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• Poland Holy Cross Voivodeship - WGS

  This project used NGS (next generation sequencing), using Illumina NOVASEQ 6000 and Illumina DRAGEN aligner. The dataset includes BAM and BAM.BAI files from Whole Genome Sequencing of 6 samples (6 female of Holy Cross Voivodeship, Poland from POPULOUS collection). Library Construction Protocol: Illumina DNA PCR-Free Prep, Tagmentation. Reference Genome: GRCh37.

  Dataset EGAD50000000162

• Poland Warmian-Mazurian Voivodeship WGS

  This project used NGS (next generation sequencing), using Illumina NOVASEQ 6000 and Illumina DRAGEN aligner. The dataset includes BAM and BAM.BAI files from Whole Genome Sequencing of 15 samples (8 female, 7 male of Warmian-Mazurian Voivodeship, Poland from POPULOUS collection). Library Construction Protocol: Illumina DNA PCR-Free Prep, Tagmentation. Reference Genome: GRCh37.

  Dataset EGAD50000000128

• Poland Lublin Voivodeship - WGS

  This project used NGS (next generation sequencing), using Illumina NOVASEQ 6000 and Illumina DRAGEN aligner. The dataset includes BAM and BAM.BAI files from Whole Genome Sequencing of 24 samples (14 female, 10 male of Lublin Voivodeship, Poland from POPULOUS collection). Library Construction Protocol: Illumina DNA PCR-Free Prep, Tagmentation. Reference Genome: GRCh37.

  Dataset EGAD50000000155

• Poland Lodz Voivodeship - WGS

  This project used NGS (next generation sequencing), using Illumina NOVASEQ 6000 and Illumina DRAGEN aligner. The dataset includes BAM and BAM.BAI files from Whole Genome Sequencing of 41 samples (20 female, 21 male of Lodz Voivodeship, Poland from POPULOUS collection). Library Construction Protocol: Illumina DNA PCR-Free Prep, Tagmentation. Reference Genome: GRCh37.

  Dataset EGAD50000000165

• Poland Lesser Voivodeship - WGS

  This project used NGS (next generation sequencing), using Illumina NOVASEQ 6000 and Illumina DRAGEN aligner. The dataset includes BAM and BAM.BAI files from Whole Genome Sequencing of 32 samples (14 female, 18 male of Lesser Voivodeship, Poland from POPULOUS collection). Library Construction Protocol: Illumina DNA PCR-Free Prep, Tagmentation. Reference Genome: GRCh37.

  Dataset EGAD50000000166

• Poland Mazovia Voivodeship - WGS

  This project used NGS (next generation sequencing), using Illumina NOVASEQ 6000 and Illumina DRAGEN aligner. The dataset includes BAM and BAM.BAI files from Whole Genome Sequencing of 43 samples (16 female, 27 male of Mazovia Voivodeship, Poland from POPULOUS collection). Library Construction Protocol: Illumina DNA PCR-Free Prep, Tagmentation. Reference Genome: GRCh37.

  Dataset EGAD50000000164

• Poland Greater Poland Voivodeship - WGS

  This project used NGS (next generation sequencing), using Illumina NOVASEQ 6000 and Illumina DRAGEN aligner. The dataset includes BAM and BAM.BAI files from Whole Genome Sequencing of 37 samples (19 female, 18 male of Greater Voivodeship, Poland from POPULOUS collection). Library Construction Protocol: Illumina DNA PCR-Free Prep, Tagmentation. Reference Genome: GRCh37.

  Dataset EGAD50000000161

• Poland Subcarpathian Voivodeship - WGS

  This project used NGS (next generation sequencing), using Illumina NOVASEQ 6000 and Illumina DRAGEN aligner. The dataset includes BAM and BAM.BAI files from Whole Genome Sequencing of 22 samples (11 female, 11 male of Subcarpathian Voivodeship, Poland from POPULOUS collection). Library Construction Protocol: Illumina DNA PCR-Free Prep, Tagmentation. Reference Genome: GRCh37.

