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  Study EGAS00001008448

• SAFIR02_Agilent

  Genomics to select patients with metastatic breast cancer for targeted therapy (microarray_agilent)

  Dataset EGAD00010002243

• EXCEED Study HRC imputation

  EXCEED samples imputed to HRC reference panel using Michigan Imputation server

  Dataset EGAD00010001685

• OA Functional Genomics

  Functional genomics approaches to understand osteoarthritis

  Dataset EGAD00010001746

• Variant_files_100_ID_trios

  High Quality Variant Call files, generated by bioscope, converted to vcf format. Complete dataset for all 300 samples.

  Dataset EGAD00001000277

• Gene Expression Study of Individuals with Sex Chromosome Aneuploidies

  Males and females show dramatic differences in their vulnerability to the same diseases. For example, compared to men, lupus is six times more prevalent, thyroid cancer is three times more prevalent, and unipolar depression is twice as prevalent in women. Diseases with a strong male bias include autism (5:1), dilated cardiomyopathy (3:1), and ankylosing spondylitis (5:1). Historically, such differences have been attributed solely to extrinsic factors such as circulating sex hormones or environmental influences. We hypothesized that intrinsic factors - genetic differences between XX and XY cells - have unappreciated biological consequences throughout the body and contribute to sex differences in disease incidence and severity. This hypothesis stems from our long-term effort to sequence the sex chromosomes of diverse mammalian species, which has identified a set of homologous genes on the X and Y chromosomes that are dosage-sensitive, expressed throughout the body, and encode regulators of chromatin modification, transcription, translation, and protein stability. These X- and Y-encoded genes differ in sequence and expression pattern, which likely manifests in genome-wide differences in gene regulation between XX and XY cells and influences all aspects of human biology, including sex differences in disease susceptibility. These hard-wired molecular sex differences have been largely overlooked and understudied, representing a significant gap in our knowledge of human biology.The gene expression study of individuals with sex chromosome aneuploidies takes advantage of natural human variation in sex chromosome number, i.e. sex chromosome aneuploidy, to investigate alterations in genome-wide gene expression that correlate with changes in X- and Y-chromosome dosage. We analyzed samples from 114 individuals with a variety of sex chromosome aneuploidies, including 45,X; 47,XXY; 47,XYY; 47,XXX; 48,XXYY; and 49,XXXXY. We generated lymphoblastoid cell lines (LCLs) from blood samples and, in some cases, fibroblast cultures from skin biopsies. We supplemented our collection with previously-derived cell lines. To evaluate gene expression, we performed deep profiling of the transcriptome (RNA-seq) from these LCLs and fibroblasts. We performed parallel analyses on samples collected from 62 control 46,XX and 46,XY individuals, 6 individuals with trisomy 21, and 14 individuals with structural variations of the X and Y chromosomes. In addition, we performed CRISPRi knockdowns on 3 of the 46,XX and 3 of the 46,XY fibroblast samples for the homologous transcription factors ZFX and ZFY, encoded on the X and Y chromosomes, respectively.In the April 2024 update, we added RNA-seq datasets derived from isolated CD4+ T cells and monocytes from 76 and 72 adults, respectively, with the following sex chromosome constitutions: 45,X; 46,XX; 46,XY; 47,XXX; 47,XXY; 47,XYY. These individuals are largely a subset of the same cohort described above. In addition, we performed RNA-seq on in-vitro stimulated CD4+ T cells with the following sex chromosome constitutions: 45,X; 46,XX; 46,XY; 47,XXY.In the August 2024 update, we added RNA-seq datasets generated from the following: 1) LCLs derived from individuals with AZFa deletions of the Y chromosome, 2) DDX3X and DDX3Y knockdown (via CRISPRi) in XY fibroblasts, and 3) 5-ethyl uridine (5-EU) treatment in XY and XYYYY LCLs.

