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bioconductor-cancersubtypes
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public |
Cancer subtypes identification, validation and visualization based on multiple genomic data sets
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2023-07-18 |
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bioconductor-pfp
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public |
Pathway Fingerprint Framework in R
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2023-07-18 |
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bioconductor-eegc
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public |
Engineering Evaluation by Gene Categorization (eegc)
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2023-07-18 |
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bioconductor-multisight
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public |
Multi-omics Classification, Functional Enrichment and Network Inference analysis
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2023-07-18 |
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bioconductor-ripat
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public |
Retroviral Integration Pattern Analysis Tool (RIPAT)
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2023-07-18 |
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bioconductor-kissde
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public |
Retrieves Condition-Specific Variants in RNA-Seq Data
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2023-07-18 |
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bioconductor-crisprseekplus
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public |
crisprseekplus
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2023-07-18 |
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r-qiime2r
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public |
Import qiime2 artifacts to R.
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2023-07-17 |
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r-breakaway
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public |
Understanding the drivers of microbial diversity is an important frontier of microbial ecology, and investigating the diversity of samples from microbial ecosystems is a common step in any microbiome analysis. 'breakaway' is the premier package for statistical analysis of microbial diversity. 'breakaway' implements the latest and greatest estimates of species richness, as well as the most commonly used estimates. Methods uniquely available in this package include objective Bayes estimators described in Barger and Bunge (2010) <doi:10.1214/10-BA527>, frequency-ratio-based estimators described in Willis and Bunge (2015) <doi:10.1111/biom.12332>, and as described in Willis, Whitman, and Bunge (2016) <doi:10.1111/rssc.12206>, a linear modeling approach for detecting changes in diversity.
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2023-07-17 |
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bioconductor-msstatssamplesize
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public |
Simulation tool for optimal design of high-dimensional MS-based proteomics experiment
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2023-07-17 |
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r-xgr
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public |
The central goal of XGR by Fang et al. (2016) <doi:10.1186/s13073-016-0384-y> is to provide a data interpretation system necessary to do "big data" science. It is designed to make a user-defined gene or SNP list (or genomic regions) more interpretable by comprehensively utilising ontology annotations and interaction networks to reveal relationships and enhance opportunities for biological discovery. XGR is unique in supporting a broad range of ontologies (including knowledge of biological and molecular functions, pathways, diseases and phenotypes - in both human and mouse) and different types of networks (including functional, physical and pathway interactions). There are two core functionalities of XGR. The first is to provide basic infrastructures for easy access to built-in ontologies and networks. The second is to support data interpretations via 1) enrichment analysis using either built-in or custom ontologies, 2) similarity analysis for calculating semantic similarity between genes (or SNPs) based on their ontology annotation profiles, 3) network analysis for identification of gene networks given a query list of (significant) genes, SNPs or genomic regions, and 4) annotation analysis for interpreting genomic regions using co-localised functional genomic annotations (such as open chromatin, epigenetic marks, TF binding sites and genomic segments) and using nearby gene annotations (by ontologies). Together with its web app, XGR aims to provide a user-friendly tool for exploring genomic relations at the gene, SNP and genomic region level.
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2023-07-17 |
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r-sigtree
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public |
Provides tools to identify and visualize branches in a phylogenetic tree that are significantly responsive to some intervention, taking as primary inputs a phylogenetic tree (of class phylo) and a data frame (or matrix) of corresponding tip (OTU) labels and p-values.
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2023-07-17 |
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bioconductor-traviz
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public |
Trajectory functions for visualization and interpretation.
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2023-07-17 |
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r-nanopore
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public |
R methods, associated with Nanopore tutorials, for analysis and presentation of Oxford Nanopore Technologies long-read sequence data
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2023-07-17 |
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bioconductor-chic
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public |
Quality Control Pipeline for ChIP-Seq Data
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2023-07-17 |
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r-metalonda
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public |
Identify time intervals of differentially abundant metagenomics features in longitudinal studies.
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2023-07-17 |
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bioconductor-refplus
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public |
A function set for the Extrapolation Strategy (RMA+) and Extrapolation Averaging (RMA++) methods.
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2023-07-17 |
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bioconductor-metab
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public |
Metab: An R Package for a High-Throughput Analysis of Metabolomics Data Generated by GC-MS.
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2023-07-17 |
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r-millefy
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public |
Millefy: Genome browser-like visualization of single-cell RNA-seq dataset.
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2023-07-16 |
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bioconductor-oder
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public |
Optimising the Definition of Expressed Regions
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2023-07-16 |
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bioconductor-mmappr2
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public |
Mutation Mapping Analysis Pipeline for Pooled RNA-Seq
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2023-07-16 |
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transdecoder
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public |
TransDecoder identifies candidate coding regions within transcript sequences, such as those generated by de novo RNA-Seq transcript assembly using Trinity, or constructed based on RNA-Seq alignments to the genome using Tophat and Cufflinks.
