R-universe search: txdb.hsapiens.ucsc.hg19.knowngene

bioc

UCSC.utils:Low-level utilities to retrieve data from the UCSC Genome Browser

A set of low-level utilities to retrieve data from the UCSC Genome Browser. Most functions in the package access the data via the UCSC REST API but some of them query the UCSC MySQL server directly. Note that the primary purpose of the package is to support higher-level functionalities implemented in downstream packages like GenomeInfoDb or txdbmaker.

Maintained by Hervé Pagès. Last updated 2 months ago.

infrastructure genomeassembly annotation genomeannotation dataimport bioconductor-package core-package

57.6 match 1 stars 10.09 score 4 scripts 1.7k dependents

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.

genetics infrastructure annotation sequencing genomeannotation bioconductor-package core-package

37.7 match 26 stars 15.34 score 5.3k scripts 339 dependents

ropensci

UCSCXenaTools:Download and Explore Datasets from UCSC Xena Data Hubs

Download and explore datasets from UCSC Xena data hubs, which are a collection of UCSC-hosted public databases such as TCGA, ICGC, TARGET, GTEx, CCLE, and others. Databases are normalized so they can be combined, linked, filtered, explored and downloaded.

Maintained by Shixiang Wang. Last updated 5 months ago.

api-client bioinformatics ccle downloader icgc tcga toil treehouse ucsc ucsc-xena

33.6 match 106 stars 8.55 score 163 scripts 1 dependents

bioc

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.

infrastructure dataimport annotation genomeannotation genomeassembly genetics sequencing bioconductor-package core-package

27.8 match 3 stars 9.70 score 92 scripts 86 dependents

bioc

rtracklayer:R interface to genome annotation files and the UCSC genome browser

Extensible framework for interacting with multiple genome browsers (currently UCSC built-in) and manipulating annotation tracks in various formats (currently GFF, BED, bedGraph, BED15, WIG, BigWig and 2bit built-in). The user may export/import tracks to/from the supported browsers, as well as query and modify the browser state, such as the current viewport.

Maintained by Michael Lawrence. Last updated 8 days ago.

annotation visualization dataimport zlib openssl curl

15.8 match 12.66 score 6.7k scripts 481 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.

sva preprocesscore stringr biomart genefilter org.hs.eg.db genomicfeatures txdb.hsapiens.ucsc.hg19.knowngene tcgabiolinks biocgenerics genomicranges iranges s4vectors

30.0 match 18 stars 6.47 score 41 scripts

shixiangwang

sigminer:Extract, Analyze and Visualize Mutational Signatures for Genomic Variations

Genomic alterations including single nucleotide substitution, copy number alteration, etc. are the major force for cancer initialization and development. Due to the specificity of molecular lesions caused by genomic alterations, we can generate characteristic alteration spectra, called 'signature' (Wang, Shixiang, et al. (2021) <DOI:10.1371/journal.pgen.1009557> & Alexandrov, Ludmil B., et al. (2020) <DOI:10.1038/s41586-020-1943-3> & Steele Christopher D., et al. (2022) <DOI:10.1038/s41586-022-04738-6>). This package helps users to extract, analyze and visualize signatures from genomic alteration records, thus providing new insight into cancer study.

Maintained by Shixiang Wang. Last updated 5 months ago.

bayesian-nmf bioinformatics cancer-research cnv copynumber-signatures cosmic-signatures dbs easy-to-use indel mutational-signatures nmf nmf-extraction sbs signature-extraction somatic-mutations somatic-variants visualization cpp

15.9 match 150 stars 9.48 score 123 scripts 2 dependents

openbiox

UCSCXenaShiny:Interactive Analysis of UCSC Xena Data

Provides functions and a Shiny application for downloading, analyzing and visualizing datasets from UCSC Xena (<http://xena.ucsc.edu/>), which is a collection of UCSC-hosted public databases such as TCGA, ICGC, TARGET, GTEx, CCLE, and others.

Maintained by Shixiang Wang. Last updated 4 months ago.

cancer-dataset shiny-apps ucsc-xena

16.6 match 96 stars 8.54 score 35 scripts

bioc

derfinder:Annotation-agnostic differential expression analysis of RNA-seq data at base-pair resolution via the DER Finder approach

This package provides functions for annotation-agnostic differential expression analysis of RNA-seq data. Two implementations of the DER Finder approach are included in this package: (1) single base-level F-statistics and (2) DER identification at the expressed regions-level. The DER Finder approach can also be used to identify differentially bounded ChIP-seq peaks.

Maintained by Leonardo Collado-Torres. Last updated 3 months ago.

differentialexpression sequencing rnaseq chipseq differentialpeakcalling software immunooncology coverage annotation-agnostic bioconductor derfinder

14.0 match 42 stars 10.03 score 78 scripts 6 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.

annotationdata genetics txdb danio_rerio

80.5 match 1.70 score

bioc

biscuiteer:Convenience Functions for Biscuit

A test harness for bsseq loading of Biscuit output, summarization of WGBS data over defined regions and in mappable samples, with or without imputation, dropping of mostly-NA rows, age estimates, etc.

Maintained by Jacob Morrison. Last updated 5 months ago.

dataimport methylseq dnamethylation

21.8 match 6 stars 6.16 score 16 scripts

bioc

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.

immunooncology software sequencing riboseq rnaseq functionalgenomics coverage alignment dataimport cpp

11.7 match 33 stars 10.63 score 115 scripts 2 dependents

kharchenkolab

numbat:Haplotype-Aware CNV Analysis from scRNA-Seq

A computational method that infers copy number variations (CNVs) in cancer scRNA-seq data and reconstructs the tumor phylogeny. 'numbat' integrates signals from gene expression, allelic ratio, and population haplotype structures to accurately infer allele-specific CNVs in single cells and reconstruct their lineage relationship. 'numbat' can be used to: 1. detect allele-specific copy number variations from single-cells; 2. differentiate tumor versus normal cells in the tumor microenvironment; 3. infer the clonal architecture and evolutionary history of profiled tumors. 'numbat' does not require tumor/normal-paired DNA or genotype data, but operates solely on the donor scRNA-data data (for example, 10x Cell Ranger output). Additional examples and documentations are available at <https://kharchenkolab.github.io/numbat/>. For details on the method please see Gao et al. Nature Biotechnology (2022) <doi:10.1038/s41587-022-01468-y>.

Maintained by Teng Gao. Last updated 16 days ago.

cancer-genomics cnv-detection lineage-tracing phylogeny single-cell single-cell-analysis single-cell-rna-seq spatial-transcriptomics cpp

15.8 match 179 stars 7.41 score 120 scripts

bioc

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.

software annotation genomeannotation functionalgenomics visualization genome-annotation

10.3 match 26 stars 9.76 score 246 scripts 5 dependents

bioc

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.

software genomeannotation genomeassembly datarepresentation sequencing coverage functionalgenomics visualization

12.9 match 26 stars 7.44 score 25 scripts

bioc

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.

infrastructure visualization preprocessing

10.9 match 8.04 score 273 scripts 75 dependents

bioc

coMET:coMET: visualisation of regional epigenome-wide association scan (EWAS) results and DNA co-methylation patterns

Visualisation of EWAS results in a genomic region. In addition to phenotype-association P-values, coMET also generates plots of co-methylation patterns and provides a series of annotation tracks. It can be used to other omic-wide association scans as lon:g as the data can be translated to genomic level and for any species.

Maintained by Tiphaine Martin. Last updated 2 days ago.

software differentialmethylation visualization sequencing genetics functionalgenomics microarray methylationarray methylseq chipseq dnaseq riboseq rnaseq exomeseq dnamethylation genomewideassociation motifannotation

19.0 match 4.41 score 17 scripts

jokergoo

circlize:Circular Visualization

Circular layout is an efficient way for the visualization of huge amounts of information. Here this package provides an implementation of circular layout generation in R as well as an enhancement of available software. The flexibility of the package is based on the usage of low-level graphics functions such that self-defined high-level graphics can be easily implemented by users for specific purposes. Together with the seamless connection between the powerful computational and visual environment in R, it gives users more convenience and freedom to design figures for better understanding complex patterns behind multiple dimensional data. The package is described in Gu et al. 2014 <doi:10.1093/bioinformatics/btu393>.

Maintained by Zuguang Gu. Last updated 1 years ago.

5.0 match 983 stars 15.62 score 10k scripts 213 dependents

bioc

TCGAbiolinks:TCGAbiolinks: An R/Bioconductor package for integrative analysis with GDC data

The aim of TCGAbiolinks is : i) facilitate the GDC open-access data retrieval, ii) prepare the data using the appropriate pre-processing strategies, iii) provide the means to carry out different standard analyses and iv) to easily reproduce earlier research results. In more detail, the package provides multiple methods for analysis (e.g., differential expression analysis, identifying differentially methylated regions) and methods for visualization (e.g., survival plots, volcano plots, starburst plots) in order to easily develop complete analysis pipelines.

