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• FIT interval CRCs versus Screen-detected CRCs

  Formalin-fixed, paraffin-embedded samples from 27 FIT interval CRC and 54 screen-detected CRCs collected in a pilot-program of FIT-based CRC screening in the southwest and northwest regions in the Netherlands, were used in this study. DNA was extracted for 1) Shallow Sequencing (copy number analysis) and 2) TSACP Amplicon Cancer Gene Panel (mutations) of 22 FIT Interval CRCs and 45 screen-detected CRCs.

  Dataset EGAD00001006409

• Single-cell RNA-seq data of bronchoalveolar lavage (BAL) fluid in late severe COVID-19

  We performed single-cell RNA-sequencing of cells in the bronchoalveolar lavage (BAL) fluid of late severe COVID-19. This study provides detailed insights into the alveolar macrophage response to SARS-CoV-2 infection and reveals a profibrotic macrophage response in severe COVID-19 patients.

  Dataset EGAD00001008161

• RNAseq_pituitary_adenoma

  Total RNA was extracted using RNAble (Eurobio), cleaned-up with RNeasy columns (Qiagen) and sequenced. The libraries were prepared at the Genomics Platform of the Cochin Institute, following the TruSeq Stranded mRNA protocol (Illumina), starting from 1 µg of high quality total RNA. Paired end (2 × 75 bp) sequencing was performed on a Nextseq 500 platform (Illumina). FASTQ sequences were aligned on hg19 (GRCh37) human reference genome with STAR (v.2.5.2a)

  Dataset EGAD00001004996

• WGS data from NEN patient derived tumor organoids (PDTOs) and matched parental tumors - MUMC

  The dataset includes cram files from WGS of 2 NEN tumors and matched PDTOs. For all tumors, cram files from WGS of matched normal tissue from the corresponding patients are included. Analysis VCF files are also included in the dataset. The sequencing was done with a NovaSeq 6000 instrument.

  Dataset EGAD00001009988

• AT-AML samples dataset

  Serial samples from one AT-AML patient as described in publication Goldgraben et al Pediatric Blood & Cancer 2020. Whole exome sequencing of a AT-'germline' blood sample, one bone marrow sample (at AML diagnosis) and 3 AML blood samples. Library preped using the Illumina Nextera Rapid Capture Exome Enrichment Kit, and sequenced as PE150 on HiSeq4000. Provided: 5 BAM files (GRCh37); 2 VCF analyses (germline and somatic)

  Dataset EGAD00001006090

• Prognostic and immunomodulatory consequences of ERV expression in ovarian cancer

  The dataset contains transcriptional data obtained using total RNA sequencing on a Illumina machin. 59 samples are from the Hammersmith Hospital (HH) cohort of human primary ovarian tumours and 20 samples are from ovarian cancer cell lines Kuramochi (3 replicates) and Ovsaho (2 replicates) treated with 1 uM DNMTi guadecitabine or vehicle, at an early (day 5) or late (day 8) timepoint.

  Dataset EGAD00001006589

• Single-cell RNA and TCR sequencing of 37 PBMC pools of advanced HCC patients.

  scRNAseq and scTCRseq of serial peripheral blood mononuclear cell (PBMC) samples (n=72) taken at various timepoints before and during treatment (Week 0 (W0), Week 3 (W3), Week 6 (W6)). PBMC samples were pooled together into 37 pools, loading 2 or three samples per lane in the 10X Genomics chip, in equal proportions, according to a pre-designed pooling matrix.

  Dataset EGAD00001011345

• BLUEPRINT Gene expression analysis during human B-cell differentiation using the Affymetrix Human Genome U219 Array

  We performed gene expression analysis using the Affymetrix Human Genome U219 Array of 9 subpopulations covering the complete B-cell maturation program: hematopoietic progenitor cells (HPC); pre-B-I cells (preB1C); pre-B-II cells (preB2C); naive B cells from peripheral blood (naiBC); naive B cells from tonsil (t-naiBC); germinal center B cells (gcBC); plasma cells from tonsil (t-PC); memory B cells from peripheral blood (memBC) and plasma cells from bone marrow (bm-PC). All the samples were isolated from healthy donors and, with the exception of bm-PC (only 1 replicate), we used 3 to 11 biological replicates of each subtype.

