Topic: Brain proteins, microglia and lab models
GenoTools, a Python package, streamlines population genetics research by integrating ancestry estimation, quality control, and genome-wide association studies capabilities into efficient pipelines. By tracking samples, variants, and quality-specific measures throughout fully customizable pipelines, users can easily manage genetics data for large and small studies. GenoTools' "Ancestry" module renders highly accurate predictions, allowing for high-quality ancestry-specific studies, and enables custom ancestry model training and serialization specified to the user's genotyping or sequencing platform. As the genotype processing engine that powers several large initiatives, including the NIH's Center for Alzheimer's and Related Dementias and the Global Parkinson's Genetics Program, GenoTools was used to process and analyze the UK Biobank and major Alzheimer's disease and Parkinson's disease datasets with over 400,000 genotypes from arrays and 5,000 whole genome sequencing samples and has led to novel discoveries in diverse populations. It has provided replicable ancestry predictions, implemented rigorous quality control, and conducted genetic ancestry-specific genome-wide association studies to identify systematic errors or biases through a single command. GenoTools is a customizable tool that enables users to efficiently analyze and scale genotyping and sequencing (whole genome sequencing and exome) data with reproducible and scalable ancestry, quality control, and genome-wide association studies pipelines.
Cite this study APA, Vancouver, BibTeX · download .bib or .ris
APA 7th
Vitale, D., Koretsky, M. J., Kuznetsov, N., Hong, S., Martin, J., James, M., et al. (2025). GenoTools: an open-source Python package for efficient genotype data quality control and analysis. G3 (Bethesda, Md.). https://doi.org/10.1093/g3journal/jkae268
Vancouver
Vitale D, Koretsky MJ, Kuznetsov N, Hong S, Martin J, James M, et al. GenoTools: an open-source Python package for efficient genotype data quality control and analysis. G3 (Bethesda, Md.). 2025. doi:10.1093/g3journal/jkae268. PMID: 39566101.
BibTeX
@article{vitale2025-39566101,
author = {Vitale, D. and Koretsky, M. J. and Kuznetsov, N. and Hong, S. and Martin, J. and James, M. and Makarious, M. B. and Leonard, H. and others},
title = {{GenoTools: an open-source Python package for efficient genotype data quality control and analysis}},
journal = {G3 (Bethesda, Md.)},
year = {2025},
doi = {10.1093/g3journal/jkae268},
pmid = {39566101},
url = {https://doi.org/10.1093/g3journal/jkae268}
}
Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. The record's author list ends in “et al.”, so not every author is named. Check the citation against the original before you use it.
Key findings
- By tracking samples, variants, and quality-specific measures throughout fully customizable pipelines, users can easily manage genetics data for large and small studies.
- GenoTools' "Ancestry" module renders highly accurate predictions, allowing for high-quality ancestry-specific studies, and enables custom ancestry model training and serialization specified to the user's genotyping or sequencing platform.
- As the genotype processing engine that powers several large initiatives, including the NIH's Center for Alzheimer's and Related Dementias and the Global Parkinson's Genetics Program, GenoTools was used to process and analyze the UK Biobank and major Alzheimer's disease and Parkinson's disease datasets with over 400,000 genotypes from arrays and 5,000 whole genome sequencing samples and has led to novel discoveries in diverse populations.
- It has provided replicable ancestry predictions, implemented rigorous quality control, and conducted genetic ancestry-specific genome-wide association studies to identify systematic errors or biases through a single command.
- GenoTools is a customizable tool that enables users to efficiently analyze and scale genotyping and sequencing (whole genome sequencing and exome) data with reproducible and scalable ancestry, quality control, and genome-wide association studies pipelines.
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Study details
- Evidence strengthLow
How this study scored 41/100
Published in a peer-reviewed journal. Scored zero for study design, sample size, effect reported, studied in people and randomised / blinded because the record does not state it. We have no data on journal's citation record, times cited, citations per year, impact for its field and year, cited by studies here, still being cited, senior author's track record, institution's track record and multi-centre collaboration, so those were left out: it earned 24 of the 58 points we could judge it on, which is 41 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (G3 (Bethesda, Md.)) |
| Journal's citation record | — / 4 | No journal record from OpenAlex — left out of this score |
| Study design | 0 / 12 | No study design recorded — scores zero, not guessed (not stated in the record — scored 0) |
| Strength of evidence | 1 / 5 | Rated “low” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 4 / 5 | 2025 — within 3 year(s) of the newest study here |
| Sample size | 0 / 4 | Participant count not stated — scores zero (not stated in the record — scored 0) |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 0 / 3 | Not stated whether this was studied in people — scores zero (not stated in the record — scored 0) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | — / 7 | No citation count (not found in OpenAlex) — left out of this score |
| Citations per year | — / 5 | No citation count or no year — left out of this score |
| Impact for its field and year | — / 6 | No field-weighted citation impact (OpenAlex has none yet) — left out of this score |
| Cited by studies here | — / 6 | Not yet checked against this library's citation graph — left out of this score |
| Still being cited | — / 4 | No yearly citation counts — left out of this score |
| Senior author's track record | — / 4 | Senior author's record not available — left out of this score |
| Institution's track record | — / 3 | No institution listed in OpenAlex — left out of this score |
| Multi-centre collaboration | — / 3 | Institutions not listed — left out of this score |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 39566101) |
| Free to read | 0 / 2 | Behind a paywall — scores zero |
| Points | 24 / 58 | Scored on 11 of 20 parts. We have no data for the rest, so they are left out: 24 of the 58 points we could judge it on is 41 out of 100. |
| Total | 41 / 100 | — |
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