Maintained by Tiago Chedraoui Silva. Last updated 27 days ago.

dnamethylation differentialmethylation generegulation geneexpression methylationarray differentialexpression pathways network sequencing survival software bioc bioconductor gdc integrative-analysis tcga tcga-data tcgabiolinks

5.0 match 305 stars 14.45 score 1.6k scripts 6 dependents

bioc

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.

annotation infrastructure

9.7 match 7.45 score 34 scripts 35 dependents

bioc

HiCcompare:HiCcompare: Joint normalization and comparative analysis of multiple Hi-C datasets

HiCcompare provides functions for joint normalization and difference detection in multiple Hi-C datasets. HiCcompare operates on processed Hi-C data in the form of chromosome-specific chromatin interaction matrices. It accepts three-column tab-separated text files storing chromatin interaction matrices in a sparse matrix format which are available from several sources. HiCcompare is designed to give the user the ability to perform a comparative analysis on the 3-Dimensional structure of the genomes of cells in different biological states.`HiCcompare` differs from other packages that attempt to compare Hi-C data in that it works on processed data in chromatin interaction matrix format instead of pre-processed sequencing data. In addition, `HiCcompare` provides a non-parametric method for the joint normalization and removal of biases between two Hi-C datasets for the purpose of comparative analysis. `HiCcompare` also provides a simple yet robust method for detecting differences between Hi-C datasets.

Maintained by Mikhail Dozmorov. Last updated 5 months ago.

software hic sequencing normalization difference-detection hi-c visualization

7.6 match 19 stars 8.61 score 51 scripts 5 dependents

nanxstats

ggsci:Scientific Journal and Sci-Fi Themed Color Palettes for 'ggplot2'

A collection of 'ggplot2' color palettes inspired by plots in scientific journals, data visualization libraries, science fiction movies, and TV shows.

Maintained by Nan Xiao. Last updated 9 months ago.

color-palettes data-visualization ggplot2 ggsci sci-fi scientific-journals visualization

3.6 match 680 stars 18.00 score 26k scripts 438 dependents

bioc

GenomeInfoDb:Utilities for manipulating chromosome names, including modifying them to follow a particular naming style

Contains data and functions that define and allow translation between different chromosome sequence naming conventions (e.g., "chr1" versus "1"), including a function that attempts to place sequence names in their natural, rather than lexicographic, order.

Maintained by Hervé Pagès. Last updated 2 months ago.

genetics datarepresentation annotation genomeannotation bioconductor-package core-package

3.6 match 32 stars 16.46 score 1.3k scripts 1.7k dependents

bioc

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.

visualization

6.0 match 8.71 score 145 scripts 2 dependents

bioc

ChIPpeakAnno:Batch annotation of the peaks identified from either ChIP-seq, ChIP-chip experiments, or any experiments that result in large number of genomic interval data

The package encompasses a range of functions for identifying the closest gene, exon, miRNA, or custom features—such as highly conserved elements and user-supplied transcription factor binding sites. Additionally, users can retrieve sequences around the peaks and obtain enriched Gene Ontology (GO) or Pathway terms. In version 2.0.5 and beyond, new functionalities have been introduced. These include features for identifying peaks associated with bi-directional promoters along with summary statistics (peaksNearBDP), summarizing motif occurrences in peaks (summarizePatternInPeaks), and associating additional identifiers with annotated peaks or enrichedGO (addGeneIDs). The package integrates with various other packages such as biomaRt, IRanges, Biostrings, BSgenome, GO.db, multtest, and stat to enhance its analytical capabilities.

Maintained by Jianhong Ou. Last updated 2 months ago.

annotation chipseq chipchip

5.8 match 8.75 score 584 scripts 6 dependents

bioc

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 11 days ago.

crispr functionalgenomics genetarget bioconductor bioconductor-package crispr-cas9 crispr-design crispr-target genomics-analysis grna grna-sequence grna-sequences sgrna sgrna-design

5.5 match 22 stars 8.28 score 80 scripts 3 dependents

bioc

Gviz:Plotting data and annotation information along genomic coordinates

Genomic data analyses requires integrated visualization of known genomic information and new experimental data. Gviz uses the biomaRt and the rtracklayer packages to perform live annotation queries to Ensembl and UCSC and translates this to e.g. gene/transcript structures in viewports of the grid graphics package. This results in genomic information plotted together with your data.

Maintained by Robert Ivanek. Last updated 5 months ago.

visualization microarray sequencing

3.4 match 79 stars 13.08 score 1.4k scripts 48 dependents

bioc

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.

geneexpression sequencing visualization genomeannotation coverage

10.4 match 4.30 score 6 scripts

bioc

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.

immunooncology coverage rnaseq chipseq sequencing visualization geneexpression transcription alternativesplicing

7.9 match 5.49 score 26 scripts 1 dependents

bioc

MungeSumstats:Standardise summary statistics from GWAS

The *MungeSumstats* package is designed to facilitate the standardisation of GWAS summary statistics. It reformats inputted summary statisitics to include SNP, CHR, BP and can look up these values if any are missing. It also pefrorms dozens of QC and filtering steps to ensure high data quality and minimise inter-study differences.

Maintained by Alan Murphy. Last updated 3 months ago.

snp wholegenome genetics comparativegenomics genomewideassociation genomicvariation preprocessing

7.2 match 1 stars 5.87 score 91 scripts

stuart-lab

Signac:Analysis of Single-Cell Chromatin Data

A framework for the analysis and exploration of single-cell chromatin data. The 'Signac' package contains functions for quantifying single-cell chromatin data, computing per-cell quality control metrics, dimension reduction and normalization, visualization, and DNA sequence motif analysis. Reference: Stuart et al. (2021) <doi:10.1038/s41592-021-01282-5>.

Maintained by Tim Stuart. Last updated 7 months ago.

atac bioinformatics single-cell zlib cpp

3.4 match 349 stars 12.19 score 3.7k scripts 1 dependents

bioc

seqsetvis:Set Based Visualizations for Next-Gen Sequencing Data

seqsetvis enables the visualization and analysis of sets of genomic sites in next gen sequencing data. Although seqsetvis was designed for the comparison of mulitple ChIP-seq samples, this package is domain-agnostic and allows the processing of multiple genomic coordinate files (bed-like files) and signal files (bigwig files pileups from bam file). seqsetvis has multiple functions for fetching data from regions into a tidy format for analysis in data.table or tidyverse and visualization via ggplot2.

Maintained by Joseph R Boyd. Last updated 3 months ago.

software chipseq multiplecomparison sequencing visualization

7.0 match 5.82 score 82 scripts

bioc

GenVisR:Genomic Visualizations in R

Produce highly customizable publication quality graphics for genomic data primarily at the cohort level.

Maintained by Zachary Skidmore. Last updated 5 months ago.

infrastructure datarepresentation classification dnaseq

4.0 match 215 stars 9.87 score 76 scripts

bioc

OmicCircos:High-quality circular visualization of omics data

OmicCircos is an R application and package for generating high-quality circular plots for omics data.

Maintained by Ying Hu. Last updated 5 months ago.

visualization statistics annotation

7.5 match 5.20 score 80 scripts

bioc

rGREAT:GREAT Analysis - Functional Enrichment on Genomic Regions

GREAT (Genomic Regions Enrichment of Annotations Tool) is a type of functional enrichment analysis directly performed on genomic regions. This package implements the GREAT algorithm (the local GREAT analysis), also it supports directly interacting with the GREAT web service (the online GREAT analysis). Both analysis can be viewed by a Shiny application. rGREAT by default supports more than 600 organisms and a large number of gene set collections, as well as self-provided gene sets and organisms from users. Additionally, it implements a general method for dealing with background regions.

Maintained by Zuguang Gu. Last updated 4 days ago.

genesetenrichment go pathways software sequencing wholegenome genomeannotation coverage cpp

3.8 match 86 stars 9.96 score 320 scripts 1 dependents

bioc

igvR:igvR: integrative genomics viewer

Access to igv.js, the Integrative Genomics Viewer running in a web browser.

Maintained by Arkadiusz Gladki. Last updated 5 months ago.

visualization thirdpartyclient genomebrowsers

4.5 match 43 stars 8.31 score 118 scripts

bioc

sevenC:Computational Chromosome Conformation Capture by Correlation of ChIP-seq at CTCF motifs

Chromatin looping is an essential feature of eukaryotic genomes and can bring regulatory sequences, such as enhancers or transcription factor binding sites, in the close physical proximity of regulated target genes. Here, we provide sevenC, an R package that uses protein binding signals from ChIP-seq and sequence motif information to predict chromatin looping events. Cross-linking of proteins that bind close to loop anchors result in ChIP-seq signals at both anchor loci. These signals are used at CTCF motif pairs together with their distance and orientation to each other to predict whether they interact or not. The resulting chromatin loops might be used to associate enhancers or transcription factor binding sites (e.g., ChIP-seq peaks) to regulated target genes.

