MBV : a method to solve sample mislabeling and detect technical bias in large combined genotype and sequencing assay datasets

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Detecting and Estimating Contamination of Human DNA Samples in Sequencing and Array-Based Genotype Data

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Population Variation and Genetic Control of Modular Chromatin Architecture in Humans

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A tool for RNA sequencing sample identity check

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A compendium of uniformly processed human gene expression and splicing quantitative trait loci

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Dynamic landscape of immune cell-specific gene regulation in immune-mediated diseases

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Fine-mapping, trans-ancestral and genomic analyses identify causal variants, cells, genes and drug targets for type 1 diabetes

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Cell-type-specific cis-eQTLs in eight human brain cell types identify novel risk genes for psychiatric and neurological disorders

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Genetic analysis of the human microglial transcriptome across brain regions, aging and disease pathologies

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Chromatin three-dimensional interactions mediate genetic effects on gene expression

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An atlas of genetic scores to predict multi-omic traits

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Integrative transcriptomic analysis of the amyotrophic lateral sclerosis spinal cord implicates glial activation and suggests new risk genes

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A software tool ‘CroCo’ detects pervasive cross-species contamination in next generation sequencing data

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Molecular quantitative trait loci

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Four groups of type 2 diabetes contribute to the etiological and clinical heterogeneity in newly diagnosed individuals: An IMI DIRECT study

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snRNA-seq stratifies multiple sclerosis patients into distinct white matter glial responses

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Chromatin domain alterations linked to 3D genome organization in a large cohort of schizophrenia and bipolar disorder brains

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Efficient differential expression analysis of large-scale single-cell transcriptomics data using Dreamlet

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The effect of genetic variation on promoter usage and enhancer activity

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Integrative genomic analyses identify candidate causal genes for calcific aortic valve stenosis involving tissue-specific regulation

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Genetic analysis of blood molecular phenotypes reveals common properties in the regulatory networks affecting complex traits

Brown, A. A., Fernandez-Tajes, J. J., Hong, M., Brorsson, C., Koivula, R. W., Davtian, D., Dupuis, T., Sartori, A., Michalettou, T.-D., Forgie, I. M., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-40569-3 · Cited by 43 · see citing works

Dissecting the genetic heterogeneity of gastric cancer

Hess, T., Maj, C., Gehlen, J., Borisov, O., Haas, S., Gockel, I., Vieth, M. W., Piessen, G., Alakus, H., Vashist, Y. K., et al. (2023) · EBioMedicine · doi:10.1016/j.ebiom.2023.104616 · Cited by 34 · see citing works

The contribution of genetic determinants of blood gene expression and splicing to molecular phenotypes and health outcomes

Tokolyi, A., Persyn, E., Nath, A. P., Burnham, K. L., Marten, J., Vanderstichele, T., Tardáguila, M., Stacey, D., Farr, B. W., Iyer, V., et al. (2025) · Nature Genetics · doi:10.1038/s41588-025-02096-3 · Cited by 36 · see citing works

SPEAQeasy: a scalable pipeline for expression analysis and quantification for R/bioconductor-powered RNA-seq analyses

Eagles, N. J., Burke, E. E., Leonard, J., Barry, B. K., Stolz, J. M., Huuki-Myers, L. A., Phan, B. N., Larios‐Serrato, V., Gutiérrez-Millán, E., Aguilar-Ordóñez, I., et al. (2021) · BMC Bioinformatics · doi:10.1186/s12859-021-04142-3 · Cited by 24 · see citing works

ABCA7 variants impact phosphatidylcholine and mitochondria in neurons

von Maydell, D., Wright, S. E., Pao, P.-C., Staab, C., King, O., Spitaleri, A., Bonner, J. M., Liu, L., Yu, C. J., Chiu, C.-C., et al. (2025) · Nature · doi:10.1038/s41586-025-09520-y · Cited by 35 · see citing works

Kssd: sequence dimensionality reduction by k-mer substring space sampling enables real-time large-scale datasets analysis

