4.7 Article

A field guide for the compositional analysis of any-omics data

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Geosciences, Multidisciplinary

Variable Selection in Compositional Data Analysis Using Pairwise Logratios

Michael Greenacre

MATHEMATICAL GEOSCIENCES (2019)

Article Microbiology

A Novel Sparse Compositional Technique Reveals Microbial Perturbations

Cameron Martino et al.

MSYSTEMS (2019)

Article Biochemical Research Methods

Evaluating measures of association for single-cell transcriptomics

Michael A. Skinnider et al.

NATURE METHODS (2019)

Article Biochemical Research Methods

A broken promise: microbiome differential abundance methods do not control the false discovery rate

Stijn Hawinkel et al.

BRIEFINGS IN BIOINFORMATICS (2019)

Review Biochemical Research Methods

Understanding sequencing data as compositions: an outlook and review

Thomas P. Quinn et al.

BIOINFORMATICS (2018)

Article Microbiology

Absolute quantitation of microbiota abundance in environmental samples

Andrzej Tkacz et al.

MICROBIOME (2018)

Article Microbiology

Balances: a New Perspective for Microbiome Analysis

J. Rivera-Pinto et al.

MSYSTEMS (2018)

Article Multidisciplinary Sciences

Synthetic microbe communities provide internal reference standards for metagenome sequencing and analysis

Simon A. Hardwick et al.

NATURE COMMUNICATIONS (2018)

Review Medicine, Research & Experimental

An Introduction to the Analysis of Single-Cell RNA-Sequencing Data

Aisha A. AlJanahi et al.

MOLECULAR THERAPY-METHODS & CLINICAL DEVELOPMENT (2018)

Article Biotechnology & Applied Microbiology

Analysis and correction of compositional bias in sparse sequencing count data

M. Senthil Kumar et al.

BMC GENOMICS (2018)

Article Biotechnology & Applied Microbiology

Observation weights unlock bulk RNA-seq tools for zero inflation and single-cell applications

Koen Van den Berge et al.

GENOME BIOLOGY (2018)

Article Biochemistry & Molecular Biology

Assessing the reliability of spike-in normalization for analyses of single-cell RNA sequencing data

Aaron T. L. Lun et al.

GENOME RESEARCH (2017)

Article Biochemical Research Methods

Salmon provides fast and bias-aware quantification of transcript expression

Rob Patro et al.

NATURE METHODS (2017)

Article Microbiology

Microbiome Datasets Are Compositional: And This Is Not Optional

Gregory B. Gloor et al.

FRONTIERS IN MICROBIOLOGY (2017)

Article Multidisciplinary Sciences

propr: An R-package for Identifying Proportionally Abundant Features Using Compositional Data Analysis

Thomas P. Quinn et al.

SCIENTIFIC REPORTS (2017)

Article Automation & Control Systems

Robust biomarker identification in a two-class problem based on pairwise log-ratios

Jan Walach et al.

CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS (2017)

Editorial Material Biochemistry & Molecular Biology

The Overlooked Fact: Fundamental Need for Spike-In Control for Virtually All Genome-Wide Analyses

Kaifu Chen et al.

MOLECULAR AND CELLULAR BIOLOGY (2016)

Article Biochemical Research Methods

Representing genetic variation with synthetic DNA standards

Ira W. Deveson et al.

NATURE METHODS (2016)

Article Biochemical Research Methods

Spliced synthetic genes as internal controls in RNA sequencing experiments

Simon A. Hardwick et al.

NATURE METHODS (2016)

Article Biology

How should we measure proportionality on relative gene expression data?

Ionas Erb et al.

THEORY IN BIOSCIENCES (2016)

Article Statistics & Probability

Compositional Uncertainty Should Not Be Ignored in High-Throughput Sequencing Data Analysis

Gregory B. Gloor et al.

AUSTRIAN JOURNAL OF STATISTICS (2016)

Article Biochemical Research Methods

Use of Metatranscriptomics in Microbiome Research

Stavros Bashiardes et al.

BIOINFORMATICS AND BIOLOGY INSIGHTS (2016)

Article Automation & Control Systems

zCompositions - R Package for multivariate imputation of left-censored data under a compositional approach

Javier Palarea-Albaladejo et al.

CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS (2015)

Review Biochemistry & Molecular Biology

The Technology and Biology of Single-Cell RNA Sequencing

Aleksandra A. Kolodziejczyk et al.