Maintained by Jonas Ibn-Salem. Last updated 5 months ago.

dna3dstructure chipchip coverage dataimport epigenetics functionalgenomics classification regression chipseq hic annotation 3d-genome chip-seq chromatin-interaction hi-c prediction sequence-motif transcription-factors

6.9 match 12 stars 5.38 score 3 scripts

bioc

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.

annotation sequencing genomeannotation bioconductor-package core-package

5.3 match 3 stars 6.77 score 63 scripts 1 dependents

bioc

casper:Characterization of Alternative Splicing based on Paired-End Reads

Infer alternative splicing from paired-end RNA-seq data. The model is based on counting paths across exons, rather than pairwise exon connections, and estimates the fragment size and start distributions non-parametrically, which improves estimation precision.

Maintained by David Rossell. Last updated 4 months ago.

immunooncology geneexpression differentialexpression transcription rnaseq sequencing cpp

7.0 match 5.02 score 66 scripts

teng-gao

hahmmr:Haplotype-Aware Hidden Markov Model for RNA

Haplotype-aware Hidden Markov Model for RNA (HaHMMR) is a method for detecting copy number variations (CNVs) from bulk RNA-seq data. Additional examples, documentations, and details on the method are available at <https://github.com/kharchenkolab/hahmmr/>.

Maintained by Teng Gao. Last updated 1 years ago.

cpp

15.8 match 2.18 score 4 scripts 1 dependents

bioc

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.

annotation genomeannotation dataimport preprocessing rnaseq singlecell transcriptomics transcription geneexpression functionalgenomics reproducibleresearch reportwriting immunooncology

3.1 match 67 stars 10.58 score 466 scripts 1 dependents

bioc

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 polyadenylation differential polyadenylation site usage rna-seq gene regulation transcription

7.1 match 4.30 score 1 scripts

bioc

ISAnalytics:Analyze gene therapy vector insertion sites data identified from genomics next generation sequencing reads for clonal tracking studies

In gene therapy, stem cells are modified using viral vectors to deliver the therapeutic transgene and replace functional properties since the genetic modification is stable and inherited in all cell progeny. The retrieval and mapping of the sequences flanking the virus-host DNA junctions allows the identification of insertion sites (IS), essential for monitoring the evolution of genetically modified cells in vivo. A comprehensive toolkit for the analysis of IS is required to foster clonal trackign studies and supporting the assessment of safety and long term efficacy in vivo. This package is aimed at (1) supporting automation of IS workflow, (2) performing base and advance analysis for IS tracking (clonal abundance, clonal expansions and statistics for insertional mutagenesis, etc.), (3) providing basic biology insights of transduced stem cells in vivo.

Maintained by Francesco Gazzo. Last updated 3 months ago.

biomedicalinformatics sequencing singlecell

5.3 match 3 stars 5.83 score 15 scripts

cbiit

LDlinkR:Calculating Linkage Disequilibrium (LD) in Human Population Groups of Interest

Provides access to the 'LDlink' API (<https://ldlink.nih.gov/?tab=apiaccess>) using the R console. This programmatic access facilitates researchers who are interested in performing batch queries in 1000 Genomes Project (2015) <doi:10.1038/nature15393> data using 'LDlink'. 'LDlink' is an interactive and powerful suite of web-based tools for querying germline variants in human population groups of interest. For more details, please see Machiela et al. (2015) <doi:10.1093/bioinformatics/btv402>.

Maintained by Timothy A. Myers. Last updated 11 months ago.

ld-calculator ldlink ldlink-api ldlink-webtool linkage-disequilibrium population-genetics

3.3 match 58 stars 9.21 score 206 scripts 1 dependents

bioc

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.

alternativesplicing chipseq coverage geneexpression rnaseq sequencing software transcription visualization annotation

5.2 match 3 stars 5.62 score 4 scripts

bioc

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.

singlecell rnaseq workflowstep cpp

3.8 match 9 stars 7.35 score 165 scripts

bioc

EpiCompare:Comparison, Benchmarking & QC of Epigenomic Datasets

EpiCompare is used to compare and analyse epigenetic datasets for quality control and benchmarking purposes. The package outputs an HTML report consisting of three sections: (1. General metrics) Metrics on peaks (percentage of blacklisted and non-standard peaks, and peak widths) and fragments (duplication rate) of samples, (2. Peak overlap) Percentage and statistical significance of overlapping and non-overlapping peaks. Also includes upset plot and (3. Functional annotation) functional annotation (ChromHMM, ChIPseeker and enrichment analysis) of peaks. Also includes peak enrichment around TSS.

Maintained by Hiranyamaya Dash. Last updated 30 days ago.

epigenetics genetics qualitycontrol chipseq multiplecomparison functionalgenomics atacseq dnaseseq benchmark benchmarking bioconductor bioconductor-package comparison html interactive-reporting

3.6 match 14 stars 7.54 score 46 scripts

bioc

cfdnakit:Fragmen-length analysis package from high-throughput sequencing of cell-free DNA (cfDNA)

This package provides basic functions for analyzing shallow whole-genome sequencing (~0.3X or more) of cell-free DNA (cfDNA). The package basically extracts the length of cfDNA fragments and aids the vistualization of fragment-length information. The package also extract fragment-length information per non-overlapping fixed-sized bins and used it for calculating ctDNA estimation score (CES).

Maintained by Pitithat Puranachot. Last updated 5 months ago.

copynumbervariation sequencing wholegenome

5.1 match 8 stars 5.20 score 8 scripts

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ChIPQC:Quality metrics for ChIPseq data

Quality metrics for ChIPseq data.

Maintained by Tom Carroll. Last updated 5 months ago.

sequencing chipseq qualitycontrol reportwriting

4.8 match 5.45 score 140 scripts

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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.

alignment annotation rnaseq sequencing transcriptomics

6.0 match 4.30 score 9 scripts

bioc

transcriptR:An Integrative Tool for ChIP- And RNA-Seq Based Primary Transcripts Detection and Quantification

The differences in the RNA types being sequenced have an impact on the resulting sequencing profiles. mRNA-seq data is enriched with reads derived from exons, while GRO-, nucRNA- and chrRNA-seq demonstrate a substantial broader coverage of both exonic and intronic regions. The presence of intronic reads in GRO-seq type of data makes it possible to use it to computationally identify and quantify all de novo continuous regions of transcription distributed across the genome. This type of data, however, is more challenging to interpret and less common practice compared to mRNA-seq. One of the challenges for primary transcript detection concerns the simultaneous transcription of closely spaced genes, which needs to be properly divided into individually transcribed units. The R package transcriptR combines RNA-seq data with ChIP-seq data of histone modifications that mark active Transcription Start Sites (TSSs), such as, H3K4me3 or H3K9/14Ac to overcome this challenge. The advantage of this approach over the use of, for example, gene annotations is that this approach is data driven and therefore able to deal also with novel and case specific events. Furthermore, the integration of ChIP- and RNA-seq data allows the identification all known and novel active transcription start sites within a given sample.

Maintained by Armen R. Karapetyan. Last updated 5 months ago.

immunooncology transcription software sequencing rnaseq coverage

7.5 match 3.30 score 2 scripts

bioc

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.

genetics annotationdata sequencing coverage annotation bioconductor bioconductor-packages ensembl

1.6 match 35 stars 14.08 score 892 scripts 108 dependents

bioc

SomaticSignatures:Somatic Signatures

The SomaticSignatures package identifies mutational signatures of single nucleotide variants (SNVs). It provides a infrastructure related to the methodology described in Nik-Zainal (2012, Cell), with flexibility in the matrix decomposition algorithms.

Maintained by Julian Gehring. Last updated 5 months ago.

sequencing somaticmutation visualization clustering genomicvariation statisticalmethod

3.3 match 22 stars 6.85 score 54 scripts 1 dependents

bioc

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.

infrastructure dataimport gui thirdpartyclient core-package u24ca289073

1.6 match 17 stars 13.89 score 2.7k scripts 102 dependents

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.

genetics infrastructure dataimport sequencing rnaseq riboseq chipseq methylseq snp geneexpression coverage genesetenrichment alignment qualitycontrol immunooncology reportwriting workflowstep workflowmanagement

1.9 match 53 stars 11.56 score 344 scripts 3 dependents

bioc

iGC:An integrated analysis package of Gene expression and Copy number alteration

This package is intended to identify differentially expressed genes driven by Copy Number Alterations from samples with both gene expression and CNA data.

Maintained by Liang-Bo Wang. Last updated 5 months ago.

software biological question differentialexpression genomicvariation assaydomain copynumbervariation geneexpression researchfield genetics technology microarray sequencing workflowstep multiplecomparison

5.6 match 1 stars 3.78 score 1 scripts

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cicero:Predict cis-co-accessibility from single-cell chromatin accessibility data

Cicero computes putative cis-regulatory maps from single-cell chromatin accessibility data. It also extends monocle 2 for use in chromatin accessibility data.

