{"entity": "journal", "iuid": "c427a3d3816a44218046e8e886040ca3", "timestamp": "2026-08-20T20:45:19.310Z", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/journal/Cell%20Genom.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/journal/Cell%20Genom"}}, "title": "Cell Genom", "issn": "2666-979X", "issn-l": null, "publications_count": 3, "publications": [{"entity": "publication", "iuid": "1accba29e72d4bf2b6a9fb6c0fd54f20", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/1accba29e72d4bf2b6a9fb6c0fd54f20.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/1accba29e72d4bf2b6a9fb6c0fd54f20"}}, "title": "Secure and federated quantitative trait loci mapping with privateQTL.", "authors": [{"family": "Choi", "given": "Yoolim Annie", "initials": "YA"}, {"family": "Kim", "given": "Yebin", "initials": "Y"}, {"family": "Miao", "given": "Peihan", "initials": "P"}, {"family": "Lappalainen", "given": "Tuuli", "initials": "T"}, {"family": "G\u00fcrsoy", "given": "Gamze", "initials": "G"}], "type": "journal article", "published": "2025-02-12", "journal": {"title": "Cell Genom", "issn": "2666-979X", "volume": "5", "issue": "2", "pages": "100769", "issn-l": null}, "abstract": "Understanding the relationship between genotypes and phenotypes is crucial for advancing personalized medicine. Expression quantitative trait loci (eQTL) mapping plays a significant role by correlating genetic variants to gene expression levels. Despite the progress made by large-scale projects, eQTL mapping still faces challenges in statistical power and privacy concerns. Multi-site studies can increase sample sizes but are hindered by privacy issues. We present privateQTL, a novel framework leveraging secure multi-party computation for secure and federated eQTL mapping. When tested in a real-world scenario with data from different studies, privateQTL outperformed meta-analysis by accurately correcting for covariates and batch effect and retaining higher accuracy and precision for both eGene-eVariant mapping and effect size estimation. In addition, privateQTL is modular and scalable, making it adaptable for other molecular phenotypes and large-scale studies. Our results indicate that privateQTL is a practical solution for privacy-preserving collaborative eQTL mapping.", "doi": "10.1016/j.xgen.2025.100769", "pmid": "39947138", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC11872535"}, {"db": "pii", "key": "S2666-979X(25)00025-4"}], "notes": [], "created": "2026-08-20T08:06:33.772Z", "modified": "2026-08-20T08:06:33.814Z"}, {"entity": "publication", "iuid": "45ed0e7d11e64d6f8393598672f64147", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/45ed0e7d11e64d6f8393598672f64147.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/45ed0e7d11e64d6f8393598672f64147"}}, "title": "Identifying genetic regulatory variants that affect transcription factor activity.", "authors": [{"family": "Li", "given": "Xiaoting", "initials": "X"}, {"family": "Lappalainen", "given": "Tuuli", "initials": "T"}, {"family": "Bussemaker", "given": "Harmen J", "initials": "HJ"}], "type": "journal article", "published": "2023-09-13", "journal": {"title": "Cell Genom", "issn": "2666-979X", "volume": "3", "issue": "9", "pages": "100382", "issn-l": null}, "abstract": "Genetic variants affecting gene expression levels in humans have been mapped in the Genotype-Tissue Expression (GTEx) project. Trans-acting variants impacting many genes simultaneously through a shared transcription factor (TF) are of particular interest. Here, we developed a generalized linear model (GLM) to estimate protein-level TF activity levels in an individual-specific manner from GTEx RNA sequencing (RNA-seq) profiles. It uses observed differential gene expression after TF perturbation as a predictor and, by analyzing differential expression within pairs of neighboring genes, controls for the confounding effect of variation in chromatin state along the genome. We inferred genotype-specific activities for 55 TFs across 49 tissues. Subsequently performing genome-wide association analysis on this virtual trait revealed TF activity quantitative