Showing 21 of total 21 results (show query)
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methrix:Fast and efficient summarization of generic bedGraph files from Bisufite sequencing
Bedgraph files generated by Bisulfite pipelines often come in various flavors. Critical downstream step requires summarization of these files into methylation/coverage matrices. This step of data aggregation is done by Methrix, including many other useful downstream functions.
Maintained by Anand Mayakonda. Last updated 5 months ago.
dnamethylationsequencingcoveragebedgraphbioinformaticsdna-methylation
19.5 match 31 stars 7.51 score 39 scripts 1 dependentsbioc
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.
annotationvisualizationdataimportzlibopensslcurl
5.0 match 12.66 score 6.7k scripts 481 dependentsbioc
methylKit:DNA methylation analysis from high-throughput bisulfite sequencing results
methylKit is an R package for DNA methylation analysis and annotation from high-throughput bisulfite sequencing. The package is designed to deal with sequencing data from RRBS and its variants, but also target-capture methods and whole genome bisulfite sequencing. It also has functions to analyze base-pair resolution 5hmC data from experimental protocols such as oxBS-Seq and TAB-Seq. Methylation calling can be performed directly from Bismark aligned BAM files.
Maintained by Altuna Akalin. Last updated 16 days ago.
dnamethylationsequencingmethylseqgenome-biologymethylationstatistical-analysisvisualizationcurlbzip2xz-utilszlibcpp
5.1 match 220 stars 11.80 score 578 scripts 3 dependentsbioc
plyranges:A fluent interface for manipulating GenomicRanges
A dplyr-like interface for interacting with the common Bioconductor classes Ranges and GenomicRanges. By providing a grammatical and consistent way of manipulating these classes their accessiblity for new Bioconductor users is hopefully increased.
Maintained by Michael Love. Last updated 5 months ago.
infrastructuredatarepresentationworkflowstepcoveragebioconductordata-analysisdplyrgenomic-rangesgenomicstidy-data
3.8 match 143 stars 12.60 score 1.9k scripts 20 dependentsbioc
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.
generegulationvisualizationdataimport
3.0 match 3 stars 9.28 score 35 scripts 19 dependentsbioc
RnBeads:RnBeads
RnBeads facilitates comprehensive analysis of various types of DNA methylation data at the genome scale.
Maintained by Fabian Mueller. Last updated 1 months ago.
dnamethylationmethylationarraymethylseqepigeneticsqualitycontrolpreprocessingbatcheffectdifferentialmethylationsequencingcpgislandimmunooncologytwochanneldataimport
4.0 match 6.85 score 169 scripts 1 dependentstanaylab
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.
3.3 match 4 stars 5.86 scorebioc
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.
3.5 match 3 stars 4.85 score 17 scriptsbioc
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.
technologymicroarraynormalization
4.0 match 4.30 score 4 scriptsbioc
methodical:Discovering genomic regions where methylation is strongly associated with transcriptional activity
DNA methylation is generally considered to be associated with transcriptional silencing. However, comprehensive, genome-wide investigation of this relationship requires the evaluation of potentially millions of correlation values between the methylation of individual genomic loci and expression of associated transcripts in a relatively large numbers of samples. Methodical makes this process quick and easy while keeping a low memory footprint. It also provides a novel method for identifying regions where a number of methylation sites are consistently strongly associated with transcriptional expression. In addition, Methodical enables housing DNA methylation data from diverse sources (e.g. WGBS, RRBS and methylation arrays) with a common framework, lifting over DNA methylation data between different genome builds and creating base-resolution plots of the association between DNA methylation and transcriptional activity at transcriptional start sites.
Maintained by Richard Heery. Last updated 2 months ago.
dnamethylationmethylationarraytranscriptiongenomewideassociationsoftwareopenjdk
3.5 match 4.65 score 14 scriptsbioc
igvShiny:igvShiny: a wrapper of Integrative Genomics Viewer (IGV - an interactive tool for visualization and exploration integrated genomic data)
This package is a wrapper of Integrative Genomics Viewer (IGV). It comprises an htmlwidget version of IGV. It can be used as a module in Shiny apps.
Maintained by Arkadiusz Gladki. Last updated 5 months ago.
softwareshinyappssequencingcoverage
1.9 match 37 stars 7.40 score 120 scriptsbnprks
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.