Maintained by Hannah Pliner. Last updated 5 months ago.

sequencing clustering cellbasedassays immunooncology generegulation genetarget epigenetics atacseq singlecell

3.6 match 5.80 score 312 scripts

bioc

REMP:Repetitive Element Methylation Prediction

Machine learning-based tools to predict DNA methylation of locus-specific repetitive elements (RE) by learning surrounding genetic and epigenetic information. These tools provide genomewide and single-base resolution of DNA methylation prediction on RE that are difficult to measure using array-based or sequencing-based platforms, which enables epigenome-wide association study (EWAS) and differentially methylated region (DMR) analysis on RE.

Maintained by Yinan Zheng. Last updated 5 months ago.

dnamethylation microarray methylationarray sequencing genomewideassociation epigenetics preprocessing multichannel twochannel differentialmethylation qualitycontrol dataimport

3.5 match 2 stars 5.94 score 18 scripts

pboutros

bedr:Genomic Region Processing using Tools Such as 'BEDTools', 'BEDOPS' and 'Tabix'

Genomic regions processing using open-source command line tools such as 'BEDTools', 'BEDOPS' and 'Tabix'. These tools offer scalable and efficient utilities to perform genome arithmetic e.g indexing, formatting and merging. bedr API enhances access to these tools as well as offers additional utilities for genomic regions processing.

Maintained by Paul C. Boutros. Last updated 6 years ago.

4.1 match 4.98 score 264 scripts 2 dependents

tanaylab

misha:Toolkit for Analysis of Genomic Data

A toolkit for analysis of genomic data. The 'misha' package implements an efficient data structure for storing genomic data, and provides a set of functions for data extraction, manipulation and analysis. Some of the 2D genome algorithms were described in Yaffe and Tanay (2011) <doi:10.1038/ng.947>.

Maintained by Aviezer Lifshitz. Last updated 6 days ago.

genomic-data-analysis cpp

3.5 match 4 stars 5.86 score

grealesm

RapidoPGS:A Fast and Light Package to Compute Polygenic Risk Scores

Quickly computes polygenic scores from GWAS summary statistics of either case-control or quantitative traits without parameter tuning. Reales,G., Vigorito, E., Kelemen,M., Wallace,C. (2021) <doi:10.1101/2020.07.24.220392> "RápidoPGS: A rapid polygenic score calculator for summary GWAS data without a test dataset".

Maintained by Guillermo Reales. Last updated 25 days ago.

3.5 match 13 stars 5.59 score 9 scripts

bioc

oligoClasses:Classes for high-throughput arrays supported by oligo and crlmm

This package contains class definitions, validity checks, and initialization methods for classes used by the oligo and crlmm packages.

Maintained by Benilton Carvalho. Last updated 5 months ago.

infrastructure

3.3 match 5.85 score 93 scripts 17 dependents

bioc

pgxRpi:R wrapper for Progenetix

The package is an R wrapper for Progenetix REST API built upon the Beacon v2 protocol. Its purpose is to provide a seamless way for retrieving genomic data from Progenetix database—an open resource dedicated to curated oncogenomic profiles. Empowered by this package, users can effortlessly access and visualize data from Progenetix.

Maintained by Hangjia Zhao. Last updated 13 days ago.

copynumbervariation genomicvariation dataimport software

3.3 match 3 stars 5.95 score 6 scripts

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GeneBreak:Gene Break Detection

Recurrent breakpoint gene detection on copy number aberration profiles.

Maintained by Evert van den Broek. Last updated 5 months ago.

acgh copynumbervariation dnaseq genetics sequencing wholegenome visualization

4.0 match 2 stars 4.60 score 6 scripts

bioc

rCGH:Comprehensive Pipeline for Analyzing and Visualizing Array-Based CGH Data

A comprehensive pipeline for analyzing and interactively visualizing genomic profiles generated through commercial or custom aCGH arrays. As inputs, rCGH supports Agilent dual-color Feature Extraction files (.txt), from 44 to 400K, Affymetrix SNP6.0 and cytoScanHD probeset.txt, cychp.txt, and cnchp.txt files exported from ChAS or Affymetrix Power Tools. rCGH also supports custom arrays, provided data complies with the expected format. This package takes over all the steps required for individual genomic profiles analysis, from reading files to profiles segmentation and gene annotations. This package also provides several visualization functions (static or interactive) which facilitate individual profiles interpretation. Input files can be in compressed format, e.g. .bz2 or .gz.

Maintained by Frederic Commo. Last updated 5 months ago.

acgh copynumbervariation preprocessing featureextraction

3.6 match 4 stars 5.10 score 26 scripts 1 dependents

bioc

interacCircos:The Generation of Interactive Circos Plot

Implement in an efficient approach to display the genomic data, relationship, information in an interactive circular genome(Circos) plot. 'interacCircos' are inspired by 'circosJS', 'BioCircos.js' and 'NG-Circos' and we integrate the modules of 'circosJS', 'BioCircos.js' and 'NG-Circos' into this R package, based on 'htmlwidgets' framework.

Maintained by Zhe Cui. Last updated 5 months ago.

visualization

4.5 match 4.00 score 1 scripts

bioc

TFutils:TFutils

This package helps users to work with TF metadata from various sources. Significant catalogs of TFs and classifications thereof are made available. Tools for working with motif scans are also provided.

Maintained by Vincent Carey. Last updated 4 months ago.

transcriptomics

3.8 match 4.80 score 21 scripts

bioc

epimutacions:Robust outlier identification for DNA methylation data

The package includes some statistical outlier detection methods for epimutations detection in DNA methylation data. The methods included in the package are MANOVA, Multivariate linear models, isolation forest, robust mahalanobis distance, quantile and beta. The methods compare a case sample with a suspected disease against a reference panel (composed of healthy individuals) to identify epimutations in the given case sample. It also contains functions to annotate and visualize the identified epimutations.

Maintained by Dolors Pelegri-Siso. Last updated 5 months ago.

dnamethylation biologicalquestion preprocessing statisticalmethod normalization cpp

4.3 match 4.23 score 28 scripts

bioc

BSgenomeForge:Forge your own BSgenome data package

A set of tools to forge BSgenome data packages. Supersedes the old seed-based tools from the BSgenome software package. This package allows the user to create a BSgenome data package in one function call, simplifying the old seed-based process.

Maintained by Hervé Pagès. Last updated 5 months ago.

infrastructure datarepresentation genomeassembly annotation genomeannotation sequencing alignment dataimport sequencematching bioconductor-package core-package

3.6 match 4 stars 4.90 score 6 scripts

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aCGH:Classes and functions for Array Comparative Genomic Hybridization data

Functions for reading aCGH data from image analysis output files and clone information files, creation of aCGH S3 objects for storing these data. Basic methods for accessing/replacing, subsetting, printing and plotting aCGH objects.

Maintained by Peter Dimitrov. Last updated 5 months ago.

copynumbervariation dataimport genetics cpp

3.3 match 5.38 score 9 scripts 4 dependents

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motifTestR:Perform key tests for binding motifs in sequence data

Taking a set of sequence motifs as PWMs, test a set of sequences for over-representation of these motifs, as well as any positional features within the set of motifs. Enrichment analysis can be undertaken using multiple statistical approaches. The package also contains core functions to prepare data for analysis, and to visualise results.

Maintained by Stevie Pederson. Last updated 9 days ago.

motifannotation chipseq chiponchip sequencematching software

3.6 match 1 stars 4.90 score 2 scripts

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clustifyr:Classifier for Single-cell RNA-seq Using Cell Clusters

Package designed to aid in classifying cells from single-cell RNA sequencing data using external reference data (e.g., bulk RNA-seq, scRNA-seq, microarray, gene lists). A variety of correlation based methods and gene list enrichment methods are provided to assist cell type assignment.

Maintained by Rui Fu. Last updated 5 months ago.

singlecell annotation sequencing microarray geneexpression assign-identities clusters marker-genes rna-seq single-cell-rna-seq

1.8 match 119 stars 9.63 score 296 scripts

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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.

visualization genomeannotation functionalgenomics genomeassembly hic cpp

1.7 match 308 stars 10.16 score 167 scripts 3 dependents

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NoRCE:NoRCE: Noncoding RNA Sets Cis Annotation and Enrichment

While some non-coding RNAs (ncRNAs) are assigned critical regulatory roles, most remain functionally uncharacterized. This presents a challenge whenever an interesting set of ncRNAs needs to be analyzed in a functional context. Transcripts located close-by on the genome are often regulated together. This genomic proximity on the sequence can hint to a functional association. We present a tool, NoRCE, that performs cis enrichment analysis for a given set of ncRNAs. Enrichment is carried out using the functional annotations of the coding genes located proximal to the input ncRNAs. Other biologically relevant information such as topologically associating domain (TAD) boundaries, co-expression patterns, and miRNA target prediction information can be incorporated to conduct a richer enrichment analysis. To this end, NoRCE includes several relevant datasets as part of its data repository, including cell-line specific TAD boundaries, functional gene sets, and expression data for coding & ncRNAs specific to cancer. Additionally, the users can utilize custom data files in their investigation. Enrichment results can be retrieved in a tabular format or visualized in several different ways. NoRCE is currently available for the following species: human, mouse, rat, zebrafish, fruit fly, worm, and yeast.

