Showing 50 of total 50 results (show query)
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dada2:Accurate, high-resolution sample inference from amplicon sequencing data
The dada2 package infers exact amplicon sequence variants (ASVs) from high-throughput amplicon sequencing data, replacing the coarser and less accurate OTU clustering approach. The dada2 pipeline takes as input demultiplexed fastq files, and outputs the sequence variants and their sample-wise abundances after removing substitution and chimera errors. Taxonomic classification is available via a native implementation of the RDP naive Bayesian classifier, and species-level assignment to 16S rRNA gene fragments by exact matching.
Maintained by Benjamin Callahan. Last updated 5 months ago.
immunooncologymicrobiomesequencingclassificationmetagenomicsampliconbioconductorbioinformaticsmetabarcodingtaxonomycpp
487 stars 13.17 score 3.0k scripts 4 dependentsbioc
systemPipeR:systemPipeR: Workflow Environment for Data Analysis and Report Generation
systemPipeR is a multipurpose data analysis workflow environment that unifies R with command-line tools. It enables scientists to analyze many types of large- or small-scale data on local or distributed computer systems with a high level of reproducibility, scalability and portability. At its core is a command-line interface (CLI) that adopts the Common Workflow Language (CWL). This design allows users to choose for each analysis step the optimal R or command-line software. It supports both end-to-end and partial execution of workflows with built-in restart functionalities. Efficient management of complex analysis tasks is accomplished by a flexible workflow control container class. Handling of large numbers of input samples and experimental designs is facilitated by consistent sample annotation mechanisms. As a multi-purpose workflow toolkit, systemPipeR enables users to run existing workflows, customize them or design entirely new ones while taking advantage of widely adopted data structures within the Bioconductor ecosystem. Another important core functionality is the generation of reproducible scientific analysis and technical reports. For result interpretation, systemPipeR offers a wide range of plotting functionality, while an associated Shiny App offers many useful functionalities for interactive result exploration. The vignettes linked from this page include (1) a general introduction, (2) a description of technical details, and (3) a collection of workflow templates.
Maintained by Thomas Girke. Last updated 5 months ago.
geneticsinfrastructuredataimportsequencingrnaseqriboseqchipseqmethylseqsnpgeneexpressioncoveragegenesetenrichmentalignmentqualitycontrolimmunooncologyreportwritingworkflowstepworkflowmanagement
53 stars 11.52 score 344 scripts 3 dependentsbioc
EDASeq:Exploratory Data Analysis and Normalization for RNA-Seq
Numerical and graphical summaries of RNA-Seq read data. Within-lane normalization procedures to adjust for GC-content effect (or other gene-level effects) on read counts: loess robust local regression, global-scaling, and full-quantile normalization (Risso et al., 2011). Between-lane normalization procedures to adjust for distributional differences between lanes (e.g., sequencing depth): global-scaling and full-quantile normalization (Bullard et al., 2010).
Maintained by Davide Risso. Last updated 5 months ago.
immunooncologysequencingrnaseqpreprocessingqualitycontroldifferentialexpression
5 stars 10.24 score 594 scripts 9 dependentsbioc
RUVSeq:Remove Unwanted Variation from RNA-Seq Data
This package implements the remove unwanted variation (RUV) methods of Risso et al. (2014) for the normalization of RNA-Seq read counts between samples.
Maintained by Davide Risso. Last updated 5 months ago.
immunooncologydifferentialexpressionpreprocessingrnaseqsoftware
13 stars 9.91 score 482 scripts 5 dependentsbioc
scone:Single Cell Overview of Normalized Expression data
SCONE is an R package for comparing and ranking the performance of different normalization schemes for single-cell RNA-seq and other high-throughput analyses.
Maintained by Davide Risso. Last updated 1 months ago.
immunooncologynormalizationpreprocessingqualitycontrolgeneexpressionrnaseqsoftwaretranscriptomicssequencingsinglecellcoverage
53 stars 9.00 score 104 scriptsbioc
QuasR:Quantify and Annotate Short Reads in R
This package provides a framework for the quantification and analysis of Short Reads. It covers a complete workflow starting from raw sequence reads, over creation of alignments and quality control plots, to the quantification of genomic regions of interest. Read alignments are either generated through Rbowtie (data from DNA/ChIP/ATAC/Bis-seq experiments) or Rhisat2 (data from RNA-seq experiments that require spliced alignments), or can be provided in the form of bam files.
