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• Enhanced cortical neural stem cell identity through SMAD/WNT inhibition in human cerebral organoids facilitates emergence of outer radial glial cells

  For scRNA-Seq, single live cells were suspended in 0.4% BSA in DPBS buffer (1000 cells/µL) and subjected for GEM generation and barcoding. Library preparation was performed according to the recommended procedures of the manufacture Chromium Single Cell 3’ reagent Kit V3.1 chemistry. 10,000 cells were targeted for capturing and 9 cycles were used for cDNA amplification, while 12 cycles were performed for library formation, and sequencing was performed on an Illumina NovaSeq 6000 sequencer. For bulk RNA-Seq, RNA was purified using the miRNeasy™ RNA MiniPrep (Qiagene) and RNA-seq libraries were generated either using the Illumina TruSeq RNA Library Preparation Kits and sequenced on the Illumina HiSeq 2500 sequencer as 76 bp paired-end reads, or using the NEBnext UltraDirectional RNA Library Preparation Kits after rRNA depletion using the NEBNext rRNA depletion kit and sequenced on an Illumina HiSeq 2500 sequencer using 50 cycles of single-end sequencing.

  Dataset EGAD00001008609

• dbGaP Collection: NHLBI Heart Failure Related dbGaP Data (No IRB requirement)

  The National Heart, Lung, and Blood Institute (NHLBI) Big Data Analysis Challenge: Creating New Paradigms for Heart Failure Research has concluded. The NHLBI will continue to make this collection of data available to the research community.Past information regarding the Data Collection for the NHLBI Big Data Analysis Challenge: Creating New Paradigms for Heart Failure Research is below.The National Heart, Lung, and Blood Institute (NHLBI), part of the National Institutes of Health (NIH), is inviting novel Solutions for the NHLBI Big Data Analysis Challenge: Creating New Paradigms for Heart Failure Research. The goal of the challenge is to foster innovation in computational analysis and machine learning approaches utilizing large-scale NHLBI-funded datasets to identify new paradigms in heart failure research. The challenge aims to address the need for new open source disease models that can define sub-categorizations of adult heart failure to serve as a springboard for new research hypotheses and tool development in areas of heart failure research from basic to clinical settings. NHLBI has a history of making considerable investments in the creation of deep data resources including: long-standing, deeply-phenotyped epidemiological cohorts, innovative clinical trials, and large-scale precision medicine efforts that have generated whole genome sequencing and "other omics" data for more than one-hundred thousand individuals. To provide challenge participants with streamlined access to data across NHLBI's numerous studies containing heart failure data, the NHLBI has created this dbGaP study collection. Data access for this collection is controlled by NHLBI's Data Access Committee. Challenge participants are required to follow the use restrictions and acknowledgement instructions from the original dataset(s). Please note that the data in this collection are not harmonized across studies or otherwise altered from the original study. The NHLBI Big Data Analysis Challenge: Heart Failure Data Collection contains all NHLBI studies currently in dbGaP that contain data that may be relevant to research on heart failure. The studies in this collection are approved for General Research Use (GRU), Health/Medical/Biomedical Use (HMB), or Disease-Specific Use (DS) that permits research on heart failure. These studies span a variety of study designs, inclusion and exclusion criteria, sample sizes, and provide a wide breadth and depth of phenotype data on study participants. The available genomic data in these studies also varies, including genotyping arrays, sequencing (targeted, exome, whole genome), and additional -omic data (e.g., RNA or metabolite profiles). Please refer to each study's individual accession page to learn more about how study data were collected. Challenge participants are reminded that in addition to dbGaP, NHLBI's Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC) contains other studies that have collected data relevant to heart failure and may wish to utilize BioLINCC data in the development of their Solution. Please refer to the individual accession page for each study in this collection to learn more about the history of each study.

