NanoTube includes functions for the processing, quality control, analysis, and visualization of NanoString nCounter data. Analysis functions include differential analysis and gene set analysis methods, as well as postprocessing steps to help understand the results. Additional functions are included to enable interoperability with other Bioconductor NanoString data analysis packages.
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library(NanoTube)
# Process and normalize NanoString data
dat <- processNanostringData(
nsFiles = example_data,
sampleTab = sample_info,
idCol = "RCC_Name",
groupCol = "Sample_Diagnosis",
normalization = "nSolver"
)
# Run differential expression analysis using Limma
limmaResults <- runLimmaAnalysis(dat, base.group = "None")
# Generate volcano plot of differential expression results
deVolcano(limmaResults, plotContrast = "Autoimmune.retinopathy")
# Run gene set enrichment analysis
fgseaResults <- limmaToFGSEA(limmaResults, gene.sets = ExamplePathways)
Input: RCC files or tabular expression data, sample metadata. Output: Normalized ExpressionSet, differential expression statistics, volcano plots, and GSEA results.
processNanostringData.runLimmaAnalysis.limmaToFGSEA or nsdiffToFGSEA.positiveQC, negativeQC, nanostringPCA, or RLE plots.DESeq2 or edgeR.limma directly.processNanostringData ("nSolver", "RUVIII", "RUVg", or "none").runLimmaAnalysis.positiveQC and negative controls using negativeQC before downstream analysis.idCol in processNanostringData to ensure correct merging.droplevels() before analysis.NanoStringDiff for differential analysis using a generalized linear model.limma for general linear modeling.RUVSeq for removing unwanted variation.まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
The package contains functions for exploratory oligonucleotide array analysis. The dependence on tkWidgets only concerns few convenience functions. 'affy' is fully functional without it.
日本語の概要は準備中です。原文の説明を表示しています。
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
日本語の概要は準備中です。原文の説明を表示しています。
This package provides a client for the Bioconductor AnnotationHub web resource. The AnnotationHub web resource provides a central location where genomic files (e.g., VCF, bed, wig) and other resources from standard locations (e.g., UCSC, En
日本語の概要は準備中です。原文の説明を表示しています。
apeglm provides Bayesian shrinkage estimators for effect sizes for a variety of GLM models, using approximation of the posterior for individual coefficients.
日本語の概要は準備中です。原文の説明を表示しています。
ASURAT is a software for single-cell data analysis. Using ASURAT, one can simultaneously perform unsupervised clustering and biological interpretation in terms of cell type, disease, biological process, and signaling pathway activity. Inputting a single-cell RNA-seq data and knowledge-based databases, such as Cell Ontology, Gene Ontology, KEGG, etc., ASURAT transforms gene expression tables into original multivariate tables, termed sign-by-sample matrices (SSMs).
日本語の概要は準備中です。原文の説明を表示しています。
AUCell allows to identify cells with active gene sets (e.g. signatures, gene modules...) in single-cell RNA-seq data. AUCell uses the "Area Under the Curve" (AUC) to calculate whether a critical subset of the input gene set is enriched with
日本語の概要は準備中です。原文の説明を表示しています。