R-universe search: needs:beanplot

bioc

minfi:Analyze Illumina Infinium DNA methylation arrays

Tools to analyze & visualize Illumina Infinium methylation arrays.

Maintained by Kasper Daniel Hansen. Last updated 4 months ago.

immunooncology dnamethylation differentialmethylation epigenetics microarray methylationarray multichannel twochannel dataimport normalization preprocessing qualitycontrol

60 stars 12.82 score 996 scripts 27 dependents

bioc

methylumi:Handle Illumina methylation data

This package provides classes for holding and manipulating Illumina methylation data. Based on eSet, it can contain MIAME information, sample information, feature information, and multiple matrices of data. An "intelligent" import function, methylumiR can read the Illumina text files and create a MethyLumiSet. methylumIDAT can directly read raw IDAT files from HumanMethylation27 and HumanMethylation450 microarrays. Normalization, background correction, and quality control features for GoldenGate, Infinium, and Infinium HD arrays are also included.

Maintained by Sean Davis. Last updated 5 months ago.

dnamethylation twochannel preprocessing qualitycontrol cpgisland

9 stars 9.90 score 89 scripts 9 dependents

bioc

netZooR:Unified methods for the inference and analysis of gene regulatory networks

netZooR unifies the implementations of several Network Zoo methods (netzoo, netzoo.github.io) into a single package by creating interfaces between network inference and network analysis methods. Currently, the package has 3 methods for network inference including PANDA and its optimized implementation OTTER (network reconstruction using mutliple lines of biological evidence), LIONESS (single-sample network inference), and EGRET (genotype-specific networks). Network analysis methods include CONDOR (community detection), ALPACA (differential community detection), CRANE (significance estimation of differential modules), MONSTER (estimation of network transition states). In addition, YARN allows to process gene expresssion data for tissue-specific analyses and SAMBAR infers missing mutation data based on pathway information.

Maintained by Tara Eicher. Last updated 14 days ago.

networkinference network generegulation geneexpression transcription microarray graphandnetwork gene-regulatory-network transcription-factors

105 stars 7.98 score

bioc

wateRmelon:Illumina DNA methylation array normalization and metrics

15 flavours of betas and three performance metrics, with methods for objects produced by methylumi and minfi packages.

Maintained by Leo C Schalkwyk. Last updated 4 months ago.

dnamethylation microarray twochannel preprocessing qualitycontrol

7.73 score 247 scripts 2 dependents

bioc

shinyMethyl:Interactive visualization for Illumina methylation arrays

Interactive tool for visualizing Illumina methylation array data. Both the 450k and EPIC array are supported.

Maintained by Jean-Philippe Fortin. Last updated 5 months ago.

dnamethylation microarray twochannel preprocessing qualitycontrol methylationarray

5 stars 7.34 score 42 scripts

bioc

missMethyl:Analysing Illumina HumanMethylation BeadChip Data

Normalisation, testing for differential variability and differential methylation and gene set testing for data from Illumina's Infinium HumanMethylation arrays. The normalisation procedure is subset-quantile within-array normalisation (SWAN), which allows Infinium I and II type probes on a single array to be normalised together. The test for differential variability is based on an empirical Bayes version of Levene's test. Differential methylation testing is performed using RUV, which can adjust for systematic errors of unknown origin in high-dimensional data by using negative control probes. Gene ontology analysis is performed by taking into account the number of probes per gene on the array, as well as taking into account multi-gene associated probes.

Maintained by Belinda Phipson. Last updated 30 days ago.

normalization dnamethylation methylationarray genomicvariation geneticvariability differentialmethylation genesetenrichment

7.24 score 300 scripts 1 dependents

bioc

RnBeads:RnBeads

RnBeads facilitates comprehensive analysis of various types of DNA methylation data at the genome scale.

Maintained by Fabian Mueller. Last updated 2 months ago.

dnamethylation methylationarray methylseq epigenetics qualitycontrol preprocessing batcheffect differentialmethylation sequencing cpgisland immunooncology twochannel dataimport

6.85 score 169 scripts 1 dependents

bioc

SIAMCAT:Statistical Inference of Associations between Microbial Communities And host phenoTypes

Pipeline for Statistical Inference of Associations between Microbial Communities And host phenoTypes (SIAMCAT). A primary goal of analyzing microbiome data is to determine changes in community composition that are associated with environmental factors. In particular, linking human microbiome composition to host phenotypes such as diseases has become an area of intense research. For this, robust statistical modeling and biomarker extraction toolkits are crucially needed. SIAMCAT provides a full pipeline supporting data preprocessing, statistical association testing, statistical modeling (LASSO logistic regression) including tools for evaluation and interpretation of these models (such as cross validation, parameter selection, ROC analysis and diagnostic model plots).

