Article

A statistical nonparametric method for identifying consistently important features across samples

2019-11-07

Abstract excerpt

In many applications, a consistently high measurement across many samples can indicate particularly meaningful or useful information for quality control or biological interpretation. Identification of these strong features among many others can be challenging especially when the samples cannot be expected to have the same distribution or range of values. We present a general method called conserved feature discove...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 41e317ab-e9ff-5cbd-a7df-458d33d11575
DOI: 10.1101/833624

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

A statistical nonparametric method for identifying consistently important features across samplesDOI 10.1101/833624Read

A novel method to enhance the sensitivity of marker detection using a refined hierarchical prior of tissue similaritiesSemantic proximity Read

Symmetry as a Fundamental Principle in Defining Gene Expression and Phenotypic TraitsSemantic proximity Read

Investigating normal human gene expression in tissues with high-throughput transcriptomic and proteomic dataSemantic proximity Read

Patterns of unwanted biological and technical expression variation across 49 human tissuesSemantic proximity Read

GEOlimma: Differential Expression Analysis and Feature Selection Using Pre-Existing Microarray DataSemantic proximity Read

Deriving Ranges of Optimal Estimated Transcript Expression Due to Non-identifiabilitySemantic proximity Read

Rigor and Reproducibility of Digital Spatial Profiling on Clinically Sourced Human TissuesSemantic proximity Read

MultiPLIER: a transfer learning framework for transcriptomics reveals systemic features of rare diseaseSemantic proximity Read

Making sense out of massive data by going beyond differential expression.Semantic proximity Read

SpaFun: Discovering Domain-specific Spatial Expression Patterns and New Disease-Relevant Genes using Functional Principal Component AnalysisSemantic proximity Read

ROTS 2.0: A reproducibility-driven framework for robust statistical modeling across diverse high-throughput omics study designsSemantic proximity Read

Identification of differentially distributed gene expression and distinct sets of cancer-related genes identified by changes in mean and variabilitySemantic proximity Read