Maintained by Gulden Olgun. Last updated 5 months ago.

biologicalquestion differentialexpression genomeannotation genesetenrichment genetarget genomeassembly go

3.6 match 1 stars 4.60 score 6 scripts

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CNEr:CNE Detection and Visualization

Large-scale identification and advanced visualization of sets of conserved noncoding elements.

Maintained by Ge Tan. Last updated 5 months ago.

generegulation visualization dataimport

1.8 match 3 stars 9.28 score 35 scripts 19 dependents

tdhock

PeakSegDisk:Disk-Based Constrained Change-Point Detection

Disk-based implementation of Functional Pruning Optimal Partitioning with up-down constraints <doi:10.18637/jss.v101.i10> for single-sample peak calling (independently for each sample and genomic problem), can handle huge data sets (10^7 or more).

Maintained by Toby Dylan Hocking. Last updated 6 months ago.

cpp

3.4 match 4 stars 4.65 score 37 scripts

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sesame:SEnsible Step-wise Analysis of DNA MEthylation BeadChips

Tools For analyzing Illumina Infinium DNA methylation arrays. SeSAMe provides utilities to support analyses of multiple generations of Infinium DNA methylation BeadChips, including preprocessing, quality control, visualization and inference. SeSAMe features accurate detection calling, intelligent inference of ethnicity, sex and advanced quality control routines.

Maintained by Wanding Zhou. Last updated 2 months ago.

dnamethylation methylationarray preprocessing qualitycontrol bioinformatics dna-methylation microarray

1.8 match 69 stars 9.08 score 258 scripts 1 dependents

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BubbleTree:BubbleTree: an intuitive visualization to elucidate tumoral aneuploidy and clonality in somatic mosaicism using next generation sequencing data

CNV analysis in groups of tumor samples.

Maintained by Todd Creasy. Last updated 5 months ago.

copynumbervariation software sequencing coverage

4.0 match 3.95 score 15 scripts

bioc

hiAnnotator:Functions for annotating GRanges objects

hiAnnotator contains set of functions which allow users to annotate a GRanges object with custom set of annotations. The basic philosophy of this package is to take two GRanges objects (query & subject) with common set of seqnames (i.e. chromosomes) and return associated annotation per seqnames and rows from the query matching seqnames and rows from the subject (i.e. genes or cpg islands). The package comes with three types of annotation functions which calculates if a position from query is: within a feature, near a feature, or count features in defined window sizes. Moreover, each function is equipped with parallel backend to utilize the foreach package. In addition, the package is equipped with wrapper functions, which finds appropriate columns needed to make a GRanges object from a common data frame.

Maintained by Nirav V Malani. Last updated 5 months ago.

software annotation

3.4 match 4.65 score 15 scripts 1 dependents

bioc

xenLite:Simple classes and methods for managing Xenium datasets

Define a relatively light class for managing Xenium data using Bioconductor. Address use of parquet for coordinates, SpatialExperiment for assay and sample data. Address serialization and use of cloud storage.

Maintained by Vincent Carey. Last updated 5 months ago.

infrastructure

3.4 match 1 stars 4.48 score 4 scripts

rli012

Hapi:Inference of Chromosome-Length Haplotypes Using Genomic Data of Single Gamete Cells

Inference of chromosome-length haplotypes using a few haploid gametes of an individual. The gamete genotype data may be generated from various platforms including genotyping arrays and sequencing even with low-coverage. Hapi simply takes genotype data of known hetSNPs in single gamete cells as input and report the high-resolution haplotypes as well as confidence of each phased hetSNPs. The package also includes a module allowing downstream analyses and visualization of identified crossovers in the gametes.

Maintained by Ruidong Li. Last updated 7 years ago.

snp genomicvariation genetics hiddenmarkovmodel singlecell sequencing microarray

4.0 match 3.79 score 41 scripts

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CNAnorm:A normalization method for Copy Number Aberration in cancer samples

Performs ratio, GC content correction and normalization of data obtained using low coverage (one read every 100-10,000 bp) high troughput sequencing. It performs a "discrete" normalization looking for the ploidy of the genome. It will also provide tumour content if at least two ploidy states can be found.

Maintained by Stefano Berri. Last updated 5 months ago.

copynumbervariation sequencing coverage normalization wholegenome dnaseq genomicvariation fortran

3.5 match 4.30 score 6 scripts

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SigsPack:Mutational Signature Estimation for Single Samples

Single sample estimation of exposure to mutational signatures. Exposures to known mutational signatures are estimated for single samples, based on quadratic programming algorithms. Bootstrapping the input mutational catalogues provides estimations on the stability of these exposures. The effect of the sequence composition of mutational context can be taken into account by normalising the catalogues.

Maintained by Franziska Schumann. Last updated 5 months ago.

somaticmutation snp variantannotation biomedicalinformatics dnaseq

3.5 match 2 stars 4.30 score 4 scripts

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ACME:Algorithms for Calculating Microarray Enrichment (ACME)

ACME (Algorithms for Calculating Microarray Enrichment) is a set of tools for analysing tiling array ChIP/chip, DNAse hypersensitivity, or other experiments that result in regions of the genome showing "enrichment". It does not rely on a specific array technology (although the array should be a "tiling" array), is very general (can be applied in experiments resulting in regions of enrichment), and is very insensitive to array noise or normalization methods. It is also very fast and can be applied on whole-genome tiling array experiments quite easily with enough memory.

Maintained by Sean Davis. Last updated 5 months ago.

technology microarray normalization

3.5 match 4.30 score 4 scripts

bioc

SMITE:Significance-based Modules Integrating the Transcriptome and Epigenome

This package builds on the Epimods framework which facilitates finding weighted subnetworks ("modules") on Illumina Infinium 27k arrays using the SpinGlass algorithm, as implemented in the iGraph package. We have created a class of gene centric annotations associated with p-values and effect sizes and scores from any researchers prior statistical results to find functional modules.

Maintained by Neil Ari Wijetunga. Last updated 5 months ago.

immunooncology differentialmethylation differentialexpression systemsbiology networkenrichment genomeannotation network sequencing rnaseq coverage

3.4 match 1 stars 4.26 score 13 scripts

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recount3:Explore and download data from the recount3 project

The recount3 package enables access to a large amount of uniformly processed RNA-seq data from human and mouse. You can download RangedSummarizedExperiment objects at the gene, exon or exon-exon junctions level with sample metadata and QC statistics. In addition we provide access to sample coverage BigWig files.

Maintained by Leonardo Collado-Torres. Last updated 3 months ago.

coverage differentialexpression geneexpression rnaseq sequencing software dataimport annotation-agnostic bioconductor count derfinder exon gene human illumina junction mouse recount recount3

1.8 match 33 stars 8.03 score 216 scripts

bnprks

BPCells:Single Cell Counts Matrices to PCA

> Efficient operations for single cell ATAC-seq fragments and RNA counts matrices. Interoperable with standard file formats, and introduces efficient bit-packed formats that allow large storage savings and increased read speeds.

Maintained by Benjamin Parks. Last updated 1 months ago.

zlib hdf5 cpp

1.9 match 184 stars 7.48 score 172 scripts

myles-lewis

locuszoomr:Gene Locus Plot with Gene Annotations

Publication-ready regional gene locus plots similar to those produced by the web interface 'LocusZoom' <https://my.locuszoom.org>, but running locally in R. Genetic or genomic data with gene annotation tracks are plotted via R base graphics, 'ggplot2' or 'plotly', allowing flexibility and easy customisation including laying out multiple locus plots on the same page. It uses the 'LDlink' API <https://ldlink.nih.gov/?tab=apiaccess> to query linkage disequilibrium data from the 1000 Genomes Project and can overlay this on plots <doi:10.1093/bioadv/vbaf006>.

Maintained by Myles Lewis. Last updated 13 days ago.

1.9 match 40 stars 7.43 score 50 scripts

bioc

ConsensusClusterPlus:ConsensusClusterPlus

algorithm for determining cluster count and membership by stability evidence in unsupervised analysis

Maintained by Matt Wilkerson. Last updated 5 months ago.

software clustering

1.6 match 8.36 score 412 scripts 22 dependents

bioc

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.

software transcription coverage geneexpression generegulation peakdetection dataimport datarepresentation transcriptomics sequencing annotation genomebrowsers normalization preprocessing visualization

1.8 match 8 stars 7.46 score 67 scripts 1 dependents

bioc

chimeraviz:Visualization tools for gene fusions

chimeraviz manages data from fusion gene finders and provides useful visualization tools.