Yi, H., Lin, Y., Lin, C., & Jin, W. (2021) · Genome biology · doi:10.1186/s13059-021-02303-4 · Cited by 21 · see citing works

Regulation of HLA class I expression by non-coding gene variations

Bettens, F., Ongen, H., Rey, G., Bühler, S., Sollet, Z. C., Dermitzakis, E. T., & Villard, J. (2022) · PLoS Genetics · doi:10.1371/journal.pgen.1010212 · Cited by 22 · see citing works

Multi-omic Analyses Shed Light on The Genetic Control of High-altitude Adaptation in Sheep

Li, C., Chen, B., Suo, L., Pu, P., Zhu, X., Zhou, S., Kalds, P., Zhang, K., Bhati, M., Leonard, A. S., et al. (2024) · Genomics Proteomics & Bioinformatics · doi:10.1093/gpbjnl/qzae030 · Cited by 22 · see citing works

eQTLs identify regulatory networks and drivers of variation in the individual response to sepsis

Burnham, K. L., Milind, N., Lee, W., Kwok, A. J., Cano-Gamez, K., Mi, Y., Geoghegan, C. G., Zhang, P., Addison, J., Galley, H. F., et al. (2024) · Cell Genomics · doi:10.1016/j.xgen.2024.100587 · Cited by 21 · see citing works

MR-link-2: pleiotropy robust cis Mendelian randomization validated in three independent reference datasets of causality

van der Graaf, A., Warmerdam, R., Auwerx, C., Boltz, T., Boomsma, D. I., Brown, A., Cheruiyot, E. K., Davenport, E. E., Dupuis, T., Esko, T., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-60868-1 · Cited by 17 · see citing works

Cell-Type Composition Affects Adipose Gene Expression Associations With Cardiometabolic Traits

Brotman, S. M., Oravilahti, A., Rosen, J. D., Alvarez, M., Heinonen, S., van der Kolk, B. W., Silva, L. F., Perrin, H. J., Vadlamudi, S., Pylant, C. L., et al. (2023) · Diabetes · doi:10.2337/db23-0365 · Cited by 17 · see citing works

Population-scale cross-disorder atlas of the human prefrontal cortex at single-cell resolution

Fullard, J. F., Nm, P., Lee, D., Mathur, D. D., Therrien, K., Hong, A., Casey, C., Shao, Z., Alvia, M., Argyriou, S., et al. (2025) · Scientific Data · doi:10.1038/s41597-025-04687-5 · Cited by 17 · see citing works

Assessment of kinship detection using RNA-seq data

Blay, N., Casas, E., Galván‐Femenía, I., Graffelman, J., de Cid, R., & Vavouri, T. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz776 · Cited by 16 · see citing works

Non-coding autoimmune risk variant defines role for ICOS in T peripheral helper cell development

Kim, T., Martínez‐Bonet, M., Wang, Q., Hackert, N. S., Sparks, J. A., Baglaenko, Y., Koh, B., Darbousset, R., Briviesca, R. L., Chen, X., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-46457-8 · Cited by 16 · see citing works

Gene expression QTL mapping in stimulated iPSC-derived macrophages provides insights into common complex diseases

Panousis, N. I., Garwany, O. E., Knights, A. J., Rop, J., Kumasaka, N., Imaz, M., Vilarino, L. B., Tsingene, A., Tokolyi, A., Barnett, A., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-61670-9 · Cited by 16 · see citing works

A brief guide to analyzing expression quantitative trait loci

Ko, B. S., Lee, S. B., & Kim, T.-K. (2024) · Molecules and Cells · doi:10.1016/j.mocell.2024.100139 · Cited by 16 · see citing works

Multi-omics analysis in primary T cells elucidates mechanisms behind disease-associated genetic loci