Maintained by Jakob Wirbel. Last updated 5 months ago.

immunooncology metagenomics classification microbiome sequencing preprocessing clustering featureextraction geneticvariability multiplecomparison regression

6.72 score 147 scripts

bioc

ChAMP:Chip Analysis Methylation Pipeline for Illumina HumanMethylation450 and EPIC

The package includes quality control metrics, a selection of normalization methods and novel methods to identify differentially methylated regions and to highlight copy number alterations.

Maintained by Yuan Tian. Last updated 5 months ago.

microarray methylationarray normalization twochannel copynumber dnamethylation

6.50 score 278 scripts

bioc

quantro:A test for when to use quantile normalization

A data-driven test for the assumptions of quantile normalization using raw data such as objects that inherit eSets (e.g. ExpressionSet, MethylSet). Group level information about each sample (such as Tumor / Normal status) must also be provided because the test assesses if there are global differences in the distributions between the user-defined groups.

Maintained by Stephanie Hicks. Last updated 5 months ago.

normalization preprocessing multiplecomparison microarray sequencing

6.40 score 69 scripts 2 dependents

bioc

recountmethylation:Access and analyze public DNA methylation array data compilations

Resources for cross-study analyses of public DNAm array data from NCBI GEO repo, produced using Illumina's Infinium HumanMethylation450K (HM450K) and MethylationEPIC (EPIC) platforms. Provided functions enable download, summary, and filtering of large compilation files. Vignettes detail background about file formats, example analyses, and more. Note the disclaimer on package load and consult the main manuscripts for further info.

Maintained by Sean K Maden. Last updated 5 months ago.

dnamethylation epigenetics microarray methylationarray experimenthub

9 stars 6.28 score 9 scripts

bioc

lumi:BeadArray Specific Methods for Illumina Methylation and Expression Microarrays

The lumi package provides an integrated solution for the Illumina microarray data analysis. It includes functions of Illumina BeadStudio (GenomeStudio) data input, quality control, BeadArray-specific variance stabilization, normalization and gene annotation at the probe level. It also includes the functions of processing Illumina methylation microarrays, especially Illumina Infinium methylation microarrays.

Maintained by Lei Huang. Last updated 5 months ago.

microarray onechannel preprocessing dnamethylation qualitycontrol twochannel

6.26 score 294 scripts 5 dependents

bioc

iNETgrate:Integrates DNA methylation data with gene expression in a single gene network

The iNETgrate package provides functions to build a correlation network in which nodes are genes. DNA methylation and gene expression data are integrated to define the connections between genes. This network is used to identify modules (clusters) of genes. The biological information in each of the resulting modules is represented by an eigengene. These biological signatures can be used as features e.g., for classification of patients into risk categories. The resulting biological signatures are very robust and give a holistic view of the underlying molecular changes.

Maintained by Habil Zare. Last updated 5 months ago.

geneexpression rnaseq dnamethylation networkinference network graphandnetwork biomedicalinformatics systemsbiology transcriptomics classification clustering dimensionreduction principalcomponent mrnamicroarray normalization geneprediction kegg survival core-services

74 stars 6.21 score 1 scripts

bioc

ENmix:Quality control and analysis tools for Illumina DNA methylation BeadChip

Tools for quanlity control, analysis and visulization of Illumina DNA methylation array data.

Maintained by Zongli Xu. Last updated 18 days ago.

dnamethylation preprocessing qualitycontrol twochannel microarray onechannel methylationarray batcheffect normalization dataimport regression principalcomponent epigenetics multichannel differentialmethylation immunooncology

6.01 score 115 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

2 stars 5.94 score 18 scripts

bioc

MetaNeighbor:Single cell replicability analysis

MetaNeighbor allows users to quantify cell type replicability across datasets using neighbor voting.

Maintained by Stephan Fischer. Last updated 5 months ago.

immunooncology geneexpression go multiplecomparison singlecell transcriptomics

5.89 score 78 scripts

bioc

deconvR:Simulation and Deconvolution of Omic Profiles

This package provides a collection of functions designed for analyzing deconvolution of the bulk sample(s) using an atlas of reference omic signature profiles and a user-selected model. Users are given the option to create or extend a reference atlas and,also simulate the desired size of the bulk signature profile of the reference cell types.The package includes the cell-type-specific methylation atlas and, Illumina Epic B5 probe ids that can be used in deconvolution. Additionally,we included BSmeth2Probe, to make mapping WGBS data to their probe IDs easier.