Maintained by Stian Lågstad. Last updated 5 months ago.

infrastructure alignment

2.0 match 37 stars 6.71 score 14 scripts

bioc

oncomix:Identifying Genes Overexpressed in Subsets of Tumors from Tumor-Normal mRNA Expression Data

This package helps identify mRNAs that are overexpressed in subsets of tumors relative to normal tissue. Ideal inputs would be paired tumor-normal data from the same tissue from many patients (>15 pairs). This unsupervised approach relies on the observation that oncogenes are characteristically overexpressed in only a subset of tumors in the population, and may help identify oncogene candidates purely based on differences in mRNA expression between previously unknown subtypes.

Maintained by Daniel Pique. Last updated 5 months ago.

geneexpression sequencing

3.4 match 3.78 score 4 scripts

bioc

SCANVIS:SCANVIS - a tool for SCoring, ANnotating and VISualizing splice junctions

SCANVIS is a set of annotation-dependent tools for analyzing splice junctions and their read support as predetermined by an alignment tool of choice (for example, STAR aligner). SCANVIS assesses each junction's relative read support (RRS) by relating to the context of local split reads aligning to annotated transcripts. SCANVIS also annotates each splice junction by indicating whether the junction is supported by annotation or not, and if not, what type of junction it is (e.g. exon skipping, alternative 5' or 3' events, Novel Exons). Unannotated junctions are also futher annotated by indicating whether it induces a frame shift or not. SCANVIS includes a visualization function to generate static sashimi-style plots depicting relative read support and number of split reads using arc thickness and arc heights, making it easy for users to spot well-supported junctions. These plots also clearly delineate unannotated junctions from annotated ones using designated color schemes, and users can also highlight splice junctions of choice. Variants and/or a read profile are also incoroporated into the plot if the user supplies variants in bed format and/or the BAM file. One further feature of the visualization function is that users can submit multiple samples of a certain disease or cohort to generate a single plot - this occurs via a "merge" function wherein junction details over multiple samples are merged to generate a single sashimi plot, which is useful when contrasting cohorots (eg. disease vs control).

Maintained by Phaedra Agius. Last updated 5 months ago.

software researchfield transcriptomics workflowstep annotation visualization

3.1 match 4.00 score 2 scripts

bioc

NanoMethViz:Visualise methylation data from Oxford Nanopore sequencing

NanoMethViz is a toolkit for visualising methylation data from Oxford Nanopore sequencing. It can be used to explore methylation patterns from reads derived from Oxford Nanopore direct DNA sequencing with methylation called by callers including nanopolish, f5c and megalodon. The plots in this package allow the visualisation of methylation profiles aggregated over experimental groups and across classes of genomic features.

Maintained by Shian Su. Last updated 7 days ago.

software longread visualization differentialmethylation dnamethylation epigenetics dataimport zlib cpp

1.8 match 26 stars 6.95 score 11 scripts

bioc

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.

rnaseq geneexpression transcription alternativesplicing generegulation differentialsplicing functionalgenomics epigenetics transcriptomics preprocessing alternative-promoters genomics promoter-activity promoter-annotation rna-seq-data

1.8 match 51 stars 6.66 score 15 scripts

bioc

Repitools:Epigenomic tools

Tools for the analysis of enrichment-based epigenomic data. Features include summarization and visualization of epigenomic data across promoters according to gene expression context, finding regions of differential methylation/binding, BayMeth for quantifying methylation etc.

Maintained by Mark Robinson. Last updated 5 months ago.

dnamethylation geneexpression methylseq

2.0 match 5.90 score 267 scripts

bioc

atena:Analysis of Transposable Elements

Quantify expression of transposable elements (TEs) from RNA-seq data through different methods, including ERVmap, TEtranscripts and Telescope. A common interface is provided to use each of these methods, which consists of building a parameter object, calling the quantification function with this object and getting a SummarizedExperiment object as output container of the quantified expression profiles. The implementation allows one to quantify TEs and gene transcripts in an integrated manner.

Maintained by Robert Castelo. Last updated 1 months ago.

transcription transcriptomics rnaseq sequencing preprocessing software geneexpression coverage differentialexpression functionalgenomics

1.9 match 10 stars 6.18 score 1 scripts

msq-123

chromseq:Split Chromosome 'Fasta' File

Chromosome files in the 'Fasta' format usually contain large sequences like human genome. Sometimes users have to split these chromosomes into different files according to their chromosome number. The 'chromseq' can help to handle this. So the selected chromosome sequence can be used for downstream analysis like motif finding. Howard Y. Chang(2019) <doi:10.1038/s41587-019-0206-z>.

Maintained by Shaoqian Ma. Last updated 5 years ago.

3.4 match 4 stars 3.30 score

bioc

YAPSA:Yet Another Package for Signature Analysis

This package provides functions and routines for supervised analyses of mutational signatures (i.e., the signatures have to be known, cf. L. Alexandrov et al., Nature 2013 and L. Alexandrov et al., Bioaxiv 2018). In particular, the family of functions LCD (LCD = linear combination decomposition) can use optimal signature-specific cutoffs which takes care of different detectability of the different signatures. Moreover, the package provides different sets of mutational signatures, including the COSMIC and PCAWG SNV signatures and the PCAWG Indel signatures; the latter infering that with YAPSA, the concept of supervised analysis of mutational signatures is extended to Indel signatures. YAPSA also provides confidence intervals as computed by profile likelihoods and can perform signature analysis on a stratified mutational catalogue (SMC = stratify mutational catalogue) in order to analyze enrichment and depletion patterns for the signatures in different strata.

Maintained by Zuguang Gu. Last updated 5 months ago.

sequencing dnaseq somaticmutation visualization clustering genomicvariation statisticalmethod biologicalquestion

1.8 match 6.41 score 57 scripts

bioc

r3Cseq:Analysis of Chromosome Conformation Capture and Next-generation Sequencing (3C-seq)

This package is used for the analysis of long-range chromatin interactions from 3C-seq assay.

Maintained by Supat Thongjuea. Last updated 5 months ago.

preprocessing sequencing

2.3 match 3 stars 4.85 score 17 scripts

blaserlab

blaseRdata:Supporting Data for the blaseRtools Package

What the package does (one paragraph).

Maintained by Brad Blaser. Last updated 12 months ago.

6.0 match 1.70 score 6 scripts

bioc

breakpointR:Find breakpoints in Strand-seq data

This package implements functions for finding breakpoints, plotting and export of Strand-seq data.

Maintained by David Porubsky. Last updated 5 months ago.

software sequencing dnaseq singlecell coverage

1.8 match 8 stars 5.64 score 11 scripts

bioc

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.

alignment coverage differentialexpression featureextraction geneexpression genomeannotation genomeassembly immunooncology longread multiplecomparison normalization rnaseq regression sequencing software transcription transcriptomics bambu bioconductor long-reads nanopore nanopore-sequencing rna-seq rna-seq-analysis transcript-quantification transcript-reconstruction cpp

1.1 match 197 stars 9.03 score 91 scripts 1 dependents

bioc

CleanUpRNAseq:Detect and Correct Genomic DNA Contamination in RNA-seq Data

RNA-seq data generated by some library preparation methods, such as rRNA-depletion-based method and the SMART-seq method, might be contaminated by genomic DNA (gDNA), if DNase I disgestion is not performed properly during RNA preparation. CleanUpRNAseq is developed to check if RNA-seq data is suffered from gDNA contamination. If so, it can perform correction for gDNA contamination and reduce false discovery rate of differentially expressed genes.

Maintained by Haibo Liu. Last updated 4 months ago.

qualitycontrol sequencing geneexpression

1.8 match 5 stars 5.44 score 4 scripts

bioc

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.

software proteomics rnaseq snp sequencing variantannotation dataimport

1.8 match 5 stars 5.30 score 4 scripts

bioc

wavClusteR:Sensitive and highly resolved identification of RNA-protein interaction sites in PAR-CLIP data

The package provides an integrated pipeline for the analysis of PAR-CLIP data. PAR-CLIP-induced transitions are first discriminated from sequencing errors, SNPs and additional non-experimental sources by a non- parametric mixture model. The protein binding sites (clusters) are then resolved at high resolution and cluster statistics are estimated using a rigorous Bayesian framework. Post-processing of the results, data export for UCSC genome browser visualization and motif search analysis are provided. In addition, the package allows to integrate RNA-Seq data to estimate the False Discovery Rate of cluster detection. Key functions support parallel multicore computing. Note: while wavClusteR was designed for PAR-CLIP data analysis, it can be applied to the analysis of other NGS data obtained from experimental procedures that induce nucleotide substitutions (e.g. BisSeq).

