ArticleBMC genomics2012
Technical and biological variance structure in mRNA-Seq data: life in the real world.
Article in BMC genomics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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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
22 citing papers in PubMed.
- The Sum of Two Halves May Be Different from the Whole-Effects of Splitting Sequencing Samples Across Lanes.Genes · 2022Article
- Patterns, Profiles, and Parsimony: Dissecting Transcriptional Signatures From Minimal Single-Cell RNA-Seq Output With SALSA.Frontiers in genetics · 2020Article
- Stepwise large genome assembly approach: a case of Siberian larch (Larix sibirica Ledeb).BMC bioinformatics · 2019Article
- Expression analysis of RNA sequencing data from human neural and glial cell lines depends on technical replication and normalization methods.BMC bioinformatics · 2018Article
- Metabolic network-based predictions of toxicant-induced metabolite changes in the laboratory rat.Scientific reports · 2018Article
- A Leveraged Signal-to-Noise Ratio (LSTNR) Method to Extract Differentially Expressed Genes and Multivariate Patterns of Expression From Noisy and Low-Replication RNAseq Data.Frontiers in genetics · 2018Article
- In Search of Biomarkers for Pathogenesis and Control of Leishmaniasis by Global Analyses ofFrontiers in cellular and infection microbiology · 2018Review
- Bayesian Inference of Allele-Specific Gene Expression Indicates Abundant Cis-Regulatory Variation in Natural Flycatcher Populations.Genome biology and evolution · 2017Article
- Article
- Gene signatures associated with adaptive humoral immunity following seasonal influenza A/H1N1 vaccination.Genes and immunity · 2016Article
- Toward reliable biomarker signatures in the age of liquid biopsies - how to standardize the small RNA-Seq workflow.Nucleic acids research · 2016Article
- Article
- Article
- High Intensity Interval Training Favourably Affects Angiotensinogen mRNA Expression and Markers of Cardiorenal Health in a Rat Model of Early-Stage Chronic Kidney Disease.BioMed research international · 2015Article
- FineSplice, enhanced splice junction detection and quantification: a novel pipeline based on the assessment of diverse RNA-Seq alignment solutions.Nucleic acids research · 2014Article
- Calculating sample size estimates for RNA sequencing data.Journal of computational biology : a journal of computational molecular cell biology · 2013Article
- Impact of bioinformatic procedures in the development and translation of high-throughput molecular classifiers in oncology.Clinical cancer research : an official journal of the American Association for Cancer Research · 2013Review
- Gene set enrichment analysis of RNA-Seq data: integrating differential expression and splicing.BMC bioinformatics · 2013Article
- Article
- Genome-wide characterization of transcriptional patterns in high and low antibody responders to rubella vaccination.PloS one · 2013Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
backgroundmRNA expression data from next generation sequencing platforms is obtained in the form of counts per gene or exon. Counts have classically been assumed to follow a Poisson distribution in which the variance is equal to the mean. The Negative Binomial distribution which allows for over-dispersion, i.e., for the variance to be greater than the mean, is commonly used to model count data as well.
resultsIn mRNA-Seq data from 25 subjects, we found technical variation to generally follow a Poisson distribution as has been reported previously and biological variability was over-dispersed relative to the Poisson model. The mean-variance relationship across all genes was quadratic, in keeping with a Negative Binomial (NB) distribution. Over-dispersed Poisson and NB distributional assumptions demonstrated marked improvements in goodness-of-fit (GOF) over the standard Poisson model assumptions, but with evidence of over-fitting in some genes. Modeling of experimental effects improved GOF for high variance genes but increased the over-fitting problem.
conclusionsThese conclusions will guide development of analytical strategies for accurate modeling of variance structure in these data and sample size determination which in turn will aid in the identification of true biological signals that inform our understanding of biological systems.
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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.