  Dataset EGAD50000000157

• Poland Pomeranian Voivodeship - WGS

  This project used NGS (next generation sequencing), using Illumina NOVASEQ 6000 and Illumina DRAGEN aligner. The dataset includes BAM and BAM.BAI files from Whole Genome Sequencing of 25 samples (14 female, 11 male of Pomeranian Voivodeship, Poland from POPULOUS collection). Library Construction Protocol: Illumina DNA PCR-Free Prep, Tagmentation. Reference Genome: GRCh37.

  Dataset EGAD50000000160

• Poland Lower Silesian Voivodeship - WGS

  This project used NGS (next generation sequencing), using Illumina NOVASEQ 6000 and Illumina DRAGEN aligner. The dataset includes BAM and BAM.BAI files from Whole Genome Sequencing of 30 samples (15 female, 15 male of Lower Silesian Voivodeship, Poland from POPULOUS collection). Library Construction Protocol: Illumina DNA PCR-Free Prep, Tagmentation. Reference Genome: GRCh37.

  Dataset EGAD50000000156

• Poland Silesian Voivodeship - WGS

  This project used NGS (next generation sequencing), using Illumina NOVASEQ 6000 and Illumina DRAGEN aligner. The dataset includes BAM and BAM.BAI files from Whole Genome Sequencing of 47 samples (23 female, 24 male of Silesian Voivodeship, Poland from POPULOUS collection). Library Construction Protocol: Illumina DNA PCR-Free Prep, Tagmentation. Reference Genome: GRCh37.

  Dataset EGAD50000000163

• Poland Kuyavian-Pomeranian Voivodeship - WGS

  This project used NGS (next generation sequencing), using Illumina NOVASEQ 6000 and Illumina DRAGEN aligner. The dataset includes BAM and BAM.BAI files from Whole Genome Sequencing of 22 samples (11 female, 11 male of Kuyavian-Pomeranian Voivodeship, Poland from POPULOUS collection). Library Construction Protocol: Illumina DNA PCR-Free Prep, Tagmentation. Reference Genome: GRCh37.

  Dataset EGAD50000000158

• Poland West Pomeranian Voivodeship - WGS

  This project used NGS (next generation sequencing), using Illumina NOVASEQ 6000 and Illumina DRAGEN aligner. The dataset includes BAM and BAM.BAI files from Whole Genome Sequencing of 17 samples (7 female, 10 male of West Pomeranian Voivodeship, Poland from POPULOUS collection). Library Construction Protocol: Illumina DNA PCR-Free Prep, Tagmentation. Reference Genome: GRCh37.

  Dataset EGAD50000000129

• cfMeDIP data for 14 Barrier samples

  We analyzed the cell free DNA methylomes using 14 plasma samples from patients with mCRPC in the Barrier cohort. Methylation was profiled using the methylated DNA immunoprecipitation coupled to next generation sequencing (MeDIP) technology.

  Dataset EGAD00001008712

• NHLBI TOPMed: GOLDN Epigenetic Determinants of Lipid Response to Dietary Fat and Fenofibrate

  The GOLDN study was initiated to assess how genetic factors interact with environmental (diet and drug) interventions to influence blood levels of triglycerides and other atherogenic lipid species and inflammation markers (registered at clinicaltrials.gov, number NCT00083369). The study recruited Caucasian participants primarily from three-generational pedigrees from two NHLBI Family Heart Study (FHS) field centers (Minneapolis, MN and Salt Lake City, UT). Only families with at least two siblings were recruited and only participants who did not take lipid-lowering agents (pharmaceuticals or nutraceuticals) for at least 4 weeks prior to the initial visit were included. The diet intervention followed the protocol of Patsch et al. (1992). The whipping cream (83% fat) meal had 700 Calories/m2 body surface area (2.93 mJ/m2 body surface area): 3% of calories were derived from protein (instant nonfat dry milk) and 14% from carbohydrate (sugar). The ratio of polyunsaturated to saturated fat was 0.06 and the cholesterol content of the average meal was 240 mg. The mixture was blended with ice and flavorings. Blood samples were drawn immediately before (fasting) and at 3.5 and 6 hours after consuming the high-fat meal. The diet intervention was administered at baseline as well as after a 3-week treatment with 160 mg micronized fenofibrate. Participants were given the option to complete one or both (diet and drug) interventions. Of all participants, 1079 had phenotypic data and provided appropriate consent, and underwent whole genome sequencing through the Trans-Omics for Precision Medicine (TOPMed) program. Comprehensive phenotypic and pedigree data for GOLDN study participants are available through dbGaP phs000741.