Maintained by Federico Comoglio. Last updated 5 months ago.

immunooncology sequencing technology ripseq rnaseq bayesian

2.0 match 4.60 score 3 scripts

bioc

CINdex:Chromosome Instability Index

The CINdex package addresses important area of high-throughput genomic analysis. It allows the automated processing and analysis of the experimental DNA copy number data generated by Affymetrix SNP 6.0 arrays or similar high throughput technologies. It calculates the chromosome instability (CIN) index that allows to quantitatively characterize genome-wide DNA copy number alterations as a measure of chromosomal instability. This package calculates not only overall genomic instability, but also instability in terms of copy number gains and losses separately at the chromosome and cytoband level.

Maintained by Yuriy Gusev. Last updated 5 months ago.

software copynumbervariation genomicvariation acgh microarray genetics sequencing

2.3 match 4.08 score 2 scripts

bioc

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.

mirna sequencematching gui shinyapps

1.9 match 4.88 score 19 scripts

bioc

GMRP:GWAS-based Mendelian Randomization and Path Analyses

Perform Mendelian randomization analysis of multiple SNPs to determine risk factors causing disease of study and to exclude confounding variabels and perform path analysis to construct path of risk factors to the disease.

Maintained by Yuan-De Tan. Last updated 5 months ago.

sequencing regression snp

2.3 match 4.00 score 3 scripts

bioc

geneAttribution:Identification of candidate genes associated with genetic variation

Identification of the most likely gene or genes through which variation at a given genomic locus in the human genome acts. The most basic functionality assumes that the closer gene is to the input locus, the more likely the gene is to be causative. Additionally, any empirical data that links genomic regions to genes (e.g. eQTL or genome conformation data) can be used if it is supplied in the UCSC .BED file format.

Maintained by Arthur Wuster. Last updated 5 months ago.

snp geneprediction genomewideassociation variantannotation genomicvariation

2.2 match 4.00 score 3 scripts

bioc

TEKRABber:An R package estimates the correlations of orthologs and transposable elements between two species

TEKRABber is made to provide a user-friendly pipeline for comparing orthologs and transposable elements (TEs) between two species. It considers the orthology confidence between two species from BioMart to normalize expression counts and detect differentially expressed orthologs/TEs. Then it provides one to one correlation analysis for desired orthologs and TEs. There is also an app function to have a first insight on the result. Users can prepare orthologs/TEs RNA-seq expression data by their own preference to run TEKRABber following the data structure mentioned in the vignettes.

Maintained by Yao-Chung Chen. Last updated 20 days ago.

differentialexpression normalization transcription geneexpression bioconductor cpp

1.7 match 3 stars 5.33 score 18 scripts

bioc

TVTB:TVTB: The VCF Tool Box

The package provides S4 classes and methods to filter, summarise and visualise genetic variation data stored in VCF files. In particular, the package extends the FilterRules class (S4Vectors package) to define news classes of filter rules applicable to the various slots of VCF objects. Functionalities are integrated and demonstrated in a Shiny web-application, the Shiny Variant Explorer (tSVE).

Maintained by Kevin Rue-Albrecht. Last updated 5 months ago.

software genetics geneticvariability genomicvariation datarepresentation gui dnaseq wholegenome visualization multiplecomparison dataimport variantannotation sequencing coverage alignment sequencematching

1.5 match 2 stars 5.76 score 16 scripts

bioc

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 5 days ago.

dataimport

1.7 match 5.02 score 22 scripts 4 dependents

bioc

IVAS:Identification of genetic Variants affecting Alternative Splicing

Identification of genetic variants affecting alternative splicing.

Maintained by Seonggyun Han. Last updated 5 months ago.

immunooncology alternativesplicing differentialexpression differentialsplicing geneexpression generegulation regression rnaseq sequencing snp software transcription

1.8 match 4.78 score 1 scripts 1 dependents

bioc

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.

differentialmethylation peakdetection geneprediction genesetenrichment

1.5 match 5.34 score 20 scripts

bioc

BindingSiteFinder:Binding site defintion based on iCLIP data

Precise knowledge on the binding sites of an RNA-binding protein (RBP) is key to understand (post-) transcriptional regulatory processes. Here we present a workflow that describes how exact binding sites can be defined from iCLIP data. The package provides functions for binding site definition and result visualization. For details please see the vignette.

Maintained by Mirko Brüggemann. Last updated 4 months ago.

sequencing geneexpression generegulation functionalgenomics coverage dataimport binding-site-classification binding-sites bioconductor-package iclip rna-binding-proteins

1.3 match 6 stars 5.65 score 3 scripts

bioc

groHMM:GRO-seq Analysis Pipeline

A pipeline for the analysis of GRO-seq data.

Maintained by Tulip Nandu. Last updated 2 days ago.

sequencing software

1.6 match 1 stars 4.48 score 25 scripts

bioc

IdeoViz:Plots data (continuous/discrete) along chromosomal ideogram

Plots data associated with arbitrary genomic intervals along chromosomal ideogram.

Maintained by Shraddha Pai. Last updated 5 months ago.

visualization microarray

1.9 match 3.88 score 25 scripts

bioc

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.

dataimport core-package u24ca289073

0.5 match 13 stars 13.76 score 486 scripts 429 dependents

wraff

wrProteo:Proteomics Data Analysis Functions

Data analysis of proteomics experiments by mass spectrometry is supported by this collection of functions mostly dedicated to the analysis of (bottom-up) quantitative (XIC) data. Fasta-formatted proteomes (eg from UniProt Consortium <doi:10.1093/nar/gky1049>) can be read with automatic parsing and multiple annotation types (like species origin, abbreviated gene names, etc) extracted. Initial results from multiple software for protein (and peptide) quantitation can be imported (to a common format): MaxQuant (Tyanova et al 2016 <doi:10.1038/nprot.2016.136>), Dia-NN (Demichev et al 2020 <doi:10.1038/s41592-019-0638-x>), Fragpipe (da Veiga et al 2020 <doi:10.1038/s41592-020-0912-y>), ionbot (Degroeve et al 2021 <doi:10.1101/2021.07.02.450686>), MassChroq (Valot et al 2011 <doi:10.1002/pmic.201100120>), OpenMS (Strauss et al 2021 <doi:10.1038/nmeth.3959>), ProteomeDiscoverer (Orsburn 2021 <doi:10.3390/proteomes9010015>), Proline (Bouyssie et al 2020 <doi:10.1093/bioinformatics/btaa118>), AlphaPept (preprint Strauss et al <doi:10.1101/2021.07.23.453379>) and Wombat-P (Bouyssie et al 2023 <doi:10.1021/acs.jproteome.3c00636>. Meta-data provided by initial analysis software and/or in sdrf format can be integrated to the analysis. Quantitative proteomics measurements frequently contain multiple NA values, due to physical absence of given peptides in some samples, limitations in sensitivity or other reasons. Help is provided to inspect the data graphically to investigate the nature of NA-values via their respective replicate measurements and to help/confirm the choice of NA-replacement algorithms. Meta-data in sdrf-format (Perez-Riverol et al 2020 <doi:10.1021/acs.jproteome.0c00376>) or similar tabular formats can be imported and included. Missing values can be inspected and imputed based on the concept of NA-neighbours or other methods. Dedicated filtering and statistical testing using the framework of package 'limma' <doi:10.18129/B9.bioc.limma> can be run, enhanced by multiple rounds of NA-replacements to provide robustness towards rare stochastic events. Multi-species samples, as frequently used in benchmark-tests (eg Navarro et al 2016 <doi:10.1038/nbt.3685>, Ramus et al 2016 <doi:10.1016/j.jprot.2015.11.011>), can be run with special options considering such sub-groups during normalization and testing. Subsequently, ROC curves (Hand and Till 2001 <doi:10.1023/A:1010920819831>) can be constructed to compare multiple analysis approaches. As detailed example the data-set from Ramus et al 2016 <doi:10.1016/j.jprot.2015.11.011>) quantified by MaxQuant, ProteomeDiscoverer, and Proline is provided with a detailed analysis of heterologous spike-in proteins.

Maintained by Wolfgang Raffelsberger. Last updated 4 months ago.

1.9 match 3.67 score 17 scripts 1 dependents

bioc

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.

software sequencing coverage

1.2 match 21 stars 5.80 score 6 scripts

jinghuazhao

gaawr2:Genetic Association Analysis

It gathers information, meta-data and scripts in a two-part Henry-Stewart talk by Zhao (2009, <doi:10.69645/DCRY5578>), which showcases analysis in aspects such as testing of polymorphic variant(s) for Hardy-Weinberg equilibrium, association with trait using genetic and statistical models as well as Bayesian implementation, power calculation in study design and genetic annotation. It also covers R integration with the Linux environment, GitHub, package creation and web applications.

Maintained by Jing Hua Zhao. Last updated 2 days ago.

1.3 match 4.90 score

mano-b

MicroSEC:Sequence Error Filter for Formalin-Fixed and Paraffin-Embedded Samples

Clinical sequencing of tumor is usually performed on formalin-fixed and paraffin-embedded samples and have many sequencing errors. We found that the majority of these errors are detected in chimeric read caused by single-strand DNA with micro-homology. Our filtering pipeline focuses on the uneven distribution of the artifacts in each read and removes such errors in formalin-fixed and paraffin-embedded samples without over-eliminating the true mutations detected in fresh frozen samples.