  Study phs002481

• Add Health: Longitudinal Study of a Nationally Representative Sample of Adolescents in Grades 7-12 in the United States during the 1994-95 School Year, Followed into Adulthood with Five Interviews/Surveys in 1995, 1996, 2001-02, 2008, and 2016-18

  The National Longitudinal Study of Adolescent to Adult Health [Add Health] is an ongoing longitudinal study of a nationally representative U.S. cohort of more than 20,000 adolescents in grades 7-12 (aged 12-19 years) in 1994 followed into adulthood with five interviews/surveys in 1995, 1996, 2001-02, 2008, and 2016-18. Add Health was designed to understand how social environments and behaviors in adolescence are linked to health and achievement outcomes in young adulthood. Add Health contains unprecedented environmental, behavioral, psychosocial, biological, and genetic data from early adolescence and into adulthood on a large, nationally representative cohort with unprecedented racial, ethnic, socioeconomic, and geographic diversity. Add Health has a large, multidisciplinary user base of over 50,000 researchers around the world who have published over 3,400 research articles. Add Health is housed at the Carolina Population Center of the University of North Carolina at Chapel Hill. Add Health datasets are distributed according to a tiered data disclosure plan designed to protect the data from the risk of direct and indirect disclosure of respondent identity. Add Health's large sample size, population diversity and rich longitudinal database of psychosocial, physical, and contextual data will permit investigation of an exceptionally broad range of phenotypes with known genetic variation. Prospective longitudinal measures are available to document change over time in each of these phenotypes, as well as change in the social environment and life experiences, making the Add Health sample ideal for understanding genetic linkages with health and behavior across the life course. The original design of Add Health included important features for understanding biological processes in health and developmental trajectories across the life course of young people, including an embedded genetic sample with more than 3,000 pairs of adolescents with varying biological resemblance (e.g., twins, full sibs, half sibs, and adolescents who grew up in the same household but have no biological relationship), testing of saliva and urine for sexually transmitted infections and HIV, and biomarkers of cardiovascular health, metabolic processes, immune function, renal function, and inflammation. Add Health therefore has critical objective indicators of health status and disease markers in young adulthood, well before chronic illness or its complications emerge in later adulthood. Because DNA has been collected on the full sample at Wave IV, it is possible to link genetic profiles with social, behavioral, and biological measures over time from adolescence into adulthood. Add Health sampled the multiple environments in which young people live their lives, including the family, peers, school, neighborhood, community, and relationship dyads, and provides independent and direct measurement of these environments over time. Add Health contains extensive longitudinal information on health-related behavior, including life histories of physical activity, involvement in risk behavior, substance use, sexual behavior, civic engagement, education, and multiple indicators of health status based on self-report (e.g., general health, chronic illness), direct measurement (e.g., overweight status and obesity), and biomarkers. No other data resource with this expanse of genotype and phenotype data on a large nationally representative longitudinal sample with race, ethnic, socioeconomic, and geographic diversity exists. A complete reference guide on study design and accomplishments can be found on the Add Health website: https://cdr.lib.unc.edu/concern/articles/6t053j27s.

  Study phs001367

• Asthma in the Lives of Families Today (ALOFT)