  Study phs001359

• Genetic Epidemiology Network of Arteriopathy (GENOA)

  The Genetic Epidemiology Network of Arteriopathy (GENOA) is one of four networks in the NHLBI Family-Blood Pressure Program (FBPP). GENOA's long-term objective is to elucidate the genetics of target organ complications of hypertension, including both atherosclerotic and arteriolosclerotic complications involving the heart, brain, kidneys, and peripheral arteries. The longitudinal GENOA Study recruited European-American and African-American sibships with at least 2 individuals with clinically diagnosed essential hypertension before age 60 years. All other members of the sibship were invited to participate regardless of their hypertension status. Participants were diagnosed with hypertension if they had either 1) a previous clinical diagnosis of hypertension by a physician with current anti-hypertensive treatment, or 2) an average systolic blood pressure ≥ 140 mm Hg or diastolic blood pressure ≥ 90 mm Hg based on the second and third readings at the time of their clinic visit. The Family Blood Pressure Program (FBPP), GENOA's parent program, is an unprecedented collaboration to identify genes influencing blood pressure (BP) levels, hypertension, and its target-organ damage. This program has conducted over 21,000 physical examinations, assembled a shared database of several hundred BP and hypertension-related phenotypic measurements, completed genome-wide linkage analyses for BP, hypertension, and hypertension associated risk factors and complications, and published over 130 manuscripts on program findings. The FBPP emerged from what was initially funded as four independent networks of investigators (HyperGEN, GenNet, SAPPHIRe and GENOA) competing to identify genetic determinants of hypertension in multiple ethnic groups. Realizing the greater likelihood of success through collaboration, the investigators created a single confederation with program-wide and network-specific goals.

  Study phs001238

• NHLBI TOPMed: Genetic Epidemiology Network of Arteriopathy (GENOA)

  The Genetic Epidemiology Network of Arteriopathy (GENOA) is one of four networks in the NHLBI Family-Blood Pressure Program (FBPP). GENOA's long-term objective is to elucidate the genetics of target organ complications of hypertension, including both atherosclerotic and arteriolosclerotic complications involving the heart, brain, kidneys, and peripheral arteries. The longitudinal GENOA Study recruited European-American and African-American sibships with at least 2 individuals with clinically diagnosed essential hypertension before age 60 years. All other members of the sibship were invited to participate regardless of their hypertension status. Participants were diagnosed with hypertension if they had either 1) a previous clinical diagnosis of hypertension by a physician with current anti-hypertensive treatment, or 2) an average systolic blood pressure = 140 mm Hg or diastolic blood pressure = 90 mm Hg based on the second and third readings at the time of their clinic visit. Only participants of the African-American Cohort were sequenced through TOPMed. The Family Blood Pressure Program (FBPP), GENOA's parent program, is an unprecedented collaboration to identify genes influencing blood pressure (BP) levels, hypertension, and its target-organ damage. This program has conducted over 21,000 physical examinations, assembled a shared database of several hundred BP and hypertension-related phenotypic measurements, completed genome-wide linkage analyses for BP, hypertension, and hypertension associated risk factors and complications, and published over 130 manuscripts on program findings. The FBPP emerged from what was initially funded as four independent networks of investigators (HyperGEN, GenNet, SAPPHIRe and GENOA) competing to identify genetic determinants of hypertension in multiple ethnic groups. Realizing the greater likelihood of success through collaboration, the investigators created a single confederation with program-wide and network-specific goals. Comprehensive phenotypic data for GENOA study participants are available through dbGaP phs001238.