Maintained by Masachika Ikegami. Last updated 3 months ago.

1.1 match 7 stars 5.66 score 8 scripts

bioc

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.

software somaticmutation proteomics sequencematching alignment

1.7 match 3.48 score 1 scripts

cran

MOCHA:Modeling for Single-Cell Open Chromatin Analysis

A statistical framework and analysis tool for open chromatin analysis designed specifically for single cell ATAC-seq (Assay for Transposase-Accessible Chromatin) data, after cell type/cluster identification. These novel modules remove unwanted technical variation, identify open chromatin, robustly models repeated measures in single cell data, implement advanced statistical frameworks to model zero-inflation for differential and co-accessibility analyses, and integrate with existing databases and modules for downstream analyses to reveal biological insights. MOCHA provides a statistical foundation for complex downstream analysis to help advance the potential of single cell ATAC-seq for applied studies. Methods for zero-inflated statistics are as described in: Ghazanfar, S., Lin, Y., Su, X. et al. (2020) <doi:10.1038/s41592-020-0885-x>. Pimentel, Ronald Silva, "Kendall's Tau and Spearman's Rho for Zero-Inflated Data" (2009) <https://scholarworks.wmich.edu/dissertations/721/>.

Maintained by Imran McGrath. Last updated 1 years ago.

1.7 match 3.49 score 31 scripts

bioc

ChromHeatMap:Heat map plotting by genome coordinate

The ChromHeatMap package can be used to plot genome-wide data (e.g. expression, CGH, SNP) along each strand of a given chromosome as a heat map. The generated heat map can be used to interactively identify probes and genes of interest.

Maintained by Tim F. Rayner. Last updated 5 months ago.

visualization

1.7 match 3.30 score

bioc

HicAggR:Set of 3D genomic interaction analysis tools

This package provides a set of functions useful in the analysis of 3D genomic interactions. It includes the import of standard HiC data formats into R and HiC normalisation procedures. The main objective of this package is to improve the visualization and quantification of the analysis of HiC contacts through aggregation. The package allows to import 1D genomics data, such as peaks from ATACSeq, ChIPSeq, to create potential couples between features of interest under user-defined parameters such as distance between pairs of features of interest. It allows then the extraction of contact values from the HiC data for these couples and to perform Aggregated Peak Analysis (APA) for visualization, but also to compare normalized contact values between conditions. Overall the package allows to integrate 1D genomics data with 3D genomics data, providing an easy access to HiC contact values.

Maintained by Olivier Cuvier. Last updated 5 months ago.

software hic dataimport datarepresentation normalization visualization dna3dstructure atacseq chipseq dnaseseq rnaseq

1.1 match 4.90 score 3 scripts

bioc

DEScan2:Differential Enrichment Scan 2

Integrated peak and differential caller, specifically designed for broad epigenomic signals.

Maintained by Dario Righelli. Last updated 5 months ago.

immunooncology peakdetection epigenetics software sequencing coverage cpp

1.6 match 3.30 score 2 scripts

cran

GenoScan:A Genome-Wide Scan Statistic Framework for Whole-Genome Sequence Data Analysis

Functions for whole-genome sequencing studies, including genome-wide scan, candidate region scan and single window test.

Maintained by Zihuai He. Last updated 6 years ago.

4.0 match 1.00 score

cran

WGScan:A Genome-Wide Scan Statistic Framework for Whole-Genome Sequence Data Analysis

Functions for the analysis of whole-genome sequencing studies to simultaneously detect the existence, and estimate the locations of association signals at genome-wide scale. The functions allow genome-wide association scan, candidate region scan and single window test.

Maintained by Zihuai He. Last updated 6 years ago.

4.0 match 1.00 score

bioc

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.

snp annotation functionalgenomics structuralprediction transcriptomics variantannotation geneprediction immunooncology

0.5 match 8 stars 6.86 score 10 scripts

bioc

easylift:An R package to perform genomic liftover

The easylift package provides a convenient tool for genomic liftover operations between different genome assemblies. It seamlessly works with Bioconductor's GRanges objects and chain files from the UCSC Genome Browser, allowing for straightforward handling of genomic ranges across various genome versions. One noteworthy feature of easylift is its integration with the BiocFileCache package. This integration automates the management and caching of chain files necessary for liftover operations. Users no longer need to manually specify chain file paths in their function calls, reducing the complexity of the liftover process.

Maintained by Abdullah Al Nahid. Last updated 5 months ago.

software workflowstep sequencing coverage genomeassembly dataimport

0.5 match 5 stars 5.00 score 7 scripts

dgbonett

statpsych:Statistical Methods for Psychologists

Implements confidence interval and sample size methods that are especially useful in psychological research. The methods can be applied in 1-group, 2-group, paired-samples, and multiple-group designs and to a variety of parameters including means, medians, proportions, slopes, standardized mean differences, standardized linear contrasts of means, plus several measures of correlation and association. Confidence interval and sample size functions are given for single parameters as well as differences, ratios, and linear contrasts of parameters. The sample size functions can be used to approximate the sample size needed to estimate a parameter or function of parameters with desired confidence interval precision or to perform a variety of hypothesis tests (directional two-sided, equivalence, superiority, noninferiority) with desired power. For details see: Statistical Methods for Psychologists, Volumes 1 – 4, <https://dgbonett.sites.ucsc.edu/>.

Maintained by Douglas G. Bonett. Last updated 3 months ago.

0.5 match 6 stars 4.83 score 15 scripts 1 dependents

bioc

RSVSim:RSVSim: an R/Bioconductor package for the simulation of structural variations

RSVSim is a package for the simulation of deletions, insertions, inversion, tandem-duplications and translocations of various sizes in any genome available as FASTA-file or BSgenome data package. SV breakpoints can be placed uniformly accross the whole genome, with a bias towards repeat regions and regions of high homology (for hg19) or at user-supplied coordinates.

Maintained by Christoph Bartenhagen. Last updated 5 months ago.

sequencing

0.5 match 4.48 score 7 scripts

bioc

MassArray:Analytical Tools for MassArray Data

This package is designed for the import, quality control, analysis, and visualization of methylation data generated using Sequenom's MassArray platform. The tools herein contain a highly detailed amplicon prediction for optimal assay design. Also included are quality control measures of data, such as primer dimer and bisulfite conversion efficiency estimation. Methylation data are calculated using the same algorithms contained in the EpiTyper software package. Additionally, automatic SNP-detection can be used to flag potentially confounded data from specific CG sites. Visualization includes barplots of methylation data as well as UCSC Genome Browser-compatible BED tracks. Multiple assays can be positionally combined for integrated analysis.

Maintained by Reid F. Thompson. Last updated 5 months ago.

immunooncology dnamethylation snp massspectrometry genetics dataimport visualization

0.5 match 4.30 score 1 scripts

rnabioco

cpp11bigwig:Read bigWig and bigBed Files

Read bigWig and bigBed files using "libBigWig" <https://github.com/dpryan79/libBigWig>. Provides lightweight access to the binary bigWig and bigBed formats developed by the UCSC Genome Browser group.

Maintained by Jay Hesselberth. Last updated 8 days ago.

cpp

0.5 match 3.95 score 3 scripts 1 dependents

bioc

rfPred:Assign rfPred functional prediction scores to a missense variants list

Based on external numerous data files where rfPred scores are pre-calculated on all genomic positions of the human exome, the package gives rfPred scores to missense variants identified by the chromosome, the position (hg19 version), the referent and alternative nucleotids and the uniprot identifier of the protein. Note that for using the package, the user has to download the TabixFile and index (approximately 3.3 Go).

Maintained by Hugo Varet. Last updated 5 months ago.

software annotation classification

0.5 match 3.60 score 4 scripts

dgbonett

vcmeta:Varying Coefficient Meta-Analysis

Implements functions for varying coefficient meta-analysis methods. These methods do not assume effect size homogeneity. Subgroup effect size comparisons, general linear effect size contrasts, and linear models of effect sizes based on varying coefficient methods can be used to describe effect size heterogeneity. Varying coefficient meta-analysis methods do not require the unrealistic assumptions of the traditional fixed-effect and random-effects meta-analysis methods. For details see: Statistical Methods for Psychologists, Volume 5, <https://dgbonett.sites.ucsc.edu/>.

Maintained by Douglas G. Bonett. Last updated 8 months ago.

0.5 match 1 stars 3.00 score 8 scripts

danieleweeks

nplplot:Plotting Linkage and Association Results

Provides routines for plotting linkage and association results along a chromosome, with marker names displayed along the top border. There are also routines for generating BED and BedGraph custom tracks for viewing in the UCSC genome browser. The data reformatting program Mega2 uses this package to plot output from a variety of programs.

Maintained by Daniel E. Weeks. Last updated 1 years ago.

0.5 match 1.00 score 8 scripts