  Social interactions and the overall psychosocial environment have a demonstrated impact on health, particularly for people living in disadvantaged urban areas. Here we investigated the effect of psychosocial experiences on gene expression in peripheral blood immune cells of 251 children with asthma in Metro Detroit. Participants were included from an ongoing longitudinal study Asthma in the Lives of Families Today (ALOFT; recruited from November 2010-July 2018. The ALOFT project was established to identify the behavioral and biological pathways through which family social environments impact youth with asthma.In version 1 we used RNA-sequencing and a new machine learning approach to identify transcriptional signatures of 19 variables including psychosocial factors, blood cell composition and asthma symptoms. Using longitudinal data collected from a subset of the participants we showed that transcriptional signatures track the longitudinal changes in measured phenotypes. Importantly, we found 169 genes associated with asthma that are regulated by psychosocial factors, and 344 significant gene-environment interactions for gene expression levels. These results demonstrate that immune gene expression mediates the link between negative psychosocial experiences and asthma risk.In version 2, we focused on pubertal development. We identified substantial gene expression changes associated with age and pubertal development. We showed that genetic effects on gene expression change dynamically during pubertal development. Gene expression changes during puberty are correlated with gene expression changes associated with asthma and may explain sex differences in prevalence. Our results show that molecular data used to study the genetics of early onset diseases should consider pubertal development as an important factor that modifies the transcriptome.Version 3 uses single cell RNA-seq to study the dynamics of the transcriptional response to glucocorticoids in activated Peripheral Blood Mononuclear Cells from 96 African American children. We employed novel statistical approaches to calculate a mean-independent measure of gene expression variability and a measure of transcriptional response pseudotime. Using these approaches, we demonstrated that glucocorticoids reverse the effects of immune stimulation on both gene expression mean and variability. Our novel measure of gene expression response dynamics, based on the diagonal linear discriminant analysis, separated individual cells by response status on the basis of their transcriptional profiles and allowed us to identify different dynamic patterns of gene expression along the response pseudotime. We identified genetic variants regulating gene expression mean and variability, including treatment-specific effects, and demonstrated widespread genetic regulation of the transcriptional dynamics of the gene expression response.Version 4 adds scATAC-seq in activated peripheral blood mononuclear cells (PBMC) from 16 children with asthma with phytohemagglutinin (PHA) or lipopolysaccharide (LPS), and treated with dexamethasone (DEX), an anti-inflammatory glucocorticoid. We analyzed changes in chromatin accessibility, measured transcription factor motif activity, and identified treatment and cell-type specific transcription factors that drive changes in both gene expression mean and variability. We observed strong positive linear dependence between motif response and their target gene expression changes, but negative in variability changes. This result suggests that an increase of transcription factor binding tightens the variability of gene expression around the mean. We then annotated genetic variants in chromatin accessibility peaks and response motifs followed by computational fine-mapping of eQTL signals from a pediatric asthma cohort. We found that eQTLs were 5-fold enriched in peaks with response motifs and refined the credible set for 410 asthma risk genes, with 191 having the causal variant in response motifs. These results enhance the understanding of molecular mechanisms for asthma risk variants mediated by gene expression.

  Study phs002182

• Exome sequencing reveals pathogenic variants in known and novel candidate genes for severe sperm motility disorders

  STUDY QUESTION: What are the causative genetic variants in patients with male infertility due to severe sperm motility disorders? SUMMARY ANSWER: We identified high confidence disease-causing variants in multiple genes previously associated with severe sperm motility disorders in 9 out of 21 patients (43%). We also identified variants in novel candidate genes in 8 additional patients (38%). WHAT IS KNOWN ALREADY: Severe sperm motility disorders are a form of male infertility characterised by vital, but immotile sperm often in combination with a spectrum of structural abnormalities of the sperm flagellum. Examples of this spectrum of disorders include dysplasia of the fibrous sheath / multiple morphological abnormalities of the sperm flagella (DFS-MMAF) and severe forms of asthenozoospermia associated to non-specific structural defects. These disorders frequently recur in families and may include chronic respiratory disease. As such, genetic causes are suspected and many genes have recently been reported. Currently, depending on the clinical sub-categorisation, up to 50% of causality in patients with severe sperm motility disorders can be explained by pathogenic variants in at least 21 known genes. STUDY DESIGN, SIZE, DURATION: We performed exome sequencing in patients with severe sperm motility disorders from two different clinics, aiming to identify the underlying genetic defects and establishing a diagnostic yield in both. PARTICIPANTS/MATERIALS, SETTING, METHOD: Two groups of infertile men, one from Argentina (n= 9) and one from Australia (n=12), with clinically defined sperm motility disorders were included. All patients in the Argentine cohort were diagnosed with DFS-MMAF, based on transmission electron microscopy. Exome sequencing was performed in all 21 patients and variants with an allele frequency of <1% in the gnomAD population were prioritised and interpreted. MAIN RESULTS AND ROLE OF CHANCE: In 9/21 patients (43%), we identified pathogenic variants in known sperm motility disorder genes: CFAP43 (3 patients); CFAP44 (2 patients), QRICH2 (2 patients), DNAH1 (1 patient) and DNAH6 (1 patient). The diagnostic rate did not differ markedly between the Argentinian and the Australian cohort (44% and 42%, respectively). Furthermore, we identified patients with variants in the novel candidate sperm motility genes CFAP58, DNAH12, DRC1, MDC1, PACRG, SSPL2C and TPTE2. One patient presented with two possibly damaging variants in four candidate genes and it remains unclear which variants were responsible for the severe sperm motility defect in this patient. LIMITATIONS, REASONS FOR CAUTION: In this study, we described patients with potential bi-allelic variants in known and novel candidate genes for severe sperm motility disorders. Due to unavailability of parental DNA, we have not assessed de novo or maternally inherited dominant variants and could not phase the mutations to establish in all cases that the mutations occur on both alleles. WIDER IMPLICATIONS OF THE FINDINGS: Our results confirm an important role for five known genes for sperm motility and we demonstrate that exome sequencing is an effective method to diagnose patients with severe sperm motility defects (9/21 diagnosed; 43%). Furthermore, our analysis revealed seven novel candidate genes for severe sperm motility disorders. Genome-wide sequencing of additional patient cohorts and re-analysis of exome data of currently unsolved cases may reveal additional variants in these novel candidate genes.