Maintained by Irem B. Gündüz. Last updated 5 months ago.

dnamethylation regression geneexpression rnaseq singlecell statisticalmethod transcriptomics bioconductor-package deconvolution dna-methylation omics

10 stars 5.78 score 15 scripts

bioc

methylclock:Methylclock - DNA methylation-based clocks

This package allows to estimate chronological and gestational DNA methylation (DNAm) age as well as biological age using different methylation clocks. Chronological DNAm age (in years) : Horvath's clock, Hannum's clock, BNN, Horvath's skin+blood clock, PedBE clock and Wu's clock. Gestational DNAm age : Knight's clock, Bohlin's clock, Mayne's clock and Lee's clocks. Biological DNAm clocks : Levine's clock and Telomere Length's clock.

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

dnamethylation biologicalquestion preprocessing statisticalmethod normalization cpp

39 stars 5.52 score 28 scripts

bioc

conumee:Enhanced copy-number variation analysis using Illumina DNA methylation arrays

This package contains a set of processing and plotting methods for performing copy-number variation (CNV) analysis using Illumina 450k or EPIC methylation arrays.

Maintained by Volker Hovestadt. Last updated 5 months ago.

copynumbervariation dnamethylation methylationarray microarray normalization preprocessing qualitycontrol software

5.48 score 30 scripts

bioc

bigmelon:Illumina methylation array analysis for large experiments

Methods for working with Illumina arrays using gdsfmt.

Maintained by Leonard C. Schalkwyk. Last updated 5 months ago.

dnamethylation microarray twochannel preprocessing qualitycontrol methylationarray dataimport cpgisland

5.47 score 21 scripts

bioc

VanillaICE:A Hidden Markov Model for high throughput genotyping arrays

Hidden Markov Models for characterizing chromosomal alteration in high throughput SNP arrays.

Maintained by Robert Scharpf. Last updated 5 months ago.

copynumbervariation

5.36 score 63 scripts 1 dependents

bioc

methylCC:Estimate the cell composition of whole blood in DNA methylation samples

A tool to estimate the cell composition of DNA methylation whole blood sample measured on any platform technology (microarray and sequencing).

Maintained by Stephanie C. Hicks. Last updated 5 months ago.

microarray sequencing dnamethylation methylationarray methylseq wholegenome

19 stars 5.18 score 8 scripts

bioc

DepecheR:Determination of essential phenotypic elements of clusters in high-dimensional entities

The purpose of this package is to identify traits in a dataset that can separate groups. This is done on two levels. First, clustering is performed, using an implementation of sparse K-means. Secondly, the generated clusters are used to predict outcomes of groups of individuals based on their distribution of observations in the different clusters. As certain clusters with separating information will be identified, and these clusters are defined by a sparse number of variables, this method can reduce the complexity of data, to only emphasize the data that actually matters.

Maintained by Jakob Theorell. Last updated 5 months ago.

software cellbasedassays transcription differentialexpression datarepresentation immunooncology transcriptomics classification clustering dimensionreduction featureextraction flowcytometry rnaseq singlecell visualization cpp

5.08 score 15 scripts

bioc

shinyepico:ShinyÉPICo

ShinyÉPICo is a graphical pipeline to analyze Illumina DNA methylation arrays (450k or EPIC). It allows to calculate differentially methylated positions and differentially methylated regions in a user-friendly interface. Moreover, it includes several options to export the results and obtain files to perform downstream analysis.

Maintained by Octavio Morante-Palacios. Last updated 5 months ago.

differentialmethylation dnamethylation microarray preprocessing qualitycontrol

5 stars 5.00 score 1 scripts

r-forge

plasma:Partial LeAst Squares for Multiomic Analysis

Contains tools for supervised analyses of incomplete, overlapping multiomics datasets. Applies partial least squares in multiple steps to find models that predict survival outcomes. See Yamaguchi et al. (2023) <doi:10.1101/2023.03.10.532096>.

Maintained by Kevin R. Coombes. Last updated 2 months ago.

4.97 score 13 scripts

bioc

crlmm:Genotype Calling (CRLMM) and Copy Number Analysis tool for Affymetrix SNP 5.0 and 6.0 and Illumina arrays

Faster implementation of CRLMM specific to SNP 5.0 and 6.0 arrays, as well as a copy number tool specific to 5.0, 6.0, and Illumina platforms.

Maintained by Benilton S Carvalho. Last updated 28 days ago.

microarray preprocessing snp copynumbervariation

4.78 score 37 scripts 3 dependents

bioc

MethylAid:Visual and interactive quality control of large Illumina DNA Methylation array data sets

A visual and interactive web application using RStudio's shiny package. Bad quality samples are detected using sample-dependent and sample-independent controls present on the array and user adjustable thresholds. In depth exploration of bad quality samples can be performed using several interactive diagnostic plots of the quality control probes present on the array. Furthermore, the impact of any batch effect provided by the user can be explored.

