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• DAC for BillionToOne

  This is the Data Access Committee for studies published by BillionToOne.

  Dac EGAC50000000418

• APL nanopore sequencing

  Nanopore sequencing for an APL patient

  Study EGAS00001005618

• Genome-Wide Association of Type 2 Diabetes in Africans: The AADM Study

  The Africa America Diabetes Mellitus (AADM) study is a genetic epidemiological study of type 2 diabetes in Sub-Saharan Africa. Study participants were enrolled through university medical centers in Nigeria, Ghana, and Kenya. Ethical approval for the study was obtained from the Institutional Review Board (IRB) of each participating institution. All subjects provided written informed consent for the collection of samples and subsequent analysis. The case definition of type 2 diabetes was based on the American Diabetes Association (ADA) criteria. After providing informed consent, participants underwent the same enrollment procedures, which included collection of demographic information, medical history, clinical examination and a blood draw. Genome-wide SNP genotyping was done on either the Axiom™ PanAFR SNP array (n=1,808) or the Multi-Ethnic Global Array (MEGA) (n=3,423). After appropriate quality control, in silico imputation was done using the African Genome Resources Haplotype Reference Panel (at the Sanger Imputation Service). Imputed genotypes were filtered for variants with minor allele frequency (MAF)≥ 0.01 and information score (info) ≥ 0.3 for genetic association analysis. Genome-wide association analysis between type 2 diabetes and the imputed genotype dosages was done using a generalized linear mixed model, which adjusted for age, gender, body mass index, the genetic relatedness matrix and the first three principal components (PCs) of the genotypes.Metabolomics profiling of plasma samples of type 2 diabetes (T2D) cases and controls in Nigerians (West Africa) was done in the AADM Study. Plasma metabolites were measured in a total of 580 individuals (N=310 for the discovery phase and N=270 for the replication stage) using the global/untargeted approach on the Metabolon platform and following the manufacturer's standard operation protocols. The analytic methods are described in detail in Doumatey et al. [Genome Med 2024]. The measured metabolites level represented by peak areas are relative values. The peak area data were batch-normalized to remove the instrument batch effects (batch variability) and the batch-normalized data correspond to the median-scaled raw data. For each identified metabolite, the minimum value across all batches in the batch-normalized was imputed for the missing values. The batch-normalized and imputed data are natural log-transformed and consist of 1116 metabolites for the discovery cohort and 1071 metabolites for the replication. Welch's two-sample t-test on the log-transformed data was used to identify metabolites differentially expressed between T2D cases and controls . All other statistical analyses conducted on both the replication and discovery cohorts used the log-transformed data. To merge the discovery and replication, the same quality control samples (bridge samples) were run with each batch of the experimental samples in both cohorts and used to correct for additional variability and uniformize the procedures. The resulting merged data is the QC-normalized and imputed data that contains only metabolites that were common to both cohorts and successfully bridged for all batches (n= 891 metabolites).

  Study phs001844

• ACTIV-6: COVID-19 Outpatient Randomized Trial to Evaluate Efficacy of Repurposed Medications

  This study is a platform protocol designed to be flexible so that it is suitable for a wide range of settings within healthcare systems and in community settings where it can be integrated into routine COVID-19 testing programs and subsequent treatment plans. This platform protocol will enroll participants in an outpatient setting with a confirmed polymerase chain reaction (PCR) or antigen test for SARS-CoV-2. Each appendix will describe a repurposed medication (study drug) to meet the protocol objectives. When only one study drug/appendix is under study, allocation between study drug and placebo will be 1:1. If multiple study drugs/appendices are under study, participants will also be randomized among the study drugs for which eligibility is confirmed. Since the route of administration of each study drug may differ, the placebos may also differ. To achieve blinding and an equitable randomization probability, a two-step randomization process will be used.In the first step, the participant will be randomized m:1 active study drug to placebo, where m is the number of active study drugs for which the participant is eligible. Then, participants will be randomized among the m study drugs for which they are eligible. Participants will carry their ‘study drug' versus ‘placebo' randomization with them into the study drug appendix. In this way, a participant allocated to placebo who is randomized to study drug A will be given the placebo that matches study drug A. This achieves equal probability of exposure to a placebo or an active study drug, and equitable distribution among all study arms for which a participant is eligible. Sites will be informed to which study drug appendix the participant is randomized, but not whether they are allocated to the study drug arm or placebo arm within that appendix. For analysis, concurrent placebo participants who were eligible for the study drug appendix will be pooled. This will result in approximately a 1:1 allocation ratio for any study drug to placebo. If a study drug appendix is stopped for efficacy and becomes standard of care, the active study drug arm may serve as a concurrent placebo for other study drugs.Participants will receive complete supply of repurposed medication (study drug) or placebo with length of treatment and amount of study drug/placebo depending on the study drug appendix and arm to which they are randomized.This study is designed so that it can be done completely remotely. However, screening and enrollment may occur in person at sites and unplanned study visits may occur in person or remotely, as deemed appropriate by an investigator for safety purposes. Participants will be on-study for up to 180 days, during which they will complete various questionnaires.

