ArticleFrontiers in genetics2013
Evaluation of calling algorithms for array-CGH.
Article in Frontiers in genetics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
8 citing papers in PubMed.
- Computational strategies for copy number variation detection, disease association, and beyond.Genome biology · 2026Review
- Progress in Methods for Copy Number Variation Profiling.International journal of molecular sciences · 2022Review
- Functional in vivo and in vitro effects of 20q11.21 genetic aberrations on hPSC differentiation.Scientific reports · 2020Article
- Clonal copy-number mosaicism in autoreactive T lymphocytes in diabetic NOD mice.Genome research · 2019Article
- Novel de novo frameshift variant in the ASXL3 gene in a child with microcephaly and global developmental delay.Molecular medicine reports · 2019Article
- iSeg: an efficient algorithm for segmentation of genomic and epigenomic data.BMC bioinformatics · 2018Article
- An integrated analysis tool for analyzing hybridization intensities and genotypes using new-generation population-optimized human arrays.BMC genomics · 2016Article
- Hidden Markov Model-Based CNV Detection Algorithms for Illumina Genotyping Microarrays.Cancer informatics · 2014Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Copy number variation (CNV) detection has become an integral part many of genetic studies and new technologies promise to revolutionize our ability to detect and link them to disease. However, recent studies highlight discrepancies in the genome wide CNV profile when measured by different technologies and even by the same technology. Furthermore, the change point algorithms used to call CNVs can have substantial disagreement on the same data set. We focus this article on comparative genomic hybridization (CGH) arrays because this platform lends itself well to accurate statistical modeling. We describe some newer methodological developments in local statistics that are well suited for CNV detection and calling on CGH arrays. Then we use both simulation studies and public data to compare these new local methods with the global methods that currently dominate literature. These results offer suggestions for choosing a particular method and provide insight to the lack of reproducibility that has been seen in the field so far.
Indexed as
Identifiers
What OpenQuestion holds
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.