Maintained by Michael Stadler. Last updated 1 months ago.
geneticspreprocessingsequencingchipseqrnaseqmethylseqcoveragealignmentqualitycontrolimmunooncologycurlbzip2xz-utilszlibcpp
6 stars 8.63 score 79 scripts 1 dependentsbioc
amplican:Automated analysis of CRISPR experiments
`amplican` performs alignment of the amplicon reads, normalizes gathered data, calculates multiple statistics (e.g. cut rates, frameshifts) and presents results in form of aggregated reports. Data and statistics can be broken down by experiments, barcodes, user defined groups, guides and amplicons allowing for quick identification of potential problems.
Maintained by Eivind Valen. Last updated 5 months ago.
immunooncologytechnologyalignmentqpcrcrisprcpp
10 stars 7.54 score 41 scriptsbioc
standR:Spatial transcriptome analyses of Nanostring's DSP data in R
standR is an user-friendly R package providing functions to assist conducting good-practice analysis of Nanostring's GeoMX DSP data. All functions in the package are built based on the SpatialExperiment object, allowing integration into various spatial transcriptomics-related packages from Bioconductor. standR allows data inspection, quality control, normalization, batch correction and evaluation with informative visualizations.
Maintained by Ning Liu. Last updated 2 months ago.
spatialtranscriptomicsgeneexpressiondifferentialexpressionqualitycontrolnormalizationexperimenthubsoftware
18 stars 7.39 score 45 scriptsbioc
DiffBind:Differential Binding Analysis of ChIP-Seq Peak Data
Compute differentially bound sites from multiple ChIP-seq experiments using affinity (quantitative) data. Also enables occupancy (overlap) analysis and plotting functions.
Maintained by Rory Stark. Last updated 2 months ago.
sequencingchipseqatacseqdnaseseqmethylseqripseqdifferentialpeakcallingdifferentialmethylationgeneregulationhistonemodificationpeakdetectionbiomedicalinformaticscellbiologymultiplecomparisonnormalizationreportwritingepigeneticsfunctionalgenomicscurlbzip2xz-utilszlibcpp
7.13 score 512 scripts 2 dependentsbioc
SingleMoleculeFootprinting:Analysis tools for Single Molecule Footprinting (SMF) data
SingleMoleculeFootprinting provides functions to analyze Single Molecule Footprinting (SMF) data. Following the workflow exemplified in its vignette, the user will be able to perform basic data analysis of SMF data with minimal coding effort. Starting from an aligned bam file, we show how to perform quality controls over sequencing libraries, extract methylation information at the single molecule level accounting for the two possible kind of SMF experiments (single enzyme or double enzyme), classify single molecules based on their patterns of molecular occupancy, plot SMF information at a given genomic location.
Maintained by Guido Barzaghi. Last updated 4 days ago.
dnamethylationcoveragenucleosomepositioningdatarepresentationepigeneticsmethylseqqualitycontrolsequencing
2 stars 6.46 score 27 scripts
adrientaudiere
MiscMetabar:Miscellaneous Functions for Metabarcoding Analysis
Facilitate the description, transformation, exploration, and reproducibility of metabarcoding analyses. 'MiscMetabar' is mainly built on top of the 'phyloseq', 'dada2' and 'targets' R packages. It helps to build reproducible and robust bioinformatics pipelines in R. 'MiscMetabar' makes ecological analysis of alpha and beta-diversity easier, more reproducible and more powerful by integrating a large number of tools. Important features are described in Taudière A. (2023) <doi:10.21105/joss.06038>.
Maintained by Adrien Taudière. Last updated 9 days ago.
sequencingmicrobiomemetagenomicsclusteringclassificationvisualizationampliconamplicon-sequencingbiodiversity-informaticsecologyilluminametabarcodingngs-analysis
17 stars 6.44 score 23 scriptsbioc
chipseq:chipseq: A package for analyzing chipseq data
Tools for helping process short read data for chipseq experiments.