MOLECULAR CELL (2015)

Article Biochemical Research Methods

Sparse and Compositionally Robust Inference of Microbial Ecological Networks

Zachary D. Kurtz et al.

PLOS COMPUTATIONAL BIOLOGY (2015)

Article Biochemical Research Methods

Library construction for next-generation sequencing: Overviews and challenges

Steven R. Head et al.

BIOTECHNIQUES (2014)

Article Biochemical Research Methods

What can go wrong at the data normalization step for identification of biomarkers?

P. Filzmoser et al.

JOURNAL OF CHROMATOGRAPHY A (2014)

Article Biotechnology & Applied Microbiology

Normalization of RNA-seq data using factor analysis of control genes or samples

Davide Risso et al.

NATURE BIOTECHNOLOGY (2014)

Article Biochemistry & Molecular Biology

svaseq: removing batch effects and other unwanted noise from sequencing data

Jeffrey T. Leek

NUCLEIC ACIDS RESEARCH (2014)

Article Biotechnology & Applied Microbiology

voom: precision weights unlock linear model analysis tools for RNA-seq read counts

Charity W. Law et al.

GENOME BIOLOGY (2014)

Article Biochemical Research Methods

Systematic evaluation of spliced alignment programs for RNA-seq data

Par G. Engstrom et al.

NATURE METHODS (2013)

Article Multidisciplinary Sciences

ANOVA-Like Differential Expression (ALDEx) Analysis for Mixed Population RNA-Seq

Andrew D. Fernandes et al.

PLOS ONE (2013)

Review Biochemical Research Methods

Tools for mapping high-throughput sequencing data

Nuno A. Fonseca et al.

BIOINFORMATICS (2012)

Article Biochemistry & Molecular Biology

Revisiting Global Gene Expression Analysis

Jakob Loven et al.

Review Biochemistry & Molecular Biology

Comprehensive literature review and statistical considerations for microarray meta-analysis

George C. Tseng et al.

NUCLEIC ACIDS RESEARCH (2012)

Review Geology

Uses and misuses of compositional data in sedimentology

Raimon Tolosana-Delgado

SEDIMENTARY GEOLOGY (2012)

Article Biochemical Research Methods

Inferring Correlation Networks from Genomic Survey Data

Jonathan Friedman et al.

PLOS COMPUTATIONAL BIOLOGY (2012)

Article Biochemistry & Molecular Biology

Synthetic spike-in standards for RNA-seq experiments

Lichun Jiang et al.

GENOME RESEARCH (2011)

Article Geosciences, Multidisciplinary

Measuring Subcompositional Incoherence

Michael Greenacre

MATHEMATICAL GEOSCIENCES (2011)

Review Genetics & Heredity

APPLICATIONS OF NEXT-GENERATION SEQUENCING Sequencing technologies - the next generation

Michael L. Metzker

NATURE REVIEWS GENETICS (2010)

Review Biochemical Research Methods

A Primer on Metagenomics

John C. Wooley et al.

PLOS COMPUTATIONAL BIOLOGY (2010)

Article Biotechnology & Applied Microbiology

A scaling normalization method for differential expression analysis of RNA-seq data

Mark D. Robinson et al.

GENOME BIOLOGY (2010)

Article Biotechnology & Applied Microbiology

Differential expression analysis for sequence count data

Simon Anders et al.

GENOME BIOLOGY (2010)

Review Genetics & Heredity

ChIP-seq: advantages and challenges of a maturing technology

Peter J. Park

NATURE REVIEWS GENETICS (2009)

Article Computer Science, Interdisciplinary Applications

compositions: A unified R package to analyze compositional data

K. Gerald van den Boogaart et al.

COMPUTERS & GEOSCIENCES (2008)

Review Immunology

Signal transduction by the lipopolysaccharide receptor, Toll-like receptor-4

EM Pålsson-McDermott et al.

IMMUNOLOGY (2004)

Article Geosciences, Multidisciplinary

Dealing with zeros and missing values in compositional data sets using nonparametric imputation

JA Martín-Fernández et al.

MATHEMATICAL GEOLOGY (2003)

Article Geosciences, Multidisciplinary

Isometric logratio transformations for compositional data analysis

JJ Egozcue et al.

MATHEMATICAL GEOLOGY (2003)

Article Geosciences, Multidisciplinary

Logratio analysis and compositional distance

J Aitchison et al.

MATHEMATICAL GEOLOGY (2000)