Maintained by L.J.Sinke. Last updated 5 months ago.

dnamethylation methylationarray microarray twochannel qualitycontrol batcheffect visualization gui

4.51 score 16 scripts

bioc

yarn:YARN: Robust Multi-Condition RNA-Seq Preprocessing and Normalization

Expedite large RNA-Seq analyses using a combination of previously developed tools. YARN is meant to make it easier for the user in performing basic mis-annotation quality control, filtering, and condition-aware normalization. YARN leverages many Bioconductor tools and statistical techniques to account for the large heterogeneity and sparsity found in very large RNA-seq experiments.

Maintained by Joseph N Paulson. Last updated 5 months ago.

software qualitycontrol geneexpression sequencing preprocessing normalization annotation visualization clustering

4.49 score 31 scripts

bioc

MAGAR:MAGAR: R-package to compute methylation Quantitative Trait Loci (methQTL) from DNA methylation and genotyping data

"Methylation-Aware Genotype Association in R" (MAGAR) computes methQTL from DNA methylation and genotyping data from matched samples. MAGAR uses a linear modeling stragety to call CpGs/SNPs that are methQTLs. MAGAR accounts for the local correlation structure of CpGs.

Maintained by Michael Scherer. Last updated 5 months ago.

regression epigenetics dnamethylation snp geneticvariability methylationarray microarray cpgisland methylseq sequencing mrnamicroarray preprocessing copynumbervariation twochannel immunooncology differentialmethylation batcheffect qualitycontrol dataimport network clustering graphandnetwork

4.30 score 3 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

4.23 score 28 scripts

bioc

funtooNorm:Normalization Procedure for Infinium HumanMethylation450 BeadChip Kit

Provides a function to normalize Illumina Infinium Human Methylation 450 BeadChip (Illumina 450K), correcting for tissue and/or cell type.

Maintained by Kathleen Klein. Last updated 5 months ago.

dnamethylation preprocessing normalization

3.70 score

bioc

MinimumDistance:A Package for De Novo CNV Detection in Case-Parent Trios

Analysis of de novo copy number variants in trios from high-dimensional genotyping platforms.

Maintained by Robert Scharpf. Last updated 5 months ago.

microarray snp copynumbervariation

3.60 score 10 scripts

rmar073

regplot:Enhanced Regression Nomogram Plot

A function to plot a regression nomogram of regression objects. Covariate distributions are superimposed on nomogram scales and the plot can be animated to allow on-the-fly changes to distribution representation and to enable outcome calculation.

Maintained by Roger Marshall. Last updated 5 years ago.

4 stars 3.45 score 53 scripts

bioc

ffpe:Quality assessment and control for FFPE microarray expression data

Identify low-quality data using metrics developed for expression data derived from Formalin-Fixed, Paraffin-Embedded (FFPE) data. Also a function for making Concordance at the Top plots (CAT-plots).

Maintained by Levi Waldron. Last updated 5 months ago.

microarray geneexpression qualitycontrol

3.03 score 27 scripts

bioc

iCheck:QC Pipeline and Data Analysis Tools for High-Dimensional Illumina mRNA Expression Data

QC pipeline and data analysis tools for high-dimensional Illumina mRNA expression data.

Maintained by Weiliang Qiu. Last updated 5 months ago.

geneexpression differentialexpression microarray preprocessing dnamethylation onechannel twochannel qualitycontrol

3.00 score 1 scripts

cbolen1

rdi:Repertoire Dissimilarity Index

Methods for calculation and visualization of the Repertoire Dissimilarity Index. Citation: Bolen and Rubelt, et al (2017) <doi:10.1186/s12859-017-1556-5>.

Maintained by Christopher Bolen. Last updated 6 years ago.

2.88 score 15 scripts

nie-xiuquan

EMAS:Epigenome-Wide Mediation Analysis Study

DNA methylation is essential for human, and environment can change the DNA methylation and affect body status. Epigenome-Wide Mediation Analysis Study (EMAS) can find potential mediator CpG sites between exposure (x) and outcome (y) in epigenome-wide. For more information on the methods we used, please see the following references: Tingley, D. (2014) <doi:10.18637/jss.v059.i05>, Turner, S. D. (2018) <doi:10.21105/joss.00731>, Rosseel, D. (2012) <doi:10.18637/jss.v048.i02>.

Maintained by Xiuquan Nie. Last updated 3 years ago.

1.00 score