Maintained by Bioconductor Package Maintainer. Last updated 5 months ago.
chipseqsequencingcoveragequalitycontroldataimport
6.35 score 91 scripts 4 dependentsbioc
scruff:Single Cell RNA-Seq UMI Filtering Facilitator (scruff)
A pipeline which processes single cell RNA-seq (scRNA-seq) reads from CEL-seq and CEL-seq2 protocols. Demultiplex scRNA-seq FASTQ files, align reads to reference genome using Rsubread, and generate UMI filtered count matrix. Also provide visualizations of read alignments and pre- and post-alignment QC metrics.
Maintained by Zhe Wang. Last updated 5 months ago.
softwaretechnologysequencingalignmentrnaseqsinglecellworkflowsteppreprocessingqualitycontrolvisualizationimmunooncologybioinformaticsscrna-seqsingle-cellumi
8 stars 6.20 score 22 scriptsbioc
segmentSeq:Methods for identifying small RNA loci from high-throughput sequencing data
High-throughput sequencing technologies allow the production of large volumes of short sequences, which can be aligned to the genome to create a set of matches to the genome. By looking for regions of the genome which to which there are high densities of matches, we can infer a segmentation of the genome into regions of biological significance. The methods in this package allow the simultaneous segmentation of data from multiple samples, taking into account replicate data, in order to create a consensus segmentation. This has obvious applications in a number of classes of sequencing experiments, particularly in the discovery of small RNA loci and novel mRNA transcriptome discovery.
Maintained by Samuel Granjeaud. Last updated 5 months ago.
multiplecomparisonsequencingalignmentdifferentialexpressionqualitycontroldataimport
6.17 score 42 scriptsbioc
esATAC:An Easy-to-use Systematic pipeline for ATACseq data analysis
This package provides a framework and complete preset pipeline for quantification and analysis of ATAC-seq Reads. It covers raw sequencing reads preprocessing (FASTQ files), reads alignment (Rbowtie2), aligned reads file operations (SAM, BAM, and BED files), peak calling (F-seq), genome annotations (Motif, GO, SNP analysis) and quality control report. The package is managed by dataflow graph. It is easy for user to pass variables seamlessly between processes and understand the workflow. Users can process FASTQ files through end-to-end preset pipeline which produces a pretty HTML report for quality control and preliminary statistical results, or customize workflow starting from any intermediate stages with esATAC functions easily and flexibly.
Maintained by Zheng Wei. Last updated 5 months ago.
immunooncologysequencingdnaseqqualitycontrolalignmentpreprocessingcoverageatacseqdnaseseqatac-seqbioconductorpipelinecppopenjdk
23 stars 6.11 score 3 scriptsbioc
metaseqR2:An R package for the analysis and result reporting of RNA-Seq data by combining multiple statistical algorithms
Provides an interface to several normalization and statistical testing packages for RNA-Seq gene expression data. Additionally, it creates several diagnostic plots, performs meta-analysis by combinining the results of several statistical tests and reports the results in an interactive way.
Maintained by Panagiotis Moulos. Last updated 18 days ago.
softwaregeneexpressiondifferentialexpressionworkflowsteppreprocessingqualitycontrolnormalizationreportwritingrnaseqtranscriptionsequencingtranscriptomicsbayesianclusteringcellbiologybiomedicalinformaticsfunctionalgenomicssystemsbiologyimmunooncologyalternativesplicingdifferentialsplicingmultiplecomparisontimecoursedataimportatacseqepigeneticsregressionproprietaryplatformsgenesetenrichmentbatcheffectchipseq
7 stars 6.05 score 3 scriptsbioc
Rqc:Quality Control Tool for High-Throughput Sequencing Data
Rqc is an optimised tool designed for quality control and assessment of high-throughput sequencing data. It performs parallel processing of entire files and produces a report which contains a set of high-resolution graphics.
Maintained by Welliton Souza. Last updated 5 months ago.
sequencingqualitycontroldataimportcpp
6.00 score 67 scriptsbioc
CellBarcode:Cellular DNA Barcode Analysis toolkit
The package CellBarcode performs Cellular DNA Barcode analysis. It can handle all kinds of DNA barcodes, as long as the barcode is within a single sequencing read and has a pattern that can be matched by a regular expression. \code{CellBarcode} can handle barcodes with flexible lengths, with or without UMI (unique molecular identifier). This tool also can be used for pre-processing some amplicon data such as CRISPR gRNA screening, immune repertoire sequencing, and metagenome data.