  Study phs001991

• Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Coronary Artery Risk Development in Young Adults Study (CARDIA)

  Cohort Description The Coronary Artery Risk Development in Young Adults (CARDIA) study is a study examining the development and determinants of clinical and subclinical cardiovascular disease and their risk factors. It began in 1985-6 with a group of 5115 black and white men and women aged 18-30 years. The participants were selected so that there would be approximately the same number of people in subgroups of race, gender, education (high school or less and more than high school), and age (18-24 and 25-30 years) in each of 4 centers: Birmingham, AL; Chicago, IL; Minneapolis, MN; and Oakland, CA. These same participants were asked to participate in follow-up examinations during 1987-1988 (Year 2), 1990-1991 (Year 5), 1992-1993 (Year 7), 1995-1996 (Year 10), 2000-2001 (Year 15), 2005-2006 (Year 20), 2010-2011 (Year 25), 2015-2016 (Year 30), and 2021-2022 (Year 35). Data Being Submitted Wave 1 questionnaire data includes 397 variables for up to 2434 CARDIA participants in C4RWave 2 questionnaire data includes 448 variables for up to 1901 CARDIA participants in C4RDried Blood Spot/Serosurvey data includes 7 variables for up to 1332 CARDIA participants in C4RDerived data includes 43 variables for up to 2723 CARDIA participants in C4RPhenotype data includes 113 variables for up to 2723 CARDIA participants in C4R

  Study phs003045

• Two lung cancer cell lines with EGFR mutations, PC-9 and KHM-3S, were either treated with Tarceva for 24 hours or left untreated. The gene expression profiles were examined by RNAseq, and the genome wide binding profiles of total STAT3 and pSTAT3 were characterized by ChIPseq.

  Lung cancers harboring activating EGFR mutants show dramatic responses to EGFR TKIs, such as Tarceva. However, nearly all patients show relapse within 1 year after initial treatment. To investigate the early signaling switches that are involved in the formation of drug resistance, and the role of STAT3 in the early signaling switches involved in the formation of drug resistance, we have treated two lung cancer cell lines with EGFR mutations, PC-9 and KMH-3S, with Tarceva for 24hours. The RNA samples with and without treatment were collected in triplicate for RNAseq experiment.The total STAT3 and pSTAT3 chromatinIP were done on samples with and without treatment for ChIPseq.

  Study EGAS00001000793

• A benchmarking resource for NGS testing of cancer predisposition genes

  A benchmarking resource of 639 individuals, to assess the analytical sensitivity of cancer predisposition gene (CPG) testing.The dataset includes sequencing data generated using the TruSight Cancer Panel (TSCP) a targeted NGS assay for analysis of CPGs and orthogonally generated data supporting at least one pathogenic variant in a CPG for a total of 645 pathogenic CPG variants.The set of pathogenic CPG variants includes strong representation of some of the most challenging types of pathogenic variants, with 339 indels, including 16 complex indels and 24 insertions or deletions with length greater than 5bp, and 74 exon CNVs, including 23 single exon CNVs. There are 502 pathogenic variants in BRCA1 or BRCA2, making this an important first-line validation dataset for laboratories performing NGS testing of BRCA1 and BRCA2.

  Study EGAS00001002993

• WTCCC case-control study for Coronary Artery Disease - Combined Controls

  WTCCC genome-wide case-control association study for Coronary Artery Disease (CAD) using six disease collections together with the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000004

• WTCCC case-control study for Type 1 Diabetes - Combined Controls

  WTCCC genome-wide case-control association study for Type 1 Diabetes (T1D) using six disease collections together with the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000015

• WTCCC case-control study for Type 2 Diabetes - Combined Controls

  WTCCC genome-wide case-control association study for Type 2 Diabetes (T2D) using six disease collections together with the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000017

• A new beta-globin mutation responsible of a beta-thalassemia (HbVar database ID 2928) was observed in 8 unrelated French families. The mutation carriers originated from Nord-Pas-de-Calais, a Northern French region where the chief town is Lille.5 unrelated mutation carriers were genotyped for a set of 12 microsatellites from chromosome 11, around the beta-globin gene. Among the 5 mutation carriers, 4 were genotyped for 97 European Ancestry Informative SNPs (EAIMs). 32 controls from Nord-Pas-de-Calais were genotyped for the microsatellites and SNPs.

  Dac EGAC00001000245

• Large Cancer Fingerprint Screening for Detection of Minimal Residual Disease.

  We describe an approach for large cancer fingerprint screening and its application to cell-free DNA from patients with cancer. Our approach involves tracking somatic mutations identified from patients' tumor biopsies, in the cell-free DNA from a blood draw.

  Study phs001977