trait loci (aQTLs) that, as a set, are enriched for functional features. Altogether, the set of tools we introduce here highlights the potential of genetic association studies for cellular endophenotypes based on a network-based multi-omics approach. The transparent peer review record is available.", "doi": "10.1016/j.xgen.2023.100382", "pmid": "37719147", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC10504674"}, {"db": "pii", "key": "S2666-979X(23)00179-9"}], "notes": [], "created": "2026-08-20T08:06:31.827Z", "modified": "2026-08-20T08:06:31.882Z"}, {"entity": "publication", "iuid": "6f1b0a0380eb4d2ca80f942e089a5d08", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/6f1b0a0380eb4d2ca80f942e089a5d08.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/6f1b0a0380eb4d2ca80f942e089a5d08"}}, "title": "Multiset correlation and factor analysis enables exploration of multi-omics data.", "authors": [{"family": "Brown", "given": "Brielin C", "initials": "BC"}, {"family": "Wang", "given": "Collin", "initials": "C"}, {"family": "Kasela", "given": "Silva", "initials": "S"}, {"family": "Aguet", "given": "Fran\u00e7ois", "initials": "F"}, {"family": "Nachun", "given": "Daniel C", "initials": "DC"}, {"family": "Taylor", "given": "Kent D", "initials": "KD"}, {"family": "Tracy", "given": "Russell P", "initials": "RP"}, {"family": "Durda", "given": "Peter", "initials": "P"}, {"family": "Liu", "given": "Yongmei", "initials": "Y"}, {"family": "Johnson", "given": "W Craig", "initials": "WC"}, {"family": "Van Den Berg", "given": "David", "initials": "D"}, {"family": "Gupta", "given": "Namrata", "initials": "N"}, {"family": "Gabriel", "given": "Stacy", "initials": "S"}, {"family": "Smith", "given": "Joshua D", "initials": "JD"}, {"family": "Gerzsten", "given": "Robert", "initials": "R"}, {"family": "Clish", "given": "Clary", "initials": "C"}, {"family": "Wong", "given": "Quenna", "initials": "Q"}, {"family": "Papanicolau", "given": "George", "initials": "G"}, {"family": "Blackwell", "given": "Thomas W", "initials": "TW"}, {"family": "Rotter", "given": "Jerome I", "initials": "JI"}, {"family": "Rich", "given": "Stephen S", "initials": "SS"}, {"family": "Barr", "given": "R Graham", "initials": "RG"}, {"family": "Ardlie", "given": "Kristin G", "initials": "KG"}, {"family": "Knowles", "given": "David A", "initials": "DA"}, {"family": "Lappalainen", "given": "Tuuli", "initials": "T"}], "type": "journal article", "published": "2023-08-09", "journal": {"title": "Cell Genom", "issn": "2666-979X", "volume": "3", "issue": "8", "pages": "100359", "issn-l": null}, "abstract": "Multi-omics datasets are becoming more common, necessitating better integration methods to realize their revolutionary potential. Here, we introduce multi-set correlation and factor analysis (MCFA), an unsupervised integration method tailored to the unique challenges of high-dimensional genomics data that enables fast inference of shared and private factors. We used MCFA to integrate methylation markers, protein expression, RNA expression, and metabolite levels in 614 diverse samples from the Trans-Omics for Precision Medicine/Multi-Ethnic Study of Atherosclerosis multi-omics pilot. Samples cluster strongly by ancestry in the shared space, even in the absence of genetic information, while private spaces frequently capture dataset-specific technical variation. Finally, we integrated genetic data by conducting a genome-wide association study (GWAS) of our inferred factors, observing that several factors are enriched for GWAS hits and trans-expression quantitative trait loci. Two of these factors appear to be related to metabolic disease. Our study provides a foundation and framework for further integrative analysis of ever larger multi-modal genomic datasets.", "doi": "10.1016/j.xgen.2023.100359", "pmid": "37601969", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC10435377"}, {"db": "pii", "key": "S2666-979X(23)00142-8"}], "notes": [], "created": "2026-08-20T08:06:30.065Z", "modified": "2026-08-20T08:06:30.135Z"}], "created": "2026-08-20T08:06:30.094Z", "modified": "2026-08-20T08:06:30.094Z"}