Shi, C., Zhao, D.-Y., Butler, J., Frantzeskos, A., Rossi, S., Ding, J., Ferrazzano, C., Wynn, C., Hum, R., Richards, E., et al. (2023) · Genome Biology · doi:10.1186/s13059-025-03492-y · Cited by 14 · see citing works

A multi-region single nucleus transcriptomic atlas of Parkinson’s disease

Prashant, N. M., Fullard, J. F., Clarence, T., Mathur, D. D., Casey, C., Hennigan, E., Alvia, M., Krause-Massaguer, J., Barreda, A., Davis, D. A., et al. (2024) · Scientific Data · doi:10.1038/s41597-024-04117-y · Cited by 15 · see citing works

Atlas of genetic effects in human microglia transcriptome across brain regions, aging and disease pathologies

Lopes, K. P., Snijders, G. J. L., Humphrey, J., de Witte, L. D., & Raj, T. (2021) · Alzheimer s & Dementia · doi:10.1002/alz.050942 · Cited by 17 · see citing works

The RNA editing landscape in acute myeloid leukemia reveals associations with disease mutations and clinical outcome

Meduri, E., Breeze, C. E., Marando, L., Richardson, S. E., & Huntly, B. J. P. (2022) · iScience · doi:10.1016/j.isci.2022.105622 · Cited by 13 · see citing works

Integrative genomics sheds light on the immunogenetics of tuberculosis in cattle

O'Grady, J. F., McHugo, G. P., Ward, J. A., Hall, T. J., O’Donnell, S. L. F., Correia, C. N., Browne, J. A., McDonald, M., Gormley, E. P., Riggio, V., et al. (2025) · Communications Biology · doi:10.1038/s42003-025-07846-x · Cited by 10 · see citing works

ABCA7 Loss-of-Function Variants Impact Phosphatidylcholine Metabolism in the Human BrainPreprint

von Maydell, D. K., Wright, S., Pao, P., Staab, C., King, O., Spitaleri, A., Bonner, J. M., Liu, L., Yu, C. J., Chiu, C.-C., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.09.05.556135 · Cited by 10 · see citing works

Fine-mapping and molecular characterisation of primary sclerosing cholangitis genetic risk loci

Goode, E. C., Fachal, L., Panousis, N., Moutsianas, L., McIntyre, R. E., Bai, B. Y. H., Kawasaki, N., Wittmann, A., Raine, T., Rushbrook, S., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-53602-w · Cited by 6 · see citing works

Splicing QTL mapping in stimulated macrophages associates low-usage splice junctions with immune-mediated disease risk

Garwany, O. E., Panousis, N. I., Knights, A. J., Kumasaka, N., Imaz, M., Vilarino, L. B., Tsingene, A., Tokolyi, A., Cotobal, C., Alegbe, T., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-61669-2 · Cited by 7 · see citing works

Misexpression of inactive genes in whole blood is associated with nearby rare structural variants

Vanderstichele, T., Burnham, K. L., de Klein, N., Tardáguila, M., Howell, B., Walter, K., Kundu, K., Koeppel, J., Lee, W., Tokolyi, A., et al. (2024) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2024.06.017 · Cited by 5 · see citing works

Aortic valve-specific genes dysregulated in calcific aortic valve stenosis as potential biomarkers and therapeutic targets

Zamani, P., Houessou, U., Manikpurage, H. D., Li, Z., Dahmene, M., Gaudreault, N., Dagenais, F., Clavel, M.-A., Pibarot, P., Arsenault, B. J., et al. (2025) · Human Genetics and Genomics Advances · doi:10.1016/j.xhgg.2025.100448 · Cited by 3 · see citing works

Quantification of heavy metal exposure in a British population cohort links total mercury levels in plasma with skin tissue-specific changes in mitochondrial-related gene expression

de Streek, M. V., Ali, A. T., Moustafa, J. S. E.-S., Glastonbury, C. A., Spector, T. D., Valdes, A. M., Staff, J. F., Morton, J., Hodgkinson, A., Bell, J. T., et al. (2025) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2025.178427 · Cited by 3 · see citing works

