ArticleBriefings in bioinformatics2018
Power and sample size calculations for high-throughput sequencing-based experiments.
Article in Briefings in bioinformatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 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.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
23 citing papers in PubMed.
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- Genetics and Traumatic Brain Injury: Findings from an Exome-Based Study of a 50-Patient Case Series.Current issues in molecular biology · 2024Article
- Impact of florfenicol dosing regimen on the phenotypic and genotypic resistance of enteric bacteria in steers.Scientific reports · 2024Article
- Review
- Unravelling the genetic architecture of human complex traits through whole genome sequencing.Nature communications · 2023Article
- Statistical analysis of high-dimensional biomedical data: a gentle introduction to analytical goals, common approaches and challenges.BMC medicine · 2023Review
- Guiding the design of well-powered Hi-C experiments to detect differential loops.bioRxiv : the preprint server for biology · 2023Article
- Guiding the design of well-powered Hi-C experiments to detect differential loops.Bioinformatics advances · 2023Article
- Temporal progress of gene expression analysis with RNA-Seq data: A review on the relationship between computational methods.Computational and structural biotechnology journal · 2023Review
- Contribution of the innate and adaptive immune systems to aortic dilation in murine mucopolysaccharidosis type I.Molecular genetics and metabolism · 2022Article
- Enhancing Research Through the Use of the Genotype-Tissue Expression (GTEx) Database.Biological research for nursing · 2021Article
- Clinically significant genomic alterations in the Chinese and Western patients with intrahepatic cholangiocarcinoma.BMC cancer · 2021Article
- The Power of Microbiome Studies: Some Considerations on Which Alpha and Beta Metrics to Use and How to Report Results.Frontiers in microbiology · 2021Article
- Best Practices for Microbiome Study Design in Companion Animal Research.Frontiers in veterinary science · 2021Review
- Review
- Biomarker development for axial spondyloarthritis.Nature reviews. Rheumatology · 2020Review
- Harmonization of quality metrics and power calculation in multi-omic studies.Nature communications · 2020Article
- Transcriptomics in Toxicogenomics, Part I: Experimental Design, Technologies, Publicly Available Data, and Regulatory Aspects.Nanomaterials (Basel, Switzerland) · 2020Review
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
Power/sample size (power) analysis estimates the likelihood of successfully finding the statistical significance in a data set. There has been a growing recognition of the importance of power analysis in the proper design of experiments. Power analysis is complex, yet necessary for the success of large studies. It is important to design a study that produces statistically accurate and reliable results. Power computation methods have been well established for both microarray-based gene expression studies and genotyping microarray-based genome-wide association studies. High-throughput sequencing (HTS) has greatly enhanced our ability to conduct biomedical studies at the highest possible resolution (per nucleotide). However, the complexity of power computations is much greater for sequencing data than for the simpler genotyping array data. Research on methods of power computations for HTS-based studies has been recently conducted but is not yet well known or widely used. In this article, we describe the power computation methods that are currently available for a range of HTS-based studies, including DNA sequencing, RNA-sequencing, microbiome sequencing and chromatin immunoprecipitation sequencing. Most importantly, we review the methods of power analysis for several types of sequencing data and guide the reader to the relevant methods for each data type.
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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.