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This package implements five methods proposed by Resnik, Schlicker, Jiang, Lin and Wang respectively for measuring semantic similarities among DO terms and gene products. Enrichment analyses including hypergeometric model and gene set enric

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bioMate-AI/biomate-bioconductor-kb7962026年6月21日 更新

A toolset for deciphering and managing biological sequences.

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bioMate-AI/biomate-bioconductor-kb7962026年6月21日 更新

KEGGGraph is an interface between KEGG pathway and graph object as well as a collection of tools to analyze, dissect and visualize these graphs. It parses the regularly updated KGML (KEGG XML) files into graph models maintaining all essenti

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bioMate-AI/biomate-bioconductor-kb7962026年6月21日 更新

cogeqc aims to facilitate systematic quality checks on standard comparative genomics analyses to help researchers detect issues and select the most suitable parameters for each data set. cogeqc can be used to asses: i. genome assembly and annotation quality with BUSCOs and comparisons of statistics with publicly available genomes on the NCBI; ii. orthogroup inference using a protein domain-based approach and; iii. synteny detection using synteny network properties. There are also data visualizat

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bioMate-AI/biomate-bioconductor-kb7962026年6月21日 更新

The 'enrichplot' package implements several visualization methods for interpreting functional enrichment results obtained from ORA or GSEA analysis. It is mainly designed to work with the 'clusterProfiler' package suite. All the visualizati

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bioMate-AI/biomate-bioconductor-kb7962026年6月21日 更新

Memory efficient string containers, string matching algorithms, and other utilities, for fast manipulation of large biological sequences or sets of sequences.

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bioMate-AI/biomate-bioconductor-kb7962026年6月21日 更新

The ability to efficiently represent and manipulate genomic annotations and alignments is playing a central role when it comes to analyzing high-throughput sequencing data (a.k.a. NGS data). The GenomicRanges package defines general purpose

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bioMate-AI/biomate-bioconductor-kb7962026年6月21日 更新

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 enc

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bioMate-AI/biomate-bioconductor-kb7962026年6月21日 更新

Systematic 3D interaction calls and differential analysis for Hi-C and HiChIP. The HiC-DC+ (Hi-C/HiChIP direct caller plus) package enables principled statistical analysis of Hi-C and HiChIP data sets – including calling significant interactions within a single experiment and performing differential analysis between conditions given replicate experiments – to facilitate global integrative studies. HiC-DC+ estimates significant interactions in a Hi-C or HiChIP experiment directly from the raw con

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bioMate-AI/biomate-bioconductor-kb7962026年6月21日 更新

This package is a implementation of biclustering ensemble method MoSBi (Molecular signature Identification from Biclustering). MoSBi provides standardized interfaces for biclustering results and can combine their results with a multi-algorithm ensemble approach to compute robust ensemble biclusters on molecular omics data. This is done by computing similarity networks of biclusters and filtering for overlaps using a custom error model. After that, the louvain modularity it used to extract biclus

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bioMate-AI/biomate-bioconductor-kb7962026年6月21日 更新

MHC (major histocompatibility complex) molecules are cell surface complexes that present antigens to T cells. The repertoire of antigens presented in a given genetic background largely depends on the sequence of the encoded MHC molecules, and thus, in humans, on the highly variable HLA (human leukocyte antigen) genes of the hyperpolymorphic HLA locus. More than 28,000 different HLA alleles have been reported, with significant differences in allele frequencies between human populations worldwide

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bioMate-AI/biomate-bioconductor-kb7962026年6月21日 更新

This tool uses the label-tree function from HyPhy to annotate a phylogenetic tree. It allows users to select a subset of leaves using either a regular expression or a list of sequence names, and then apply a specified label to these selecte

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bioMate-AI/biomate-bioconductor-kb7962026年6月21日 更新

Tools for finding bumps in genomic data

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bioMate-AI/biomate-bioconductor-kb7962026年6月21日 更新

R generic interface to Hi-C contact matrices in `.(m)cool`, `.hic` or HiC-Pro derived formats, as well as other Hi-C processed file formats. Contact matrices can be partially parsed using a random access method, allowing a memory-efficient representation of Hi-C data in R. The `HiCExperiment` class stores the Hi-C contacts parsed from local contact matrix files. `HiCExperiment` instances can be further investigated in R using the `HiContacts` analysis package.

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bioMate-AI/biomate-bioconductor-kb7962026年6月21日 更新

epigraHMM provides a set of tools for the analysis of epigenomic data based on hidden Markov Models. It contains two separate peak callers, one for consensus peaks from biological or technical replicates, and one for differential peaks from multi-replicate multi-condition experiments. In differential peak calling, epigraHMM provides window-specific posterior probabilities associated with every possible combinatorial pattern of read enrichment across conditions.

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bioMate-AI/biomate-bioconductor-kb7962026年6月21日 更新

doubletrouble aims to identify duplicated genes from whole-genome protein sequences and classify them based on their modes of duplication. The duplication modes are i. segmental duplication (SD); ii. tandem duplication (TD); iii. proximal duplication (PD); iv. transposed duplication (TRD) and; v. dispersed duplication (DD). Transposon-derived duplicates (TRD) can be further subdivided into rTRD (retrotransposon-derived duplication) and dTRD (DNA transposon-derived duplication). If users want a s

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bioMate-AI/biomate-bioconductor-kb7962026年6月21日 更新

Microbiome time series simulation with generalized Lotka-Volterra model, Self-Organized Instability (SOI), and other models. Hubbell's Neutral model is used to determine the abundance matrix. The resulting abundance matrix is applied to (Tree)SummarizedExperiment objects.

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bioMate-AI/biomate-bioconductor-kb7962026年6月21日 更新

BEER implements a Bayesian model for analyzing phage-immunoprecipitation sequencing (PhIP-seq) data. Given a PhIPData object, BEER returns posterior probabilities of enriched antibody responses, point estimates for the relative fold-change in comparison to negative control samples, and more. Additionally, BEER provides a convenient implementation for using edgeR to identify enriched antibody responses.

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bioMate-AI/biomate-bioconductor-kb7962026年6月21日 更新

Epialleles are specific DNA methylation patterns that are mitotically and/or meiotically inherited. This package calls and reports cytosine methylation as well as frequencies of hypermethylated epialleles at the level of genomic regions or individual cytosines in next-generation sequencing data using binary alignment map (BAM) files as an input. Among other things, this package can also extract and visualise methylation patterns and assess allele specificity of methylation.

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bioMate-AI/biomate-bioconductor-kb7962026年6月21日 更新

Graph objects from pathway topology derived from KEGG, Panther, PathBank, PharmGKB, Reactome SMPDB and WikiPathways databases.

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bioMate-AI/biomate-bioconductor-kb7962026年6月21日 更新

Implements the circular binary segmentation (CBS) algorithm to segment DNA copy number data and identify genomic regions with abnormal copy number.

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bioMate-AI/biomate-bioconductor-kb7962026年6月21日 更新

Functions that are needed by many other packages or which replace R functions.

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bioMate-AI/biomate-bioconductor-kb7962026年6月21日 更新

Provides a high-level R interface to CoreArray Genomic Data Structure (GDS) data files. GDS is portable across platforms with hierarchical structure to store multiple scalable array-oriented data sets with metadata information. It is suited

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bioMate-AI/biomate-bioconductor-kb7962026年6月21日 更新

topGO package provides tools for testing GO terms while accounting for the topology of the GO graph. Different test statistics and different methods for eliminating local similarities and dependencies between GO terms can be implemented and

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bioMate-AI/biomate-bioconductor-kb7962026年6月21日 更新