Maintained by Wenjie Sun. Last updated 8 days ago.
preprocessingqualitycontrolsequencingcrisprampliconamplicon-sequencingcellular-barcodecpp
1 stars 5.86 score 40 scriptsbioc
UMI4Cats:UMI4Cats: Processing, analysis and visualization of UMI-4C chromatin contact data
UMI-4C is a technique that allows characterization of 3D chromatin interactions with a bait of interest, taking advantage of a sonication step to produce unique molecular identifiers (UMIs) that help remove duplication bias, thus allowing a better differential comparsion of chromatin interactions between conditions. This package allows processing of UMI-4C data, starting from FastQ files provided by the sequencing facility. It provides two statistical methods for detecting differential contacts and includes a visualization function to plot integrated information from a UMI-4C assay.
Maintained by Mireia Ramos-Rodriguez. Last updated 5 months ago.
qualitycontrolpreprocessingalignmentnormalizationvisualizationsequencingcoveragechromatinchromatin-interactiongenomicsumi4c
5 stars 5.57 score 7 scriptsbioc
ChIPQC:Quality metrics for ChIPseq data
Quality metrics for ChIPseq data.
Maintained by Tom Carroll. Last updated 5 months ago.
sequencingchipseqqualitycontrolreportwriting
5.45 score 140 scriptsbioc
easyRNASeq:Count summarization and normalization for RNA-Seq data
Calculates the coverage of high-throughput short-reads against a genome of reference and summarizes it per feature of interest (e.g. exon, gene, transcript). The data can be normalized as 'RPKM' or by the 'DESeq' or 'edgeR' package.
Maintained by Nicolas Delhomme. Last updated 5 months ago.
geneexpressionrnaseqgeneticspreprocessingimmunooncology
5.43 score 15 scripts 1 dependentsbioc
nucleR:Nucleosome positioning package for R
Nucleosome positioning for Tiling Arrays and NGS experiments.
Maintained by Alba Sala. Last updated 5 months ago.
nucleosomepositioningcoveragechipseqmicroarraysequencinggeneticsqualitycontroldataimport
5.32 score 21 scriptsbioc
DaMiRseq:Data Mining for RNA-seq data: normalization, feature selection and classification
The DaMiRseq package offers a tidy pipeline of data mining procedures to identify transcriptional biomarkers and exploit them for both binary and multi-class classification purposes. The package accepts any kind of data presented as a table of raw counts and allows including both continous and factorial variables that occur with the experimental setting. A series of functions enable the user to clean up the data by filtering genomic features and samples, to adjust data by identifying and removing the unwanted source of variation (i.e. batches and confounding factors) and to select the best predictors for modeling. Finally, a "stacking" ensemble learning technique is applied to build a robust classification model. Every step includes a checkpoint that the user may exploit to assess the effects of data management by looking at diagnostic plots, such as clustering and heatmaps, RLE boxplots, MDS or correlation plot.
Maintained by Mattia Chiesa. Last updated 5 months ago.
sequencingrnaseqclassificationimmunooncologyopenjdk
5.32 score 7 scripts 1 dependentsbioc
icetea:Integrating Cap Enrichment with Transcript Expression Analysis
icetea (Integrating Cap Enrichment with Transcript Expression Analysis) provides functions for end-to-end analysis of multiple 5'-profiling methods such as CAGE, RAMPAGE and MAPCap, beginning from raw reads to detection of transcription start sites using replicates. It also allows performing differential TSS detection between group of samples, therefore, integrating the mRNA cap enrichment information with transcript expression analysis.