  Study EGAS00001005018

• Novel Approach to High-Throughput Identification and Characterization of Neoantigens

  This study focuses on the development of novel approach for the screening, identification and characterization of neoantigen-specific T-cell receptors (TCRs). The developed method consists of collecting targeted RNA-Seq from a T-cell specific gene panel via 3' end Illumina sequencing combined to Oxford Nanopore based full-length TCR sequencing post T-cell activation. The data generated during this study demonstrates feasibility of the approach on a Jurkat control cell line as well as T-cells isolated from the blood of 3 independent healthy donors.

  Study phs002372

• Evaluation of Local Response of Prostate Cancer to Irradiation Using Multiparametric MRI and MR-Guided Biopsies

  The purpose of this study was to determine the rate of local recurrence in patients with intermediate and high risk prostate cancer treated with radiotherapy. In this study, multiparametric MRI was first performed, and biopsy tissue was acquired from cancerous regions detected on MRI. Blood samples were also taken. DNA and RNA were extracted from tissue taken at baseline. DNA was used for whole exome sequencing (WES). RNA was used for gene expression microarray. Each patient then received radiation therapy with androgen deprivation therapy.

  Study phs001821

• Whole-genome methylation profiling of menstrual stem cells identifies novel biomarkers for endometriosis

  Endometriosis, despite its high prevalence, is underdiagnosed and poorly managed due to lack of clinically validated biomarkers and pathophysiological insight. Menstrual bloodderived stem cells (MenSCs) have been implicated in disease pathogenesis, but their diagnostic potential remains unexplored. We conducted a clinical study (n=42; 19 endometriosis, 23 controls) to assess whether DNA methylation profiles of freshly isolated MenSCs can identify disease-specific biomarkers. Whole-genome methylation sequencing revealed differentially methylated regions (DMRs) enriched in genes linked to hallmarks of endometriosis (e.g., inflammation, tissue remodelling, development). These DMRs robustly distinguished cases from controls, independent of technical and clinical variables. Machine learning models trained and validated on these DMRs achieved high diagnostic performance (specificity 83%, sensitivity 79%). Integration with an independent single-cell RNA sequencing dataset showed that the DMRs may modulate gene expression, further supporting their biological relevance. These findings position MenSC DNA methylation profiling as a promising, non-invasive approach for early endometriosis diagnosis and personalised care.

  Dataset EGAD50000002353

• Bone morphogenetic protein-9 controls pulmonary vascular growth and remodeling

  Pulmonary arterial hypertension (PAH) and hereditary hemorrhagic telangiectasia (HHT) are two distinct vascular diseases linked to impaired signaling through bone morphogenetic protein (BMP) receptor complexes in endothelial cells. Although BMP-9 plays a central role in activating this pathway by binding to ALK1 and BMPR-­II, its precise function in the pulmonary microvasculature has remained unclear. In this study, we uncover a previously unrecognized role for BMP-9 in regulating pulmonary vascular architecture and homeostasis. Our findings demonstrate that BMP-9 signaling intersects with VEGF pathways and contributes to the delicate balance between vascular growth and remodeling in the lungs. We also show that disruption of this pathway can shift vascular responses toward an HHT-­like state, potentially altering disease susceptibility. These insights offer a unique perspective on how BMP-9 and ALK1 shape pulmonary vascular biology and suggest that targeting this axis could inform future strategies for treating complex vascular diseases such as PAH.

