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• Genome and transcriptome sequence data from a metastatic breast carcinoma patient

  Genome and transcriptome sequence data from a metastatic breast carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004688

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004687

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004686

• Genome and transcriptome sequence data from a breast cancer patient

  Genome and transcriptome sequence data from a breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004711

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004710

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004713

• Genome and transcriptome sequence data from a metastatic pancreatic cancer patient

  Genome and transcriptome sequence data from a metastatic pancreatic cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004715

• Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient

  Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004716

• Genome and transcriptome sequence data from a metastatic non-small cell lung adenocarcinoma patient

  Genome and transcriptome sequence data from a metastatic non-small cell lung adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004714

• Genome and transcriptome sequence data from a metastatic pancreatic cancer patient

  Genome and transcriptome sequence data from a metastatic pancreatic cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004717

• Genome and transcriptome sequence data from a metastatic pancreatic cancer patient

  Genome and transcriptome sequence data from a metastatic pancreatic cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004718

• Autozygosity pilot - Born in Bradford (2014-11-20)

  The offspring of first cousin marriages have ~6% of their genome autozygous, i.e. homozygous identical by descent, or even more if there was further consanguinity in their ancestry. In the UK there are large populations with very high first cousin marriage rates of 20-50%. Sequencing the exomes of a sample of these individuals has the potential both to support genetic health programmes in these populations, and to provide genetic research information about rare loss of function mutations. This pilot study based on existing cohort samples from the Born In Bradford study will identify homozygous individuals for almost all variants down to an allele frequency around 1%, plus individuals carrying hundreds of new homozygous rare loss-of-function variants, and will support development of community relations and ethics for a wider study currently being designed. The data deposited in the EGA consist of low coverage whole exome sequencing on these samples.Data Access is controlled by the Wellcome Trust Sanger Institute DAC and the Born In Bradford Executive Group. This dataset contains all the data available for this study on 2014-11-20.

  Dataset EGAD00001001079

• Whole-genome sequencing in 14 cases and whole-exome sequencing in 90 cases of Chinese ESCC

  Esophageal cancer is one of the most aggressive cancers and the sixth leading cause of cancer death worldwide1. Approximately 70% of the global esophageal cancers occur in China and over 90% histopathological forms of this disease are esophageal squamous cell carcinoma (ESCC)2-3. Currently, there are limited clinical approaches for early diagnosis and treatment for ESCC, resulting in a 10% 5-year survival rate for the patients. Meanwhile, the full repertoire of genomic events leading to the pathogenesis of ESCC remains unclear. Here we show a comprehensive genomic analysis in 158 ESCC cases, as part of the International Cancer Genome Consortium (ICGC) Research Projects (http://icgc.org/icgc/cgp/72/371/1001734). We conducted whole-genome sequencing in 14 ESCC cases and whole-exome sequencing in 90 cases.

  Dataset EGAD00001001691

• Genome and transcriptome sequence data from a squamous cell carcinoma patient

  Genome and transcriptome sequence data from a squamous cell carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002040

• Genome and transcriptome sequence data from a breast ductal carcinoma patient

  Genome and transcriptome sequence data from a breast ductal carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002047

• Genome and transcriptome sequence data from a peripheral T-cell lymphoma patient

  Genome and transcriptome sequence data from a peripheral T-cell lymphoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002038

• MARS-seq dataset of five obese human subjects and a lean human subject

  Biopsies from visceral adipose tissue from the omental depot (OAT) were obtained from five obese individuals and one lean donor with participant informed consent obtained after the nature and possible consequences of the studies were explained under protocols approved by the Institutional Review Boards of the Perelman School of Medicine at the University of Pennsylvania, the Children’s Hospital of Philadelphia, or the Tel Aviv Sourasky Medical Center. The obese donors underwent bariatric surgery, the lean donor underwent cholecystectomy. OAT samples were placed in 1 mL of DMEM, and finely minced under sterile conditions before digestion in 50 mL of DMEM with 3 mg/1 mL collagenase IV (Gibco). Samples were incubated at 37°C in a rotating oven for 20-60 min. Adipocyte and stromal vascular fractions (SVF) were separated by centrifugation, and red blood cells (RBCs) were removed from the SVF by histopaque gradient (Sigma). Single-cell RNA-sequencing libraries were prepared using the MARS-seq pipeline, and sequenced on the MiSeq 500 or HiSeq 2500 Sequencing System (Illumina).