Maintained by Vivek Bhardwaj. Last updated 5 months ago.
immunooncologytranscriptiongeneexpressionsequencingrnaseqtranscriptomicsdifferentialexpressioncageexpressionrna-seq
2 stars 5.08 score 7 scriptsbioc
GARS:GARS: Genetic Algorithm for the identification of Robust Subsets of variables in high-dimensional and challenging datasets
Feature selection aims to identify and remove redundant, irrelevant and noisy variables from high-dimensional datasets. Selecting informative features affects the subsequent classification and regression analyses by improving their overall performances. Several methods have been proposed to perform feature selection: most of them relies on univariate statistics, correlation, entropy measurements or the usage of backward/forward regressions. Herein, we propose an efficient, robust and fast method that adopts stochastic optimization approaches for high-dimensional. GARS is an innovative implementation of a genetic algorithm that selects robust features in high-dimensional and challenging datasets.
Maintained by Mattia Chiesa. Last updated 5 months ago.
classificationfeatureextractionclusteringopenjdk
5.00 score 2 scriptsbioc
ribosomeProfilingQC:Ribosome Profiling Quality Control
Ribo-Seq (also named ribosome profiling or footprinting) measures translatome (unlike RNA-Seq, which sequences the transcriptome) by direct quantification of the ribosome-protected fragments (RPFs). This package provides the tools for quality assessment of ribosome profiling. In addition, it can preprocess Ribo-Seq data for subsequent differential analysis.
Maintained by Jianhong Ou. Last updated 2 months ago.
riboseqsequencinggeneregulationqualitycontrolvisualizationcoverage
4.88 score 17 scriptsbioc
ChIPseqR:Identifying Protein Binding Sites in High-Throughput Sequencing Data
ChIPseqR identifies protein binding sites from ChIP-seq and nucleosome positioning experiments. The model used to describe binding events was developed to locate nucleosomes but should flexible enough to handle other types of experiments as well.
Maintained by Peter Humburg. Last updated 5 months ago.
4.70 score 1 scriptsbioc
msgbsR:msgbsR: methylation sensitive genotyping by sequencing (MS-GBS) R functions
Pipeline for the anaysis of a MS-GBS experiment.
Maintained by Benjamin Mayne. Last updated 5 months ago.
immunooncologydifferentialmethylationdataimportepigeneticsmethylseq
4.48 score 1 scriptsbioc
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.
4.48 score 7 scriptsbioc
basecallQC:Working with Illumina Basecalling and Demultiplexing input and output files
The basecallQC package provides tools to work with Illumina bcl2Fastq (versions >= 2.1.7) software.Prior to basecalling and demultiplexing using the bcl2Fastq software, basecallQC functions allow the user to update Illumina sample sheets from versions <= 1.8.9 to >= 2.1.7 standards, clean sample sheets of common problems such as invalid sample names and IDs, create read and index basemasks and the bcl2Fastq command. Following the generation of basecalled and demultiplexed data, the basecallQC packages allows the user to generate HTML tables, plots and a self contained report of summary metrics from Illumina XML output files.
Maintained by Thomas Carroll. Last updated 5 months ago.
sequencinginfrastructuredataimportqualitycontrol
4.32 score 21 scripts
svilsen
STRMPS:Analysis of Short Tandem Repeat (STR) Massively Parallel Sequencing (MPS) Data
Loading, identifying, aggregating, manipulating, and analysing short tandem repeat regions of massively parallel sequencing data in forensic genetics. The analyses and framework implemented in this package relies on the papers of Vilsen et al. (2017) <doi:10.1016/j.fsigen.2017.01.017> and Vilsen et al. (2018) <doi:10.1016/j.fsigen.2018.04.003>. Note: that the parallelisation in the package relies on mclapply() and, thus, speed-ups will only be seen on UNIX based systems.
Maintained by Søren B. Vilsen. Last updated 16 days ago.
biostringspwalignshortreadiranges
4.30 scorebioc
GOTHiC:Binomial test for Hi-C data analysis
This is a Hi-C analysis package using a cumulative binomial test to detect interactions between distal genomic loci that have significantly more reads than expected by chance in Hi-C experiments. It takes mapped paired NGS reads as input and gives back the list of significant interactions for a given bin size in the genome.
