ArticleJournal of molecular biology2025
CNPI: Rapid Analyses of Human Copy Number Data.
Article in Journal of molecular biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- Whole Genome Sequencing Reveals amedRxiv : the preprint server for health sciences · 2026Article
- Whole-genome sequencing reveals individual and cohort level insights into chromosome 9p syndromes.Genome medicine · 2025Article
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
Tools for genotyping copy number in whole-genome sequencing (WGS) data exist. Despite their availability, there are a limited number of tools that efficiently process this data at scale with rapid compute time, low memory usage, and easy to parse outputs. This is critical as WGS continues to be housed in the "cloud." Copy Number Private Investigator (CNPI) is a computational toolkit (https://github.com/TNTurnerLab/CNPI) that performs several tasks including genotyping of regions of interest, digital karyotype determination, assessment of chromosomal sex, plotting of copy number in regions of the genome, and generation of an Individual-level Copy Number Score (ICNS). Inputs to CNPI include copy number estimates, genome-wide, from WGS data and a corresponding reference annotation file. With these inputs, CNPI can genotype any regions of the genome rapidly. For example, all genes in the genome can be genotyped in <2 s with 1 CPU and <1 GB memory. Benchmarking against gold-standard NA12878 data demonstrated good results with flexibility for users to optimize copy number thresholds based on desired sensitivity and specificity. Usage of CNPI is customizable with a variety of user-tailored functions and arguments. CNPI can be deployed to cloud based environments such as AWS lambda due to its intuitive design, near-zero cost per sample, and availability of compute resources. The application of ICNS has proven to be useful by comparing unaffected individuals to individuals with autism and 9p deletion syndrome, respectively. Overall, CNPI is advantageous for its ability to quickly provide reliable and precise copy number assessments of human genomic data.
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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.