ArticleGenome biology2015
quantro: a data-driven approach to guide the choice of an appropriate normalization method.
Article in Genome biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
59 citing papers in PubMed.
- Trial
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- Benchmarking informatics workflows for data-independent acquisition single-cell proteomics.Nature communications · 2025Article
- Microglia alter sex-specific cerebellar myelination following placental hormone loss.Nature communications · 2025Article
- Tissue-specific co-expression patterns of BAF complex genes across human endocrine and non-endocrine tissues.Endocrine connections · 2025Article
- Identification and correction of time-series transcriptomic anomalies.Nucleic acids research · 2025Article
- Time-resolved oxidative signal convergence across the algae-embryophyte divide.Nature communications · 2025Article
- Article
- Normalization of RNA-Seq data using adaptive trimmed mean with multi-reference.Briefings in bioinformatics · 2024Article
- The impact of selective HDAC inhibitors on the transcriptome of early mouse embryos.BMC genomics · 2024Article
- CoGTEx: Unscaled system-level coexpression estimation from GTEx data forecast novel functional gene partners.PloS one · 2024Article
- NORMSEQ: a tool for evaluation, selection and visualization of RNA-Seq normalization methods.Nucleic acids research · 2023Article
- Article
- satmut_utils: a simulation and variant calling package for multiplexed assays of variant effect.Genome biology · 2023Article
- Integrative profiling of gene expression and chromatin accessibility elucidates specific transcriptional networks in porcine neutrophils.Frontiers in genetics · 2023Article
- SATINN: an automated neural network-based classification of testicular sections allows for high-throughput histopathology of mouse mutants.Bioinformatics (Oxford, England) · 2022Article
- ePeak: from replicated chromatin profiling data to epigenomic dynamics.NAR genomics and bioinformatics · 2022Article
- Batch-effect detection, correction and characterisation in Illumina HumanMethylation450 and MethylationEPIC BeadChip array data.Clinical epigenetics · 2022Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Normalization is an essential step in the analysis of high-throughput data. Multi-sample global normalization methods, such as quantile normalization, have been successfully used to remove technical variation. However, these methods rely on the assumption that observed global changes across samples are due to unwanted technical variability. Applying global normalization methods has the potential to remove biologically driven variation. Currently, it is up to the subject matter experts to determine if the stated assumptions are appropriate. Here, we propose a data-driven alternative. We demonstrate the utility of our method (quantro) through examples and simulations. A software implementation is available from http://www.bioconductor.org/packages/release/bioc/html/quantro.html .
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.