  Study EGAS00001001197

• Cooperative Study of Sickle Cell Disease (CSSCD)

  The Cooperative Study of Sickle Cell Disease was initiated in 1977 to determine the natural history of sickle cell disease (SCD) from birth to death in order to identify those factors contributing to the morbidity and mortality of the disease. Specific objectives included: 1) to study the effect of sickle cell disease on growth and development from birth through adolescence 2) to study the conditions or events that may be related to the onset of painful crises 3) to obtain data on the nature, duration, and outcome of major complications of SCD 4) determine the nature, prevalence, and age- related incidence of organ damage due to SCD, and 5) study the role of SCD and its interaction with selected health events.Phases 2 and 3 of the study involved followup of the infant cohort. A total of 709 infants (age less than 6 months) were enrolled during Phase 1 of the Cooperative Study of Sickle Cell Disease (CSSCD), and Phases 2 and 3 of the CSSCD was designed to follow these children for an additional 10 years. The study objectives included: 1) define prospectively the natural history of sickle cell disease; 2) determine the relationships between cognitive and academic functioning and brain status as determined by MRI; 3) determine the cognitive or behavioral markers of silent infarct; 4) determine the relationship of family functioning on the Family Environment Scale (FES) to brain status, cognitive functioning, and social and demographic factors; 5) continue studies that will enhance the state of knowledge on the influence of sickle cell disease on the psychosocial adjustment of children and adolescents. Phase 2A of the study sought to examine the progression of organ damage in the heart, lung, kidney, and liver in adult cohort patients (born before 1/1/56) enrolled in phase 1 of the study between 3/79 and 5/81. A total of 620 patients from 11 centers were eligible for phase 2A.Instructions for requesting individual-level data are available on BioData Catalyst at https://biodatacatalyst.nhlbi.nih.gov/resources/data/. Apply for data access in dbGaP. Upon approval, users may begin accessing requested data in BioData Catalyst. For questions about availability, you may contact the BioData Catalyst team at https://biodatacatalyst.nhlbi.nih.gov/contact.

  Study phs002362

• Discovery of Colorectal Cancer Susceptibility Genes in High-Risk Families

  Colorectal cancer remains one of the most common cancers in the US with 146,970 new diagnoses and 49,920 deaths estimated for 2009. Colon cancer is also one of the most familial of cancers. Individuals with a first-degree relative with colon cancer have a 2- to 3-fold increased risk, and those with more than one first-degree relative with colon cancer, or a single first-degree relative affected at age 50 years, have a 3- to 6-fold greater risk than those with no family history. The most prominent high-risk colorectal cancer susceptibility genes, APC, MLH1, MSH2, MSH6, and PTEN, were all discovered more than a decade ago. Currently, mutation screening of these genes, plus a short list of additional genes that are responsible for a very small fraction of colorectal cancer, plays an important role in the clinical management of individuals with a strong family history of the disease or syndromic evidence for the presence of a gene mutation. At the other end of the risk spectrum, genome-wide association studies have identified a number of common alleles with very modest effects on colorectal cancer risk; their clinical utility has yet to be established. However, taken together, the known spectrum of genetic effects only explain about one quarter of the overall familial excess of colorectal cancer. It should be emphasized that, at present, the vast majority of individuals seen at familial cancer clinics are counseled on the basis of their family history alone because they do not have mutations in the known susceptibility genes. Accordingly, the long-term objective of this project is to identify the majority of genes responsible for the unexplained component of inherited colorectal cancer risk. Nextgen DNA sequencing is well suited for application to research questions in genetic susceptibility for which linkage analysis is confounded by extensive genetic heterogeneity. Taking advantage of unparalleled familial cancer genetics resources available through the Utah Population Database, candidate genes have been identified by sequencing all of the gene exons in the human genome from a series of colorectal cancer cases with a very strong family history of colorectal cancer not explained by one of the currently known high-risk susceptibility genes.

  Study phs001787