R-universe search: assaydomain

Showing 15 of total 15 results (show query)

stemangiola

tidyHeatmap:A Tidy Implementation of Heatmap

This is a tidy implementation for heatmap. At the moment it is based on the (great) package 'ComplexHeatmap'. The goal of this package is to interface a tidy data frame with this powerful tool. Some of the advantages are: Row and/or columns colour annotations are easy to integrate just specifying one parameter (column names). Custom grouping of rows is easy to specify providing a grouped tbl. For example: df %>% group_by(...). Labels size adjusted by row and column total number. Default use of Brewer and Viridis palettes.

Maintained by Stefano Mangiola. Last updated 1 months ago.

assaydomain infrastructure brewer complexheatmap custom-palette dplyr graphviz heatmap mtcars plotting rstudio scale tibble tidy tidy-data-frame tidybulk tidyverse viridis

11.0 match 335 stars 10.23 score 197 scripts 1 dependents

stemangiola

tidyseurat:Brings Seurat to the Tidyverse

It creates an invisible layer that allow to see the 'Seurat' object as tibble and interact seamlessly with the tidyverse.

Maintained by Stefano Mangiola. Last updated 8 months ago.

assaydomain infrastructure rnaseq differentialexpression geneexpression normalization clustering qualitycontrol sequencing transcription transcriptomics dplyr ggplot2 pca purrr sct seurat single-cell single-cell-rna-seq tibble tidyr tidyverse transcripts tsne umap

11.0 match 158 stars 9.66 score 398 scripts 1 dependents

bioc

tidybulk:Brings transcriptomics to the tidyverse

This is a collection of utility functions that allow to perform exploration of and calculations to RNA sequencing data, in a modular, pipe-friendly and tidy fashion.

Maintained by Stefano Mangiola. Last updated 5 months ago.

assaydomain infrastructure rnaseq differentialexpression geneexpression normalization clustering qualitycontrol sequencing transcription transcriptomics bioconductor bulk-transcriptional-analyses deseq2 differential-expression edger ensembl-ids entrez gene-symbols gsea mds-dimensions pca pipe redundancy tibble tidy tidy-data tidyverse transcripts tsne

11.0 match 168 stars 9.48 score 172 scripts 1 dependents

bioc

tidySingleCellExperiment:Brings SingleCellExperiment to the Tidyverse

'tidySingleCellExperiment' is an adapter that abstracts the 'SingleCellExperiment' container in the form of a 'tibble'. This allows *tidy* data manipulation, nesting, and plotting. For example, a 'tidySingleCellExperiment' is directly compatible with functions from 'tidyverse' packages `dplyr` and `tidyr`, as well as plotting with `ggplot2` and `plotly`. In addition, the package provides various utility functions specific to single-cell omics data analysis (e.g., aggregation of cell-level data to pseudobulks).

Maintained by Stefano Mangiola. Last updated 5 months ago.

assaydomain infrastructure rnaseq differentialexpression singlecell geneexpression normalization clustering qualitycontrol sequencing bioconductor dplyr ggplot2 plotly single-cell-rna-seq single-cell-sequencing singlecellexperiment tibble tidyr tidyverse

11.0 match 36 stars 8.86 score 125 scripts 2 dependents

bioc

tidySummarizedExperiment:Brings SummarizedExperiment to the Tidyverse

The tidySummarizedExperiment package provides a set of tools for creating and manipulating tidy data representations of SummarizedExperiment objects. SummarizedExperiment is a widely used data structure in bioinformatics for storing high-throughput genomic data, such as gene expression or DNA sequencing data. The tidySummarizedExperiment package introduces a tidy framework for working with SummarizedExperiment objects. It allows users to convert their data into a tidy format, where each observation is a row and each variable is a column. This tidy representation simplifies data manipulation, integration with other tidyverse packages, and enables seamless integration with the broader ecosystem of tidy tools for data analysis.

Maintained by Stefano Mangiola. Last updated 5 months ago.

assaydomain infrastructure rnaseq differentialexpression geneexpression normalization clustering qualitycontrol sequencing transcription transcriptomics

11.0 match 26 stars 8.44 score 196 scripts 1 dependents

bioc

CuratedAtlasQueryR:Queries the Human Cell Atlas

Provides access to a copy of the Human Cell Atlas, but with harmonised metadata. This allows for uniform querying across numerous datasets within the Atlas using common fields such as cell type, tissue type, and patient ethnicity. Usage involves first querying the metadata table for cells of interest, and then downloading the corresponding cells into a SingleCellExperiment object.

Maintained by Stefano Mangiola. Last updated 5 months ago.

assaydomain infrastructure rnaseq differentialexpression geneexpression normalization clustering qualitycontrol sequencing transcription transcriptomics database duckdb hdf5 human-cell-atlas single-cell singlecellexperiment tidyverse

11.0 match 90 stars 7.04 score 41 scripts

stemangiola

tidygate:Interactively Gate Points

Interactively gate points on a scatter plot. Interactively drawn gates are recorded and can be applied programmatically to reproduce results exactly. Programmatic gating is based on the package gatepoints by Wajid Jawaid (who is also an author of this package).