Lifespan single-cell transcriptomic atlas of the human prefrontal cortex

Yang, H., Clarence, T., Scott, M. R., Wang, X., Prashant, N. M., Pjanic, M., Venkatesh, S., Hong, A., Casey, C., Murphy, S. E., et al. (2026) · Nature · doi:10.1038/s41586-026-10271-7 · Cited by 12 · see citing works

The genetic regulation of the gastric transcriptome is associated with metabolic and obesity-related traits and diseases

Koebbe, L. L., Hess, T., Giel, A.-S., Bigge, J., Gehlen, J., Schueller, V., Geppert, M., Dumoulin, F. L., Heller, J., Schepke, M., et al. (2024) · Physiological Genomics · doi:10.1152/physiolgenomics.00120.2023 · Cited by 3 · see citing works

Single-nucleus analysis of the adult human olfactory epithelium uncovers shared neurogenesis programs with the brain

Song, L., Fullard, J. F., Coleman, C., Hennigan, E., Casey, C., Wang, X., Kawatake-Kuno, A., Argyriou, S., Kleopoulos, S., DeMaria, S., et al. (2026) · Nature Communications · doi:10.1038/s41467-026-75722-1 · Cited by 1 · see citing works

Non-coding autoimmune risk variant accelerates T peripheral helper cell development via ICOSPreprint

Kim, T., Martínez‐Bonet, M., Wang, Q., Hackert, N. S., Sparks, J. A., Baglaenko, Y., Koh, B., Darbousset, R., Briviesca, R. L., Chen, X., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.12.16.520733 · Cited by 1 · see citing works

Multi-omics analysis in primary T cells elucidates mechanisms behind disease associated genetic lociPreprint

Orozco, G., Shi, C., Zhao, D., Rossi, S., Frantzeskos, A., Ding, J., Ferrazzano, C., Wynn, C., Hum, R. M., Richards, E., et al. (2023) · Research Square · doi:10.21203/rs.3.rs-3256438/v1 · Cited by 1 · see citing works

A multi-omics resource of B cell activation reveals genetic mechanisms for immune-mediated diseasesPreprint

Aguiar, V. R. C., Franco, M. E., Aziz, N. A., Fernandez‐Salinas, D., Chiñas, M., Colantuoni, M., Xiao, Q., Hackert, N. S., Liao, Y., Cervantes‐Díaz, R., et al. (2025) · medRxiv · doi:10.1101/2025.05.22.25328104 · Cited by 1 · see citing works

A Transcriptomic Roadmap of Parkinson’s Disease Progression at Single Cell ResolutionPreprint

Clarence, T., Masse, N. Y., Porras, C., Nm, P., Berretta, S., Haroutunian, V. H., Davis, D. A., Scott, W. K., Hoffman, G. E., Fullard, J. F., et al. (2025) · medRxiv · doi:10.1101/2025.07.30.25332436 · Cited by 1 · see citing works

Improved Identification of Large-effect Rare Genetic Variants using Haplotype Aggregated Allele-specific Expression DataPreprint

Ganapathy, K. R., Broly, M., Silverstein, S., Mendoza, M., Song, E., Kotis, B., Hoffman, P., Torkamani, A., Adams, D. R., Bonnemann, C., et al. (2025) · medRxiv · doi:10.64898/2025.12.16.25341855

Genomic dissection of Systemic Lupus Erythematosus: Distinct Susceptibility, Activity and Severity SignaturesPreprint

Panousis, N. I., Bertsias, G. K., Ongen, H., Gergianaki, I., Tektonidou, M. G., Trachana, M., Romano, L., Bielser, D., Howald, C., Pamfil, C. A. M., et al. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/255109

Skeletal muscle enhancer programming of intrinsic cardiorespiratory fitnessPreprint

Weitzel, A. M., Orchard, P., Evans, C. R., Manickam, N., Treutelaar, M. K., Britton, S. L., Koch, L. G., Li, J. Z., Parker, S. C. J., & Burant, C. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.10.02.679855

