ScholarGate
Assistent

Sammenlign metoder

Gennemgå dine valgte metoder side om side; rækker, der afviger, er fremhævet.

Metabolomikanalyse×RNA-seq Differential Expression×
FagområdeBioinformatikBioinformatik
FamilieProcess / pipelineProcess / pipeline
Oprindelsesår1998–20022008–2010 (RNA-seq DE methodology established)
OphavspersonOliver et al. (coining of 'metabolomics'); Oliver Fiehn (systematic framework)Multiple groups; foundational methods from Anders & Huber (DESeq, 2010), Robinson, McCarthy & Smyth (edgeR, 2010)
TypeQuantitative omics pipelineQuantitative genomics pipeline
Oprindelig kildeFiehn, O. (2002). Metabolomics — the link between genotypes and phenotypes. Plant Molecular Biology, 48(1-2), 155–171. link ↗Love, M. I., Huber, W., & Anders, S. (2014). Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biology, 15(12), 550. DOI ↗
Aliassermetabolome profiling, metabolic profiling, metabonomics, metabolite profilingRNA-seq DE analysis, transcriptomic differential expression, bulk RNA-seq DE, DEA
Relaterede66
ResuméMetabolomics analysis is the large-scale, systematic measurement of small-molecule metabolites in a biological sample to characterise the metabolome — the complete set of metabolic intermediates and products present under defined conditions. By coupling high-throughput analytical platforms such as mass spectrometry (MS) or nuclear magnetic resonance (NMR) spectroscopy with multivariate statistics and pathway databases, metabolomics bridges the genotype–phenotype gap and captures the downstream functional output of genes, transcripts, and proteins in real time.RNA-seq differential expression (DE) analysis identifies genes whose transcript abundance differs significantly between two or more biological conditions — for example, treated versus control, or diseased versus healthy tissue. Starting from raw sequencing reads, the pipeline moves through alignment, count-based normalization, statistical modeling of count dispersion, hypothesis testing, and multiple-testing correction to produce a ranked list of differentially expressed genes accompanied by fold-change estimates and adjusted p-values.
ScholarGateDatasæt
  1. v1
  2. 2 Kilder
  3. PUBLISHED
  1. v1
  2. 2 Kilder
  3. PUBLISHED

Gå til søgning Hent slides

ScholarGateSammenlign metoder: Metabolomics analysis · RNA-seq Differential Expression. Hentet 2026-06-18 fra https://scholargate.app/da/compare