  Study phs003941

• Phenotype Risk Scores Identify Patients with Unrecognized Mendelian Disease Patterns

  This study was designed to assess the phenotypic effects of rare variants. Rare variants are difficult to study in a high-throughput manner because most cohorts are underpowered to detect associations. In order to gain power to test rare variants, we use Phenotype Risk Scores (PheRS) based on features of Mendelian diseases. PheRS is calculated using claims data from an EHR that is mapped to clinical features from OMIM's clinical descriptions of Mendelian disease. We calculated PheRS for 1,204 Mendelians diseases in a cohort of 21,701 individuals genotyped on the HumanExome BeadChip. We then tested for association between these diseases and rare variants in causal genes. A phenotype risk score is calculated as the weighted sum of features for a given disease. The features are defined as a set of phecodes (consolidated ICD codes) associated with a particular Mendelian disease as described in OMIM. The weights for each phecode are calculated as the log inverse prevalence of the phecode in our cohort. For an individual, their score equals the sum of the weights for each phecode that is present in their medical record. Our study was based on a cohort of individuals with genotype data linked to de-identified electronic health records (EHR) from Vanderbilt's BioVU resource. We hope that this method will help generate phenotype-genotype correlation data on rare variants which in turn may inform rare variant interpretations use for diagnostics.

  Study phs001516

• Alpha1-Antitrypsin Deficiency Registry (AADR-BioLINCC)

  Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives: To characterize the clinical and laboratory course of patients with severe alpha 1-antitrypsin deficiency whether or not the patient is undergoing long-term augmentation therapy.Background: A hereditary disorder, patients with low serum levels of alpha-1-antitrypsin are at an increased risk for the early onset of emphysema. The only approved treatment for alpha-1-antitrypsin deficiency is augmentation therapy using a purified preparation of human alpha-1-antitryspin. Sample sizes for a randomized controlled clinical trial of augmentation therapy were determined to be infeasible; therefore, a multi-center registry was initiated in 1988 to explore the natural history of the disease and the relative efficacy of augmentation therapy in patients with a severe deficiency of alpha-1-antitrypsin.Participants: Eligible participants included individuals 18 years of age or greater for whom the Central Laboratory confirmed that the serum alpha 1-antitrypsin level is Conclusions: Participants receiving augmentation therapy had decreased mortality risk during follow-up. FEV1 decline among all participants did not differ by augmentation therapy; however, among participants with FEV1 35-49% predicted, FEV1 decline was significantly slower for participants on augmentation therapy than for those not receiving therapy. (Am J Respir Crit Care Med, 1998; 158:49-59)

  Study phs004187

• Transdisciplinary Studies of Genetic Variation in Colorectal Cancer(CORECT): Axiom GWAS

  This study is part 1 of 2 for Schumacher et al, Nat Commun. 2015 Jul 7;6:7138. Part 1 is the original GWAS data for 9,259 participants on the Affymetrix Axiom platform of the studies listed below in the Inclusion Criteria.

  Study phs001856

• A Genomic Approach to Improved Diagnosis and Treatment of Neuroendocrine Tumors

  These are RNA-Seq samples from patients undergoing surgery for small bowel and pancreatic neuroendocrine tumors. Normal tissue, primary tumors, lymph nodes, and liver metastases were collected at surgery and stored in RNAlater until RNA extraction was carried out for RNA-Seq.

  Study phs001772

• Comprehensive analysis of the abnormality of the genes in juvenile myelomonocytic leukemia

  To develop a simple and robust methylation test for risk stratification of patients with juvenile myelomonocytic leukemia. We used the DREAM method, a method for whole genome methylation analysis using NGS, to analyze methylation profiling of patients with juvenile myelomonocytic leukemia.