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2023-07-16 |
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r-dartr
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public |
Functions are provided that facilitate the import and analysis of SNP (single nucleotide polymorphism) and silicodart (presence/absence) data. The main focus is on data generated by DarT (Diversity Arrays Technology). However, once SNP or related fragment presence/absence data from any source is imported into a genlight object many of the functions can be used. Functions are available for input and output of SNP and silicodart data, for reporting on and filtering on various criteria (e.g. CallRate, Heterozygosity, Reproducibility, maximum allele frequency). Advanced filtering is based on Linkage Disequilibrium and HWE (Hardy-Weinberg equilibrium). Other functions are available for visualization after PCoA (Principle Coordinate Analysis), or to facilitate transfer of data between genlight/genind objects and newhybrids, related, phylip, structure, faststructure packages.
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2023-07-16 |
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bioconductor-dmrforpairs
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public |
DMRforPairs: identifying Differentially Methylated Regions between unique samples using array based methylation profiles
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2023-07-16 |
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bioconductor-pwrewas
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public |
A user-friendly tool for comprehensive power estimation for epigenome wide association studies (EWAS)
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2023-07-16 |
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bioconductor-proteasy
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public |
Protease Mapping
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2023-07-16 |
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r-interpretmsspectrum
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public |
Annotate and interpret deconvoluted mass spectra (mass*intensity pairs) from high resolution mass spectrometry devices.
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2023-07-16 |
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snakemake-wrapper-utils
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public |
A collection of utility functions and classes for Snakemake wrappers.
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2023-07-16 |
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kmtricks
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public |
A k-mer matrix framework
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2023-07-16 |
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peekseq
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public |
De novo protein-coding potential calculator using a k-mer approach
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2023-07-16 |
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flair
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public |
Correction, isoform definition, and alternative splicing analysis of noisy reads (ONT and PacBio).
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2023-07-16 |
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perl-file-listing
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public |
parse directory listing
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2023-07-16 |
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bioconductor-biomm
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public |
BioMM: Biological-informed Multi-stage Machine learning framework for phenotype prediction using omics data
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2023-07-16 |
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bioconductor-mafh5.gnomad.v3.1.1.grch38
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public |
Minor allele frequency data from gnomAD version 3.1.1 for GRCh38
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2023-07-16 |
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bioconductor-foldgo
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public |
Package for Fold-specific GO Terms Recognition
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2023-07-16 |
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perl-perldoc
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public |
Documentation Framework for Perl
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2023-07-16 |
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bioconductor-nxtirfcore
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public |
Core Engine for NxtIRF: a User-Friendly Intron Retention and Alternative Splicing Analysis using the IRFinder Engine
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2023-07-15 |
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bioconductor-sispa
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public |
SISPA: Method for Sample Integrated Set Profile Analysis
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2023-07-15 |
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fastphylo
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public |
Fastphylo is software project containing the implementations of the algorithms "Fast Computation of Distance Estimators" and "Fast Neighbor Joining".
|
2023-07-15 |
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bioconductor-dasper
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public |
Detecting abberant splicing events from RNA-sequencing data
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2023-07-15 |
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bioconductor-metagene
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public |
A package to produce metagene plots
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2023-07-15 |
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r-dnet
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public |
The focus of the dnet by Fang and Gough (2014) <doi:10.1186/s13073-014-0064-8> is to make sense of omics data (such as gene expression and mutations) from different angles including: integration with molecular networks, enrichments using ontologies, and relevance to gene evolutionary ages. Integration is achieved to identify a gene subnetwork from the whole gene network whose nodes/genes are labelled with informative data (such as the significant levels of differential expression or survival risks). To help make sense of identified gene networks, enrichment analysis is also supported using a wide variety of pre-compiled ontologies and phylostratific gene age information in major organisms including: human, mouse, rat, chicken, C.elegans, fruit fly, zebrafish and arabidopsis. Add-on functionalities are supports for calculating semantic similarity between ontology terms (and between genes) and for calculating network affinity based on random walk; both can be done via high-performance parallel computing.
|
2023-07-15 |
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bioconductor-genbankr
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public |
Parsing GenBank files into semantically useful objects
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2023-07-14 |
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bioconductor-compartmap
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public |
Higher-order chromatin domain inference in single cells from scRNA-seq and scATAC-seq
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2023-07-14 |
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r-metap
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public |
The canonical way to perform meta-analysis involves using effect sizes. When they are not available this package provides a number of methods for meta-analysis of significance values including the methods of Edgington, Fisher, Lancaster, Stouffer, Tippett, and Wilkinson; a number of data-sets to replicate published results; and a routine for graphical display.
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2023-07-14 |
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bioconductor-rlseq
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public |
RLSeq: An analysis package for R-loop mapping data
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2023-07-14 |
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bioconductor-mbomic
|
public |
Integrative analysis of the microbiome and metabolome
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2023-07-14 |
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bioconductor-alpine
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public |
alpine
|
2023-07-14 |
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bioconductor-dpeak
|
public |
dPeak (Deconvolution of Peaks in ChIP-seq Analysis)
|
2023-07-13 |
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bioconductor-alpinedata
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public |
Data for the alpine package vignette
|
2023-07-13 |