  Study phs001345

• The Human Phenotype Project (HPP) is a large-scale deep-phenotype prospective longitudinal and ethnically diverse cohort

  The Human Phenotype Project (HPP) is a large-scale deep-phenotype prospective longitudinal and ethnically diverse cohort and biobank that we established. To date, approximately 28,000 participants have enrolled in the study, with over 13,000 having completed their initial visit. The project is aimed at identifying novel molecular signatures with diagnostic, prognostic and therapeutic value, and at developing AI-based predictive models for disease onset and progression. A unique feature of the HPP is its deep and longitudinal profiling that includes medical history, lifestyle and nutritional habits, vital signs, anthropometrics, blood tests, continuous glucose and sleep monitoring, imaging modalities and molecular profiling of the transcriptome, genetics, gut, vaginal and oral microbiome, metabolome and immune system. For several of these modalities, the HPP is the first or largest cohort of its kind. Our analyses of this data provide novel insights into the variation of phenotypes with age and ethnicity, highlighting the importance of having ethnically diverse cohorts and the need for establishing age-dependent norms. We demonstrate how the HPP can be used to unravel personalized molecular signatures of disease by comparison to patient-specific and disease-specific matched healthy controls. Leveraging the extensive dietary and lifestyle HPP data, we systematically identify associations between lifestyle factors and health outcomes. Finally, we present a multi-modal foundation AI model that is trained using self-supervised learning on diet and CGM data and outperforms existing methods in predicting future onset of disease. We extend this AI framework to integrate all data modalities of each subject as a continuous sequence of diverse medical events, creating a digital twin that can simulate interventions and predict health trajectories and outcomes.

  Study EGAS00001008040

• Whole transcriptome profiling of liquid biopsies from tumour xenografted mouse models: validation cohort

  While cell-free DNA (cfDNA) in liquid biopsies is widely being used and investigated, free circulating RNA (extracellular RNA, exRNA) has the potential to improve therapy response monitoring and cancer detection due to its dynamic nature. A fundamental open question hampering the initiation of large-scale liquid biopsy collections for tumour exRNA analysis is that it remains unclear in which blood subcompartment tumour-derived exRNAs primarily reside. We set out to develop a host-xenograft deconvolution framework, exRNAxeno, with cDNA mapping strategies to either a combined human-mouse reference genome or both species genomes in parallel, that can be applied to exRNA sequencing data from liquid biopsies of human xenograft mouse models, enabling to distinguish (human) tumoural RNA from (murine) host RNA, and as such to specifically analyse tumour-derived exRNA. Subsequently, the preferred exRNAxeno combination pipeline was applied to total exRNA sequencing data from blood platelets and three plasma fractions from a breast cancer patient-derived and neuroblastoma cell line-derived xenograft mouse model. We show that tumoural exRNA concentrations are not determined by plasma platelet levels, while host exRNA concentrations increase with platelet content. Furthermore, a large variability in exRNA levels and gene content across individual mice is observed. In general, the tumoural gene detectability in plasma is correlated with the RNA expression levels in the tumour tissue or cancer cell line. Our results unravel new aspects of tumour-derived exRNA biology in xenograft mouse models.

  Study EGAS00001006582

• NIPT samples for systematic evaluation of BinDel, a software tool for detecting clinically significant microdeletions in low-coverage WGS-based NIPT samples