Maintained by Borbala Mifsud. Last updated 5 months ago.
immunooncologysequencingpreprocessingepigeneticshic
4.30 score 6 scriptsbioc
IONiseR:Quality Assessment Tools for Oxford Nanopore MinION data
IONiseR provides tools for the quality assessment of Oxford Nanopore MinION data. It extracts summary statistics from a set of fast5 files and can be used either before or after base calling. In addition to standard summaries of the read-types produced, it provides a number of plots for visualising metrics relative to experiment run time or spatially over the surface of a flowcell.
Maintained by Mike Smith. Last updated 5 months ago.
qualitycontroldataimportsequencing
4.30 score 5 scriptsbioc
CircSeqAlignTk:A toolkit for end-to-end analysis of RNA-seq data for circular genomes
CircSeqAlignTk is designed for end-to-end RNA-Seq data analysis of circular genome sequences, from alignment to visualization. It mainly targets viroids which are composed of 246-401 nt circular RNAs. In addition, CircSeqAlignTk implements a tidy interface to generate synthetic sequencing data that mimic real RNA-Seq data, allowing developers to evaluate the performance of alignment tools and workflows.
Maintained by Jianqiang Sun. Last updated 5 months ago.
sequencingsmallrnaalignmentsoftware
4.30 score 3 scriptsbioc
BEAT:BEAT - BS-Seq Epimutation Analysis Toolkit
Model-based analysis of single-cell methylation data
Maintained by Kemal Akman. Last updated 5 months ago.
immunooncologygeneticsmethylseqsoftwarednamethylationepigenetics
4.30 score 3 scriptsbioc
profileplyr:Visualization and annotation of read signal over genomic ranges with profileplyr
Quick and straightforward visualization of read signal over genomic intervals is key for generating hypotheses from sequencing data sets (e.g. ChIP-seq, ATAC-seq, bisulfite/methyl-seq). Many tools both inside and outside of R and Bioconductor are available to explore these types of data, and they typically start with a bigWig or BAM file and end with some representation of the signal (e.g. heatmap). profileplyr leverages many Bioconductor tools to allow for both flexibility and additional functionality in workflows that end with visualization of the read signal.
Maintained by Tom Carroll. Last updated 5 months ago.
chipseqdataimportsequencingchiponchipcoverage
4.03 score 54 scriptsbioc
consensusDE:RNA-seq analysis using multiple algorithms
This package allows users to perform DE analysis using multiple algorithms. It seeks consensus from multiple methods. Currently it supports "Voom", "EdgeR" and "DESeq". It uses RUV-seq (optional) to remove unwanted sources of variation.
Maintained by Ashley J. Waardenberg. Last updated 5 months ago.
transcriptomicsmultiplecomparisonclusteringsequencingsoftware
4.00 score 10 scriptsbioc
octad:Open Cancer TherApeutic Discovery (OCTAD)
OCTAD provides a platform for virtually screening compounds targeting precise cancer patient groups. The essential idea is to identify drugs that reverse the gene expression signature of disease by tamping down over-expressed genes and stimulating weakly expressed ones. The package offers deep-learning based reference tissue selection, disease gene expression signature creation, pathway enrichment analysis, drug reversal potency scoring, cancer cell line selection, drug enrichment analysis and in silico hit validation. It currently covers ~20,000 patient tissue samples covering 50 cancer types, and expression profiles for ~12,000 distinct compounds.
Maintained by E. Chekalin. Last updated 5 months ago.
classificationgeneexpressionpharmacogeneticspharmacogenomicssoftwaregenesetenrichment
4.00 score 4 scriptsbioc
FastqCleaner:A Shiny Application for Quality Control, Filtering and Trimming of FASTQ Files
An interactive web application for quality control, filtering and trimming of FASTQ files. This user-friendly tool combines a pipeline for data processing based on Biostrings and ShortRead infrastructure, with a cutting-edge visual environment. Single-Read and Paired-End files can be locally processed. Diagnostic interactive plots (CG content, per-base sequence quality, etc.) are provided for both the input and output files.
Maintained by Leandro Roser. Last updated 5 months ago.
qualitycontrolsequencingsoftwaresangerseqsequencematchingcpp
4.00 score 4 scriptsbioc
Rbec:Rbec: a tool for analysis of amplicon sequencing data from synthetic microbial communities
Rbec is a adapted version of DADA2 for analyzing amplicon sequencing data from synthetic communities (SynComs), where the reference sequences for each strain exists. Rbec can not only accurately profile the microbial compositions in SynComs, but also predict the contaminants in SynCom samples.