  Study JGAS000292

• ATAC-seq data in normal colon mucosa

  This dataset includes ATAC-seq data generated in normal colon mucosa obtained in four healthy volunteers during colonoscopy indicated for colorectal cancer screening. Subjects had no lesions in the colon. Also includes one frozen sw480 colon adenocarcinoma cell line sample for piloting the protocol

  Study EGAS00001005281

• RNA004 Nanopore DRS of peripheral blood

  Direct RNA Sequencing offers the capability of standard transcriptomic analyses + RNA modification analysis, which holds promising applications for future clinical workflows. To this end, we tested the newly available RNA004 kit on human peripheral blood and provide orthogonal GLORI measurement for benchmarking of m6A-detection.

  Study EGAS50000001201

• Single cell RNA sequencing of co-culture of human organoids with polarized pro-inflammatory (M1) or anti-inflammatory (M2) macrophages

  Human intestinal organoids co-cultured with pro-inflammatory (M1) or anti-inflammatory (M2) human macrophages for 48 hours. 3 days after the co-culture alive cells were sorted and processed for single cell RNA sequencing

  Study EGAS50000000467

• Single-nucleus transcriptome sequencing of the ALS-FTD motor cortex after sorting by TDP-43

  Single-nucleus RNA-sequencing of NeuN+ nuclei of the post-mortem human primary motor cortex from patients with ALS-FTD confirmed for TDP-43 pathology, after sorting for TDP-43 signal, TDP-43 Low vs. TDP-43 High

  Study EGAS50000001566

• Integrative and comparative genomic analyses identify clinically relevant groups of pulmonary carcinoids and unveil the supra-carcinoids

  Multi-omic data for lung neuroendocrine neoplasms, including the first multi-omic sequencing data for the understudied lung atypical carcinoids. The data includes Whole-exomes, whole-genomes, RNA-seq, and EPIC 850K methylation array data.

  Study EGAS00001003699

• Genome-wide association data on male-pattern baldness

  The study comprises 1000Genomes imputed data for 581 MPB cases and 416 male controls. Cases are selected for age<40 and Hamilton-Norwood grade V-VII. Control include 270 males >60 years no signs of AGA (Hamilton-Norwood grade I).

  Study EGAS00001001354

• Synthetic genotypes and phenotypes of 500.000 individuals

  The goal of our study is to establish a pipeline for creating synthetic genotype and phenotype data on a Biobank scale. Such data can be used for developing new methodologies of analysis of common and rare diseases without risking de-identifying the underlying samples.

  Study EGAS00001006552

• June 2017 data update (bam/fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  June 2017 data update (bam/fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001003414

• SCLC study MGH - WES dataset

  For whole-exome sequencing 1 µg of DNA from fresh-frozen tumors was fragmented by sonication technology (for DNA from fresh-frozen tumors: Bioruptor, diagenode, Liѐge, Belgium; for DNA from FFPE material: Covaris). The fragments were end-repaired and adaptor-ligated, including incorporation of sample index barcodes. After size selection, libraries were subjected to an enrichment process with Sure select XT (Agilent). The final libraries were sequenced with a paired-end 2×75 bp protocol for an average coverage of 100-120x

  Dataset EGAD00001003970

• June 2018 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  June 2018 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001004300

• Fastq files used for searching for variants associated with endometriosis at 9p21 region

  We performed target re-sequencing for 1.29 Mb interval of chromosome 9 (chr9:21299764–22590271, hg19). NimbleGen SeqCap EZ choice system was used as a target enrichment method (Roche Diagnostics). A DNA probe set complementary to the target region was designed by NimbleDesign. The libraries were sequenced on the Illumina MiSeq platform with 2×150-bp paired-end module (Illumina). Fastq files for 48 Japanese patients with endometriosis are deposited.

  Dataset EGAD00001001942

• September 2016 data update (bam/fastq/vcf) for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  September 2016 data update (bam/fastq/vcf) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001002724

• May 2019 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  May 2019 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001005060

• August 2019 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  August 2019 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001005335

• August 2020 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  August 2020 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001006383

• KiCS cancer panel data for academic and for-profit use

  This data set contains KiCS cancer panel data for academic and for-profit use.

  Dataset EGAD00001009734