  Dataset EGAD50000001496

• Estonian Microbiome Project second time point dataset

  Out of the 2,509 Estonian Microbiome Project participants, a sub-cohort of over 300 individuals provided an additional stool sample after a median follow-up period of 4.4 years. All participants of the EstMB cohort gave informed consent for the data and samples to be used for scientific purposes. In the second time point, the participants were instructed to send the samples by post immediately after taking the sample and time their sample collection to avoid shipping on the weekends. The median time between sampling and arrival at the freezer in the core facility for the second time point was 53 hours and 1 minute (mean: 59 hours and 22 minutes; minimum: 34 minutes; maximum: 168 hours and 7 minutes [note: additionally, one outlying measurement was 508 hours and 27 minutes. The shotgun metagenomics paired-end sequencing was performed by Novogene Bioinformatics Technology Co., Ltd., using Illumina NovaSeq6000 platform, resulting in 4.62 ± 0.44 Gb of data per sample (insert size 350 bp, read length 2 × 250 bp).

  Dataset EGAD50000001686

• Long read mRNA sequencing of human neural retinal samples - Usher syndrome transcript landscape

  Long-read (PacBio) RNA sequencing dataset of three neural retinal samples. Three PacBio libraries were prepared according the 'standard workflow' optimized for sequencing transcripts centered around 2kb. Additionally one Library (input HNR_S2) was prepared according an optimized 'long workflow' to enrich for larger transcripts up to >10kb. To further enhance the capture of full-length transcripts for USH2A and ADGRV1 (USH2C) genes, we also employed a targeted enrichment approach using the Samplix Xdrop System, followed by PacBio long-read sequencing. USH2A and ADGRV1 enrichment was performed by targeting '5- mid and 3' targets of the respective genes. Finally, we also added ONT (Oxford Nanopore technology) long-read mRNA sequencing of three independent neural retina samples. These data were used for the validation of events observed from the Iso-Seq and Samplix data. The ONT datasets contain sequencing data of the Usher-associated genes. Files are raw BAM, and CRAM format files generated by a Sequel II machine. Additionally, the ccs3 BAM format files are included.

  Dataset EGAD50000000720

• Shallow Whole Genome Sequencing of Patient Derived Xenografts

  Chemotherapy is the standard-of-care treatment for metastatic colorectal cancer (mCRC) and benefits some patients, but what distinguishes responders from non-responders is unclear. In this study, we leveraged a comprehensive collection of 27 molecularly annotated patient-derived xenografts to uncover functional predictors of response to 5-FU and irinotecan combination therapy (FOLFIRI) in mCRC. Genetic analyses revealed that treatment sensitivity was marked by genomic scars indicative of BRCAness, suggesting homologous recombination (HR) deficiency as a key determinant. Accordingly, we surveyed a manually curated panel of 44 genes with a documented role in HR for the potential presence of pathogenic mutations. We did not observe a specific enrichment of HR gene mutations based on response to FOLFIRI. This result, combined with the absence of widespread biallelic inactivation of the analyzed genes and the predominance of mutations categorized as variants of unknown significance, suggests that FOLFIRI sensitivity is not primarily governed by underlying mutations in HR genes responsible for mitigating the genotoxic effects of this therapeutic regimen.

  Dataset EGAD50000000277

• Lung Plasma rearrangement screen

  Genomic libraries (500 bps) will be generated from total genomic DNA derived from lung cancer patients and subjected to short paired end sequencing on the llumina platform. Paired reads will be mapped to build 37 of the human reference genome to facilitate the generation of genome wide copy number information, and the identification of novel rearranged cancer genes and gene fusions.

  Dataset EGAD00001000367

• Myelodysplastic Syndrome Follow Up Series

  Agilent whole exome hybridisation capture was performed on genomic DNA derived from MDS and matched normal DNA from the same patients. Next Generation sequencing performed on the resulting exome libraries and mapped to build 37 of the human reference genome to facilitate the identification of novel cancer genes. Now we aim to discover the prevalence of our findings using bespoke pulldown methods and sequencing the products from a larger set of patient DNA.

  Dataset EGAD00001000283

• MutWP5: CRUK Mutographs of Cancer: Breast: BRCA Carriers (Targeted) (2020-01-29)

  Sequencing of LCM-derived microbiopsies from 20 women who underwent risk-reducing reduction mastectomies due to germline BRCA1/2. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Targeted data will be used as a driver and clonality screen, highly clonal or driver-containing samples will subsequently be sent for whole-genome sequencing. Results from this portion of the study will be compared to women who had cosmetic breast reduction surgeries and those with cancer. . This dataset contains all the data available for this study on 2020-01-29.