Maintained by Pengfan Zhang. Last updated 5 months ago.
sequencingmicrobialstrainmicrobiomecpp
4.00 score 1 scriptsbioc
ChIPsim:Simulation of ChIP-seq experiments
A general framework for the simulation of ChIP-seq data. Although currently focused on nucleosome positioning the package is designed to support different types of experiments.
Maintained by Peter Humburg. Last updated 5 months ago.
4.00 score 3 scripts
yunuuuu
rsahmi:Single-Cell Analysis of Host-Microbiome Interactions
A computational resource designed to accurately detect microbial nucleic acids while filtering out contaminants and false-positive taxonomic assignments from standard transcriptomic sequencing of mammalian tissues. For more details, see Ghaddar (2023) <doi:10.1038/s43588-023-00507-1>. This implementation leverages the 'polars' package for fast and systematic microbial signal recovery and denoising from host tissue genomic sequencing.
Maintained by Yun Peng. Last updated 3 days ago.
3.90 score
rgyoung6
DBTCShiny:Dada-BLAST-Taxon Assign-Condense Metabarcode Analysis 'shiny' Application
Metabarcoding analysis using the 'DBTC' package is implemented here using 'shiny' in an interactive graphical user interface to conduct Metabarcode analyses and visualize and filter results.
Maintained by Robert G Young. Last updated 10 months ago.
3.74 score 1 scriptsrgyoung6
DBTC:Dada-BLAST-Taxon Assign-Condense Metabarcode Analysis
First using 'dada2' R tools to analyse metabarcode data, the 'DBTC' package then uses the BLAST algorithm to search unknown sequences against local databases, and then takes reduced matched results and provides best taxonomic assignments.
Maintained by Robert G Young. Last updated 11 months ago.
3.65 score 1 dependentsbioc
R453Plus1Toolbox:A package for importing and analyzing data from Roche's Genome Sequencer System
The R453Plus1 Toolbox comprises useful functions for the analysis of data generated by Roche's 454 sequencing platform. It adds functions for quality assurance as well as for annotation and visualization of detected variants, complementing the software tools shipped by Roche with their product. Further, a pipeline for the detection of structural variants is provided.
Maintained by Hans-Ulrich Klein. Last updated 5 months ago.
sequencinginfrastructuredataimportdatarepresentationvisualizationqualitycontrolreportwriting
3.48 score 10 scriptsbioc
vulcan:VirtUaL ChIP-Seq data Analysis using Networks
Vulcan (VirtUaL ChIP-Seq Analysis through Networks) is a package that interrogates gene regulatory networks to infer cofactors significantly enriched in a differential binding signature coming from ChIP-Seq data. In order to do so, our package combines strategies from different BioConductor packages: DESeq for data normalization, ChIPpeakAnno and DiffBind for annotation and definition of ChIP-Seq genomic peaks, csaw to define optimal peak width and viper for applying a regulatory network over a differential binding signature.
Maintained by Federico M. Giorgi. Last updated 5 months ago.
systemsbiologynetworkenrichmentgeneexpressionchipseq
3.38 score 12 scriptsbioc
OTUbase:Provides structure and functions for the analysis of OTU data
Provides a platform for Operational Taxonomic Unit based analysis
Maintained by Daniel Beck. Last updated 5 months ago.
3.30 scorebioc
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.
immunooncologytranscriptionsoftwaresequencingrnaseqcoverage
3.30 score 2 scripts
grafxzahl
genBaRcode:Analysis and Visualization Tools for Genetic Barcode Data
Provides the necessary functions to identify and extract a selection of already available barcode constructs (Cornils, K. et al. (2014) <doi:10.1093/nar/gku081>) and freely choosable barcode designs from next generation sequence (NGS) data. Furthermore, it offers the possibility to account for sequence errors, the calculation of barcode similarities and provides a variety of visualisation tools (Thielecke, L. et al. (2017) <doi:10.1038/srep43249>).
Maintained by Lars Thielecke. Last updated 19 days ago.
2.30 score 6 scripts