bioconductor-spikein
|
public |
Affymetrix Spike-In Experiment Data
|
2024-12-19 |
bioconductor-makecdfenv
|
public |
CDF Environment Maker
|
2024-12-19 |
bioconductor-panp
|
public |
Presence-Absence Calls from Negative Strand Matching Probesets
|
2024-12-19 |
bioconductor-cardinal
|
public |
A mass spectrometry imaging toolbox for statistical analysis
|
2024-12-19 |
bioconductor-flowtime
|
public |
Annotation and analysis of biological dynamical systems using flow cytometry
|
2024-12-19 |
bioconductor-cghregions
|
public |
Dimension Reduction for Array CGH Data with Minimal Information Loss.
|
2024-12-19 |
r-hemdag
|
public |
a collection of Hierarchical Ensemble Methods (HEMs) for Directed Acyclic Graphs (DAGs).
|
2024-12-19 |
bioconductor-cormotif
|
public |
Correlation Motif Fit
|
2024-12-19 |
bioconductor-cytodx
|
public |
Robust prediction of clinical outcomes using cytometry data without cell gating
|
2024-12-19 |
r-cp4p
|
public |
Functions to check whether a vector of p-values respects the assumptions of FDR (false discovery rate) control procedures and to compute adjusted p-values.
|
2024-12-19 |
bioconductor-affydata
|
public |
Affymetrix Data for Demonstration Purpose
|
2024-12-19 |
r-mutoss
|
public |
Designed to ease the application and comparison of multiple hypothesis testing procedures for FWER, gFWER, FDR and FDX. Methods are standardized and usable by the accompanying 'mutossGUI'.
|
2024-12-19 |
bioconductor-abarray
|
public |
Microarray QA and statistical data analysis for Applied Biosystems Genome Survey Microrarray (AB1700) gene expression data.
|
2024-12-19 |
bioconductor-rain
|
public |
Rhythmicity Analysis Incorporating Non-parametric Methods
|
2024-12-19 |
bioconductor-paircompviz
|
public |
Multiple comparison test visualization
|
2024-12-19 |
bioconductor-biocviews
|
public |
Categorized views of R package repositories
|
2024-12-19 |
bioconductor-a4classif
|
public |
Automated Affymetrix Array Analysis Classification Package
|
2024-12-19 |
bioconductor-stategra
|
public |
Classes and methods for multi-omics data integration
|
2024-12-19 |
bioconductor-aracne.networks
|
public |
ARACNe-inferred gene networks from TCGA tumor datasets
|
2024-12-19 |
bioconductor-curatedbladderdata
|
public |
Bladder Cancer Gene Expression Analysis
|
2024-12-19 |
bioconductor-cghcall
|
public |
Calling aberrations for array CGH tumor profiles.
|
2024-12-19 |
bioconductor-cycle
|
public |
Significance of periodic expression pattern in time-series data
|
2024-12-19 |
bioconductor-flowclean
|
public |
flowClean
|
2024-12-18 |
bioconductor-mspurity
|
public |
Automated Evaluation of Precursor Ion Purity for Mass Spectrometry Based Fragmentation in Metabolomics
|
2024-12-18 |
bioconductor-simat
|
public |
GC-SIM-MS data processing and alaysis tool
|
2024-12-18 |
bioconductor-chimphumanbraindata
|
public |
Chimp and human brain data package
|
2024-12-18 |
bioconductor-consensusclusterplus
|
public |
ConsensusClusterPlus
|
2024-12-18 |
bioconductor-diggitdata
|
public |
Example data for the diggit package
|
2024-12-18 |
bioconductor-tronco
|
public |
TRONCO, an R package for TRanslational ONCOlogy
|
2024-12-18 |
bioconductor-flowbeads
|
public |
flowBeads: Analysis of flow bead data
|
2024-12-18 |
r-diffcorr
|
public |
A method for identifying pattern changes between 2 experimental conditions in correlation networks (e.g., gene co-expression networks), which builds on a commonly used association measure, such as Pearson's correlation coefficient. This package includes functions to calculate correlation matrices for high-dimensional dataset and to test differential correlation, which means the changes in the correlation relationship among variables (e.g., genes and metabolites) between 2 experimental conditions.
|
2024-12-18 |
bioconductor-cll
|
public |
A Package for CLL Gene Expression Data
|
2024-12-18 |
bioconductor-metabomxtr
|
public |
A package to run mixture models for truncated metabolomics data with normal or lognormal distributions
|
2024-12-18 |
r-tidygenomics
|
public |
Handle genomic data within data frames just as you would with 'GRanges'. This packages provides method to deal with genomic intervals the "tidy-way" which makes it simpler to integrate in the the general data munging process. The API is inspired by the popular 'bedtools' and the genome_join() method from the 'fuzzyjoin' package.
|
2024-12-18 |
bioconductor-dirichletmultinomial
|
public |
Dirichlet-Multinomial Mixture Model Machine Learning for Microbiome Data
|
2024-12-18 |
bioconductor-metaseq
|
public |
Meta-analysis of RNA-Seq count data in multiple studies
|
2024-12-18 |
bioconductor-ampaffyexample
|
public |
Example of Amplified Data
|
2024-12-18 |
bioconductor-turbonorm
|
public |
A fast scatterplot smoother suitable for microarray normalization
|
2024-12-18 |
bioconductor-ruvnormalize
|
public |
RUV for normalization of expression array data
|
2024-12-18 |
bioconductor-ruvcorr
|
public |
Removal of unwanted variation for gene-gene correlations and related analysis
|
2024-12-18 |
bioconductor-tmixclust
|
public |
Time Series Clustering of Gene Expression with Gaussian Mixed-Effects Models and Smoothing Splines
|
2024-12-18 |
bioconductor-gwasdata
|
public |
Data used in the examples and vignettes of the GWASTools package
|
2024-12-18 |
bioconductor-complexheatmap
|
public |
Make Complex Heatmaps
|
2024-12-18 |
bioconductor-derfinderhelper
|
public |
derfinder helper package
|
2024-12-18 |
r-perfmeas
|
public |
Package that implements different performance measures for classification and ranking tasks. AUC, precision at a given recall, F-score for single and multiple classes are available.
|
2024-12-18 |
bioconductor-nethet
|
public |
A bioconductor package for high-dimensional exploration of biological network heterogeneity
|
2024-12-18 |
bioconductor-flowchic
|
public |
Analyze flow cytometric data using histogram information
|
2024-12-18 |
r-imputelcmd
|
public |
The package contains a collection of functions for left-censored missing data imputation. Left-censoring is a special case of missing not at random (MNAR) mechanism that generates non-responses in proteomics experiments. The package also contains functions to artificially generate peptide/protein expression data (log-transformed) as random draws from a multivariate Gaussian distribution as well as a function to generate missing data (both randomly and non-randomly). For comparison reasons, the package also contains several wrapper functions for the imputation of non-responses that are missing at random. * New functionality has been added: a hybrid method that allows the imputation of missing values in a more complex scenario where the missing data are both MAR and MNAR.
|
2024-12-18 |
bioconductor-nucleosim
|
public |
Generate synthetic nucleosome maps
|
2024-12-18 |
bioconductor-scde
|
public |
Single Cell Differential Expression
|
2024-12-18 |