1.8 match 184 stars 7.48 score 172 scriptsbioc
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.
2.0 match 37 stars 6.71 score 14 scriptsbioc
rGenomeTracks:Integerated visualization of epigenomic data
rGenomeTracks package leverages the power of pyGenomeTracks software with the interactivity of R. pyGenomeTracks is a python software that offers robust method for visualizing epigenetic data files like narrowPeak, Hic matrix, TADs and arcs, however though, here is no way currently to use it within R interactive session. rGenomeTracks wrapped the whole functionality of pyGenomeTracks with additional utilites to make to more pleasant for R users.
Maintained by Omar Elashkar. Last updated 5 months ago.
3.9 match 3.30 score 2 scriptsbioc
musicatk:Mutational Signature Comprehensive Analysis Toolkit
Mutational signatures are carcinogenic exposures or aberrant cellular processes that can cause alterations to the genome. We created musicatk (MUtational SIgnature Comprehensive Analysis ToolKit) to address shortcomings in versatility and ease of use in other pre-existing computational tools. Although many different types of mutational data have been generated, current software packages do not have a flexible framework to allow users to mix and match different types of mutations in the mutational signature inference process. Musicatk enables users to count and combine multiple mutation types, including SBS, DBS, and indels. Musicatk calculates replication strand, transcription strand and combinations of these features along with discovery from unique and proprietary genomic feature associated with any mutation type. Musicatk also implements several methods for discovery of new signatures as well as methods to infer exposure given an existing set of signatures. Musicatk provides functions for visualization and downstream exploratory analysis including the ability to compare signatures between cohorts and find matching signatures in COSMIC V2 or COSMIC V3.
Maintained by Joshua D. Campbell. Last updated 5 months ago.
softwarebiologicalquestionsomaticmutationvariantannotation
1.7 match 13 stars 7.02 score 20 scriptsbioc
GenomicPlot:Plot profiles of next generation sequencing data in genomic features
Visualization of next generation sequencing (NGS) data is essential for interpreting high-throughput genomics experiment results. 'GenomicPlot' facilitates plotting of NGS data in various formats (bam, bed, wig and bigwig); both coverage and enrichment over input can be computed and displayed with respect to genomic features (such as UTR, CDS, enhancer), and user defined genomic loci or regions. Statistical tests on signal intensity within user defined regions of interest can be performed and represented as boxplots or bar graphs. Parallel processing is used to speed up computation on multicore platforms. In addition to genomic plots which is suitable for displaying of coverage of genomic DNA (such as ChIPseq data), metagenomic (without introns) plots can also be made for RNAseq or CLIPseq data as well.
Maintained by Shuye Pu. Last updated 2 months ago.
alternativesplicingchipseqcoveragegeneexpressionrnaseqsequencingsoftwaretranscriptionvisualizationannotation
1.9 match 3 stars 5.62 score 4 scriptsbioc
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.
visualizationthirdpartyclientgenomebrowsers
1.2 match 43 stars 8.31 score 118 scriptstdhock
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.
2.0 match 4 stars 4.65 score 37 scriptsbioc
InPAS:Identify Novel Alternative PolyAdenylation Sites (PAS) from RNA-seq data
Alternative polyadenylation (APA) is one of the important post- transcriptional regulation mechanisms which occurs in most human genes. InPAS facilitates the discovery of novel APA sites and the differential usage of APA sites from RNA-Seq data. It leverages cleanUpdTSeq to fine tune identified APA sites by removing false sites.
Maintained by Jianhong Ou. Last updated 2 months ago.
alternative polyadenylationdifferential polyadenylation site usagerna-seqgene regulationtranscription
1.8 match 4.30 score 1 scriptsdanieleweeks
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.
2.3 match 1.00 score 8 scriptsbioc
nearBynding:Discern RNA structure proximal to protein binding
Provides a pipeline to discern RNA structure at and proximal to the site of protein binding within regions of the transcriptome defined by the user. CLIP protein-binding data can be input as either aligned BAM or peak-called bedGraph files. RNA structure can either be predicted internally from sequence or users have the option to input their own RNA structure data. RNA structure binding profiles can be visually and quantitatively compared across multiple formats.
Maintained by Veronica Busa. Last updated 5 months ago.
visualizationmotifdiscoverydatarepresentationstructuralpredictionclusteringmultiplecomparison
0.5 match 4.08 score 12 scripts