  Dataset EGAD00001005920

• MutWP5: CRUK Mutographs of Cancer: Breast: BRCA Carriers (Exome) (2020-01-29)

  Sequencing of LCM-derived microbiopsies from 20 women who underwent risk-reducing reduction mastectomies due to germline BRCA1/2. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Exome data will be used as a driver and clonality screen, highly clonal or driver-containing samples will subsequently be sent for whole-genome sequencing. Results from this portion of the study will be compared to women who had cosmetic breast reduction surgeries and those with cancer. . This dataset contains all the data available for this study on 2020-01-29.

  Dataset EGAD00001005921

• MutWP5: CRUK Mutographs of Cancer: Breast: Cancer Mastectomy (Targeted) (2020-01-29)

  Sequencing of LCM-derived microbiopsies from 30 women who mastectomies due to Breast Cancer. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Targeted data will be used as a driver and clonality screen, highly clonal or driver-containing samples will subsequently be sent for whole-genome sequencing. Results from this portion of the study will be compared to women who had cosmetic breast reduction surgeries and those with germline BRCA 1/2 mutations. . This dataset contains all the data available for this study on 2020-01-29.

  Dataset EGAD00001005923

• MutWP5: CRUK Mutographs of Cancer: Breast: Cancer Mastectomy (Exome) (2020-01-29)

  Sequencing of LCM-derived microbiopsies from 30 women who underwent mastectomies due to a breast cancer diagnosis. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Exome data will be used as a driver and clonality screen, highly clonal or driver-containing samples will subsequently be sent for whole-genome sequencing. Results from this portion of the study will be compared to women who had cosmetic breast reduction surgeries and those with germline BRCA 1/2 mutations. . This dataset contains all the data available for this study on 2020-01-29.

  Dataset EGAD00001005924

• MGMT genomic rearrangements contribute to chemotherapy resistance in gliomas

  Temozolomide (TMZ) is an oral alkylating agent used for the treatment of glioblastoma and is now becoming a chemotherapeutic option in patients diagnosed with high-risk low-grade gliomas. The O-6-methylguanine-DNA methyltransferase (MGMT) is responsible for the direct repair of the main TMZ-induced toxic DNA adduct, the O6-Methylguanine lesion. MGMT promoter hypermethylation is currently the only known biomarker for TMZ response in glioblastoma patients. Here we show that a subset of recurrent gliomas carry MGMT genomic rearrangements that lead to MGMT overexpression, independently from changes in its promoter methylation. By leveraging the CRISPR/Cas9 technology we generated some of these MGMT rearrangements in glioma cells and demonstrated that they lead to TMZ resistance both in vitro and in vivo. Lastly we showed that such fusions can be detected in tumor-derived exosomes and could potentially represent an early detection marker of tumor recurrence in a subset of patients treated with TMZ.

  Dataset EGAD00001006281

• Human liver mtDNA sequencing

  BAM files containing paired-end mtDNA sequencing data from morphologically normal human liver. Clonal CCO-deficient patches of hepatocytes were identified in human liver samples, and samples were taken along a line spanning approximately from the portal triad to the central hepatic vein. Individual BAM files are named according to their patch, line and cut, where cut 1 is nearest to the portal triad, and cuts 2, 3 etc. lying further from the portal triad. Other file types include "Bulk" samples, contain sequencing data of the remaining CCO-deficient cells that were not sampled as part of the line of cuts, and "Stroma" control samples (used for identifying germ-line variants). Sequenced on NextSeq 500 platform.

  Dataset EGAD00001007991

• MutWP5: CRUK Mutographs of Cancer: Lung: PD37920 (Targeted) (2021-02-02)

  Sequencing of LCM-derived microbiopsies from explanted lung from COPD patient. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Deep sampling throughout multiple regions of the lung will determine whether there are differences in smoking-related mutation burden in different portions of the lung. Targeted sequencing will be conducted on samples to identify drivers of interest and clonality of the samples, well-performing samples will be sent for subsequent whole-genome sequencing. Results from this portion of the study will be compared to other individuals with smoking-related diseases (COPD, pulmonary fibrosis, lung cancer), and normal, non-smoking lungs. . This dataset contains all the data available for this study on 2021-02-02.

  Dataset EGAD00001006929