately estimate duplicated genes expression. Several strategies have been previously used, but all of them provide biased results. With Rmmquant, if a read maps at different positions, the tool detects that the corresponding genes are duplicated; it merges the genes and creates a merged gene. The counts of ambiguous reads is then based on the input genes and the merged genes. Rmmquant is a drop-in replacement of the widely used tools findOverlaps and featureCounts that handles multi-mapping reads in an unabiased way.
Maintained by Zytnicki Matthias. Last updated 5 months ago.
geneexpressiontranscriptionzlibcpp
1.3 match 3.30 score 5 scriptsbioc
alabaster.ranges:Load and Save Ranges-related Artifacts from File
Save GenomicRanges, IRanges and related data structures into file artifacts, and load them back into memory. This is a more portable alternative to serialization of such objects into RDS files. Each artifact is associated with metadata for further interpretation; downstream applications can enrich this metadata with context-specific properties.
Maintained by Aaron Lun. Last updated 5 months ago.
0.5 match 6.38 score 8 scripts 8 dependentsbioc
GenomicTuples:Representation and Manipulation of Genomic Tuples
GenomicTuples defines general purpose containers for storing genomic tuples. It aims to provide functionality for tuples of genomic co-ordinates that are analogous to those available for genomic ranges in the GenomicRanges Bioconductor package.
Maintained by Peter Hickey. Last updated 4 months ago.
infrastructuredatarepresentationsequencingcpp
0.5 match 4 stars 5.48 score 7 scriptsbioc
epivizr:R Interface to epiviz web app
This package provides connections to the epiviz web app (http://epiviz.cbcb.umd.edu) for interactive visualization of genomic data. Objects in R/bioc interactive sessions can be displayed in genome browser tracks or plots to be explored by navigation through genomic regions. Fundamental Bioconductor data structures are supported (e.g., GenomicRanges and RangedSummarizedExperiment objects), while providing an easy mechanism to support other data structures (through package epivizrData). Visualizations (using d3.js) can be easily added to the web app as well.
Maintained by Hector Corrada Bravo. Last updated 5 months ago.
visualizationinfrastructuregui
0.5 match 5.24 score 29 scripts 2 dependentsbioc
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
0.5 match 4.88 score 19 scriptsbioc
chromDraw:chromDraw is a R package for drawing the schemes of karyotypes in the linear and circular fashion.
ChromDraw is a R package for drawing the schemes of karyotype(s) in the linear and circular fashion. It is possible to visualized cytogenetic marsk on the chromosomes. This tool has own input data format. Input data can be imported from the GenomicRanges data structure. This package can visualized the data in the BED file format. Here is requirement on to the first nine fields of the BED format. Output files format are *.eps and *.svg.
Maintained by Jan Janecka. Last updated 5 months ago.
0.5 match 3.30 score 1 scripts
mbeer3
gkmSVM:Gapped-Kmer Support Vector Machine
Imports the 'gkmSVM' v2.0 functionalities into R <https://www.beerlab.org/gkmsvm/> It also uses the 'kernlab' library (separate R package by different authors) for various SVM algorithms. Users should note that the suggested packages 'rtracklayer', 'GenomicRanges', 'BSgenome', 'BiocGenerics', 'Biostrings', 'GenomeInfoDb', 'IRanges', and 'S4Vectors' are all BioConductor packages <https://bioconductor.org>.
Maintained by Mike Beer. Last updated 2 years ago.
0.5 match 2.48 score 30 scripts