Maintained by Stefano Mangiola. Last updated 6 months ago.

assaydomain infrastructure clustering datavis dataviz dplyr drawing facs gate ggplot2 interactive pipe programmatic seurat single-cell single-cell-rna-seq tibble tidy-data tidyverse

11.0 match 23 stars 6.89 score 14 scripts 1 dependents

bioc

tidyomics:Easily install and load the tidyomics ecosystem

The tidyomics ecosystem is a set of packages for ’omic data analysis that work together in harmony; they share common data representations and API design, consistent with the tidyverse ecosystem. The tidyomics package is designed to make it easy to install and load core packages from the tidyomics ecosystem with a single command.

Maintained by Stefano Mangiola. Last updated 5 months ago.

assaydomain infrastructure rnaseq differentialexpression geneexpression normalization clustering qualitycontrol sequencing transcription transcriptomics cytometry genomics tidyverse

11.0 match 64 stars 6.11 score 5 scripts

bioc

MetID:Network-based prioritization of putative metabolite IDs

This package uses an innovative network-based approach that will enhance our ability to determine the identities of significant ions detected by LC-MS.

Maintained by Zhenzhi Li. Last updated 5 months ago.

assaydomain biologicalquestion infrastructure researchfield statisticalmethod technology workflowstep network kegg

11.0 match 1 stars 5.74 score 110 scripts

bioc

BG2:Performs Bayesian GWAS analysis for non-Gaussian data using BG2

This package is built to perform GWAS analysis for non-Gaussian data using BG2. The BG2 method uses penalized quasi-likelihood along with nonlocal priors in a two step manner to identify SNPs in GWAS analysis. The research related to this package was supported in part by National Science Foundation awards DMS 1853549 and DMS 2054173.

Maintained by Jacob Williams. Last updated 5 months ago.

bayesian assaydomain snp genomewideassociation

11.0 match 4.18 score 3 scripts

bioc

pgca:PGCA: An Algorithm to Link Protein Groups Created from MS/MS Data

Protein Group Code Algorithm (PGCA) is a computationally inexpensive algorithm to merge protein summaries from multiple experimental quantitative proteomics data. The algorithm connects two or more groups with overlapping accession numbers. In some cases, pairwise groups are mutually exclusive but they may still be connected by another group (or set of groups) with overlapping accession numbers. Thus, groups created by PGCA from multiple experimental runs (i.e., global groups) are called "connected" groups. These identified global protein groups enable the analysis of quantitative data available for protein groups instead of unique protein identifiers.

Maintained by Gabriela Cohen-Freue. Last updated 5 months ago.

workflowstep assaydomain proteomics massspectrometry immunooncology

11.0 match 4.00 score 3 scripts

bioc

GWAS.BAYES:Bayesian analysis of Gaussian GWAS data

This package is built to perform GWAS analysis using Bayesian techniques. Currently, GWAS.BAYES has functionality for the implementation of BICOSS (Williams, J., Ferreira, M. A., and Ji, T. (2022). BICOSS: Bayesian iterative conditional stochastic search for GWAS. BMC Bioinformatics), BGWAS (Williams, J., Xu, S., Ferreira, M. A.. (2023) "BGWAS: Bayesian variable selection in linear mixed models with nonlocal priors for genome-wide association studies." BMC Bioinformatics), and GINA. All methods currently are for the analysis of Gaussian phenotypes The research related to this package was supported in part by National Science Foundation awards DMS 1853549, DMS 1853556, and DMS 2054173.

Maintained by Jacob Williams. Last updated 5 months ago.

bayesian assaydomain snp genomewideassociation

11.0 match 3.90 score 8 scripts

bioc

cbaf:Automated functions for comparing various omic data from cbioportal.org

This package contains functions that allow analysing and comparing omic data across various cancers/cancer subgroups easily. So far, it is compatible with RNA-seq, microRNA-seq, microarray and methylation datasets that are stored on cbioportal.org.

Maintained by Arman Shahrisa. Last updated 5 months ago.

software assaydomain dnamethylation geneexpression transcription microarray researchfield biomedicalinformatics comparativegenomics epigenetics genetics transcriptomics

11.0 match 3.78 score 1 scripts

bioc

iGC:An integrated analysis package of Gene expression and Copy number alteration

This package is intended to identify differentially expressed genes driven by Copy Number Alterations from samples with both gene expression and CNA data.

Maintained by Liang-Bo Wang. Last updated 5 months ago.

software biological question differentialexpression genomicvariation assaydomain copynumbervariation geneexpression researchfield genetics technology microarray sequencing workflowstep multiplecomparison

11.0 match 1 stars 3.78 score 1 scripts

bioc

ScreenR:Package to Perform High Throughput Biological Screening

ScreenR is a package suitable to perform hit identification in loss of function High Throughput Biological Screenings performed using barcoded shRNA-based libraries. ScreenR combines the computing power of software such as edgeR with the simplicity of use of the Tidyverse metapackage. ScreenR executes a pipeline able to find candidate hits from barcode counts, and integrates a wide range of visualization modes for each step of the analysis.

Maintained by Emanuel Michele Soda. Last updated 5 months ago.

software assaydomain geneexpression high-throughput-screening

11.0 match 1 stars 3.11 score 13 scripts