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• Whole transcriptome sequencing of chemotherapy-resistant muscle-invasive urothelial bladder cancer

  All mRNA sequencing data were acquired from single patients (BC159T) at a different time (BC159-T#1, BC159-T#2, and BC159-T#3). The first transurethral resection of bladder tumor (TUR-BT) (BC159-T#1) was diagnosed with non-MIUBC (muscle-invasive urothelial bladder cancer). Despite of intravesical bacillus Calmette-Guerin (BCG), the patient progressed into MIUBC at the second TUR-BT (BC159-T#2). After undergoing multiple neoadjuvant chemotherapy regimens (gemcitabine/paclitaxel and sequential paclitaxel), the patient developed local recurrence and multiple lung metastases and removed following palliative partial cystectomy (BC159-T#3).

  Study EGAS00001004232

• Whole-genome and transcriptome sequencing of a patient with extrapancreatic acinar cell carcinoma

  Dataset EGAD00001006023

• Rucaparib in patients presenting a metastatic breast cancer with Homologous Recombination Deficiency, without germline BRCA1/2 mutation, pronostic value of high LOH genomic score and predictive value of HRDetect (WGS)

  Study EGAS00001004756

• McGill EMC Community projects Release 7 for cell line "SaOS-2"

  Complete reference epigenome (as defined by IHEC) of a SaOS-2 cell line with osteosarcoma.

  Dataset EGAD00001007678

• Mixture of 2 (closer mtDNA)

  Mixture of 2 unrelated individuals (of close mtDNA haplogroup) sequenced by 10x as a scRNA-seq. The dataset was then processed by Cell Ranger and deconvoluted to yield each individuals genetic profile. The clustering of SNPs is submitted as the processed file. The Sequencing fastqs are submitted as unprocessed files.

  Dataset EGAD00001008727

• Dual spatially resolved transcriptomics for human host-pathogen colocalization studies in FFPE tissue sections

  Advamced Visium Spatial Gene Expression assay for FFPE tissues with human and SARS-CoV-2 whole transcriptome (WT) information at a 55 µm resolution. The dataset consists of 13 tissue sections from 5 patient lung tissue samples, 3 from COVID-19 patients and 2 from control patients.

  Dataset EGAD00001008701

• Rapid Acceleration of Diagnostics - Digital Health Technologies (RADx-DHT): Covidseeker and COVID-19 Citizen Science: Leveraging Citizen Science and Real-Time Geospatial Temporal Mobile Data for Digital Contact Tracing and SARS-CoV-2 Hotspotting

  The Covidseeker and COVID-19 Citizen Science Study integrates a retrospectively-determined geolocation digital program into an established digital infrastructure housed within the NIH-funded Eureka platform to enroll SARS-CoV-2 positive and negative individuals. The solution also leverages the ongoing COVID-19 Citizen Science Study cohort both in-person and remotely to test and implement existing technology to enhance readily accessible contact tracing methods and identify “hot spots” of transmission of SARS-CoV-2. The tools are designed to alert users regarding overlap with SARS-CoV-2 infected individuals, identifying businesses that were visited by someone who later tested positive for COVID-19, and working with those businesses and public health departments on strategies to reduce the spread of the virus. DOI: https://rapids.ll.mit.edu/10.57895/me7r-vp06

  Study phs002519

• NIH Division of Intramural Research Multiomic Monogenic Disease Study

  This cross-sectional, observational study utilized high-dimensional approaches, including transcriptomic analysis, serum protein profiling, and peripheral blood frequency assessments, to compare 228 adult and pediatric patients diagnosed with 22 monogenic immune-mediated conditions impacting various key immunological pathways, with 42 age- and sex-matched healthy controls. Participants were enrolled in clinical protocols at the National Institutes of Health in Bethesda, Maryland, USA. The primary objectives of the study were twofold: first, to identify disease-specific and shared "pan-disease" signatures using the collected data, and second, to develop a Random Forest classifier integrating these datasets to differentiate between age- and sex-matched healthy individuals and monogenic patients. This classifier produced a metric known as the "Immune Health Metric" (IHM). Subsequent analysis demonstrated that the IHM effectively distinguished healthy subjects from individuals with multiple polygenic autoimmune and inflammatory diseases in independent datasets. Moreover, it exhibited correlations with healthy aging and tracked disease activities and treatment responses across both immunological and non-immunological conditions. Additionally, the IHM accurately predicted age-dependent antibody responses to various vaccines, including influenza, Hepatitis A/B, Yellow Fever, Varicella Zoster, and Meningococcal vaccines.The microarray-based transcriptomic data, aptamer-based serum protein concentrations (Somalogic platform), peripheral blood frequency data, and clinical information will be made accessible through the database of Genotypes and Phenotypes (dbGaP).

  Study phs002732

• Gene copy number variation in pediatric mental illness in a general population

  We assessed the relationship of gene copy number variation (CNV) in mental health/neurodevelopmental traits and diagnoses, physical health, and cognitive biomarkers in a community sample of 7,100 unrelated European, and East Asian children and youth (Spit for Science). Diagnoses of mental health disorders were found in 17.5% of participants and 27.6% scored in the highest 10% on either or both ADHD and OCD trait measures. Clinically relevant CNVs were present in 3.9% of participants and were associated with elevated scores on a continuous measure of ADHD (p=5.0×10-3), on a cognitive biomarker of mental health (response inhibition (p=1.0×10-2)), and on prevalence of mental disorders (p=1.9×10-6, odds ratio: 3.09). With a rise of mental illness, our data establishes a baseline for delineating genetic contributors in paediatric-onset conditions.

  Study EGAS00001006659

• Colon cancer ctDNA

  Samples prepared using Safe-SeqS technology. All samples ran on an Illumina MiSeq instrument. Fastq files for read 1 and the index read present (R and I respectively).

  Dataset EGAD00001003579