  This dataset contains three sets of samples. The first sample set contains euploid fetus pregnancies reported by NIPTIFY screening test and postnatal evaluation. Dataset was processed similarly to previously published guidelines from KU Leuven, with modifications [1]. Briefly, peripheral blood samples were collected in cell-free DNA BCT tubes (Streck, USA), and plasma was separated with standard dual centrifugation. Cell-free DNA was extracted from 3 ml plasma using MagMAX Cell-Free DNA Isolation Kit (ThermoFisher Scientific). Whole-genome libraries were prepared using the FOCUS (Fragmented DNA Compact Sequencing Assay, Competence Centre on Health Technologies, Estonia) NIPT method protocol with 12 cycles for the final PCR enrichment step. In the following quantification, equal amounts of 36 samples were pooled, and the quality and quantity of the pool were assessed on Agilent 2200 TapeStation (Agilent Technologies, USA). Whole genome sequencing was performed on the NextSeq 550 instrument (Illumina Inc.) with an average coverage of 0.32× (minimum 0.08 and maximum 0.42) and producing 85 bp single-end reads. The second sample set contains a single NIPT sample postnatally diagnosed with Prader-Willi syndrome. The sample was sequenced with Illumina NextSeq 500 platform, producing 85 bp single-end reads with an average per-sample coverage of 0.32× at the University of Tartu, Institute of Genomics Core Facility, according to the manufacturer’s standard protocols, as described previously [2]. The third sample set contains samples SC005 (SeraCare Life Sciences Inc lot #10446565), SC0042 (#10571706), and SC016 (#10560229). These are SeraCare Life Sciences Inc circulating cell-free DNA (ccfDNA) like mixture of human genomic DNA that consists of matched maternal and fetus. SC005 and SC0042 consist of matched DNA of maternal and fetus with DiGeorge Syndrome. SC016 is a custom-ordered DNA Mix with fetus DNA having a pathogenic loss of the terminal region of 20p13 and a pathogenic 3q29 duplication. SC016 was processed as the first sample set was processed, and SC0042 was processed as the second sample set was processed. Sample SC005 was processed once as was sample set 1 and once as was sample set 2 processed. This study was performed with the approval of the Research Ethics Committee of the University of Tartu (#352/M-12). 1. Bayindir B, Dehaspe L, Brison N, Brady P, Ardui S, Kammoun M, et al. Noninvasive prenatal testing using a novel analysis pipeline to screen for all autosomal fetal aneuploidies improves pregnancy management. Eur J Hum Genet. 2015;23: 1286– 1293. doi:10.1038/ejhg.2014.282 2. Žilina O, Rekker K, Kaplinski L, Sauk M, Paluoja P, Teder H, et al. Creating basis for introducing noninvasive prenatal testing in the Estonian public health setting. Prenat Diagn. 2019;39: 1262–1268. doi:10.1002/pd.5578

  Dataset EGAD00001009512

• WGS data of paediatric TCF3::PBX1 acute lymphoblastic leukemia (set2)

  The dataset includes FASTQ and BAM files from diagnostic and matched remission (control) samples of one TCF3::PBX1 ALL patient (ALLT-376). Sequencing library was made using PCR free-based WGS library preparation (PCR-), using NEB Next® Ultra™ DNA Library Prep Kit. Both diagnostic (90x) and remission (30x) samples were sequenced using HiSeq X.

  Dataset EGAD50000001795

• WGS data of paediatric BCR::ABL1 acute lymphoblastic leukemia

  The dataset includes FASTQ and CRAM files from diagnostic and matched remission (control) samples of one BCR::ABL1 ALL patient (ALLT-399). Sequencing library was made using PCR free-based WGS library preparation (PCR-), using Novogene NGS DNA Library Prep Set Kit (Cat No. PT004). Both diagnostic (90x) and remission (30x) samples were sequenced using NovaSeqX Plus.

  Dataset EGAD50000002185

• WGS data of paediatric B-other B cell acute lymphoblastic leukemia (set5)

  The dataset includes FASTQ and BAM/CRAM files from diagnostic and matched remission (control) samples of two B-other ALL patients (ALLT-396, ALLK-131). Sequencing library was made using PCR free-based WGS library preparation (PCR-), using Novogene NGS DNA Library Prep Set. Both diagnostic (90x) and remission (30x) samples were sequenced using NovaSeqX Plus.

  Dataset EGAD50000002160

• The dataset of Detection and characterization of lung cancer using cell-free DNA fragmentomes on NovaSeq 6000 at 1-2x coverage

  The dataset contains 364 CRAM files from whole-genome next-generation sequencing on the Illumina NovaSeq 6000 at 1- 2x coverage. These are plasma samples from healthy individuals and patients with cancer.

  Dataset EGAD50000001961

• Exome sequencing data for the DIRECT study.

  This dataset contains all available fastq files for gemline, baseline plasma/biopsy, and response assessment patient samples for the DIRECT study. The total number of samples was 729 (188 germline, 190 baseline plasma, 159 baseline biopsy, and 192 response assessment). The dataset files were generated from targeted (exome) Illumina sequencing performed on paired biopsy tissue and plasma cell free DNA.

  Dataset EGAD50000001409