Additional file 1 of Kssd: sequence dimensionality reduction by k-mer substring space sampling enables real-time large-scale datasets analysis

Yi, H., Lin, Y., Lin, C., & Jin, W. (2021) · Figshare · doi:10.6084/m9.figshare.14228060

Additional file 4 of Kssd: sequence dimensionality reduction by k-mer substring space sampling enables real-time large-scale datasets analysis

Yi, H., Lin, Y., Lin, C., & Jin, W. (2021) · Figshare · doi:10.6084/m9.figshare.14228069

Additional file 5 of Kssd: sequence dimensionality reduction by k-mer substring space sampling enables real-time large-scale datasets analysis

Yi, H., Lin, Y., Lin, C., & Jin, W. (2021) · Figshare · doi:10.6084/m9.figshare.14228075

Downregulated transcription in chromosomal domains of midbrain dopamine neurons linked to schizophrenia

Singh, S., Iskhakova, M., Lambert, T. Y., Valada, A., Shokrian, N., Evans, V. D., Bendl, J. M., Auluck, P. K., Marenco, S., Wang, M., et al. (2026) · Nature Communications · doi:10.1038/s41467-026-71281-7

A long-read human pangenome initiative for comprehensive interpretation of nuclear-embedded mitochondrial DNA

Fu, L., Chen, J., Lian, D., Du, S., Wu, D., Yang, C., Wang, Z., Ma, H., Li, Z., Lake, N. J., et al. (2026) · Nature Communications · doi:10.1038/s41467-026-71348-5

Rapid convergence toward an agriculturalist regulatory landscape following lifestyle transition in Bornean hunter-gatherersPreprint

Kusuma, P., Jacobs, G. S., Luqman, H., Ma'ruf, F. A., Limardi, P., Sudoyo, H., Lansing, J. S., Malik, S. G., & Romero, I. G. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.08.09.743820

Maternal immune gene expression trajectories and dynamic genetic regulation throughout pregnancyPreprint

Hoffman, S., Burnham, K. L., Cook, E., Cohen, C. E., Sovio, U., Jones, D. S., Smith, G. C. S., & Davenport, E. E. (2026) · medRxiv · doi:10.64898/2026.09.22.26363644

reGenotyper: Detecting mislabeled samples in genetic data

Zych, K., Snoek, B. L., Elvin, M., Rodriguez, M., van der Velde, K. J., Arends, D., Westra, H.-J., Swertz, M. A., Poulin, G. B., Kammenga, J. E., et al. (2017) · PLoS ONE · doi:10.1371/journal.pone.0171324 · Cited by 17 · see citing works

BAM-matcher: a tool for rapid NGS sample matching

Wang, P. P.-S., Parker, W. T., Branford, S., & SCHREIBER, A. W. (2016) · Bioinformatics · doi:10.1093/bioinformatics/btw239 · Cited by 64 · see citing works

BAMixChecker: an automated checkup tool for matched sample pairs in NGS cohort

Chun, H., & Kim, S. (2019) · Bioinformatics · doi:10.1093/bioinformatics/btz479 · Cited by 10 · see citing works

Detecting sample swaps in diverse NGS data types using linkage disequilibrium

Javed, N. M., Farjoun, Y., Fennell, T. J., Epstein, C. B., Bernstein, B., & Noam Shoresh, F. (2020) · Nature Communications · doi:10.1038/s41467-020-17453-5 · Cited by 32 · see citing works

RNA Strain-Match: A tool for matching single-nucleus, single-cell, or bulk RNA-sequencing alignment data to its corresponding genotypePreprint

Willcox, J. A. L., Telpoukhovskaia, M. A., Hadad, N., Boas, S. M., Dunn, A. R., Saul, M. C., Ashbrook, D. G., Williams, R. W., O’Connell, K. M. S., & Kaczorowski, C. C. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.07.14.548847 · Cited by 1 · see citing works