  Dataset EGAD00001005100

• Genome and transcriptome sequence data from a breast ductal carcinoma patient

  Genome and transcriptome sequence data from a breast ductal carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005823

• Genome and transcriptome sequence data from a metastatic rectal carcinoma patient

  Genome and transcriptome sequence data from a metastatic rectal carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005825

• Genome and transcriptome sequence data from a primary unknown- upper GI or pulmonary patient

  Genome and transcriptome sequence data from a primary unknown- upper GI or pulmonary patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005827

• Genome and transcriptome sequence data from a metastatic choroidal melanoma patient

  Genome and transcriptome sequence data from a metastatic choroidal melanoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005828

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005830

• Genome and transcriptome sequence data from a poorly differentiated adenocarcinoma more consistent with metastatic melanoma patient

  Genome and transcriptome sequence data from a poorly differentiated adenocarcinoma more consistent with metastatic melanoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005831

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005832

• Genome and transcriptome sequence data from a metastatic rectal cancer patient

  Genome and transcriptome sequence data from a metastatic rectal cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005833

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005834

• Genome and transcriptome sequence data from a metastatic squamous cell carcinoma of the esophagus patient

  Genome and transcriptome sequence data from a metastatic squamous cell carcinoma of the esophagus patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005835

• Genome and transcriptome sequence data from a metastatic pancreatic adenocarcinoma patient

  Genome and transcriptome sequence data from a metastatic pancreatic adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005836

• Genome and transcriptome sequence data from a metastatic adenocarcinoma of unknown primary (upper GI?) patient

  Genome and transcriptome sequence data from a metastatic adenocarcinoma of unknown primary (upper GI?) patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005837

• Genome and transcriptome sequence data from a metastatic choroid melanoma patient

  Genome and transcriptome sequence data from a metastatic choroid melanoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005839

• Genome and transcriptome sequence data from a carcinoma primary unknown origin patient

  Genome and transcriptome sequence data from a carcinoma primary unknown origin patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005840

• Genome and transcriptome sequence data from a metastatic pancreatic adenocarcinoma patient

  Genome and transcriptome sequence data from a metastatic pancreatic adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005842

• Genome and transcriptome sequence data from a metastatic gastrointestinal stromal tumor patient

  Genome and transcriptome sequence data from a metastatic gastrointestinal stromal tumor patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005843

• Genome and transcriptome sequence data from a metastatic adrenocortical carcinoma patient

  Genome and transcriptome sequence data from a metastatic adrenocortical carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005844

• Genome and transcriptome sequence data from a metastatic unknown primary cancer patient

  Genome and transcriptome sequence data from a metastatic unknown primary cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005845

• Genome and transcriptome sequence data from a cavernous sinus meningioma patient

  Genome and transcriptome sequence data from a cavernous sinus meningioma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005846

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005847

• Genome and transcriptome sequence data from a metastatic squamous cell carcinoma of the lung patient

  Genome and transcriptome sequence data from a metastatic squamous cell carcinoma of the lung patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005850

• Single cell sequencing of a post-PD-1 inhibitor metastatic melanoma mass

  Three technical replicates of FACS-sorted T cells (CD45+CD3+) and one replicate of FACS-sorted tumor cells (MCSP+) were loaded to a targeted 10,000 cells per lane on the 10X Genomics Chromium Controler with the single cell 5’ Immune Repertoire and Gene Expression profiling kit. In total, we loaded ~30,000 individual tumor infiltrating lymphocytes (TILs) and ~10,000 melanoma cells on the 10X platform (10X Genomics, CA, USA). Reverse transcription, TCR enrichment, and library preparations were performed according to the 10X Genomics 5’ V(D)J protocol revision C. Transcriptome libraries were pooled and sequenced on the Illumina NovaSeq 6000 S2 flow cell with 26 R1, 8 i7, and 91 R2 cycles respectively. The TCR libraries were pooled and sequenced on the Illumina MiSeq V2 150 cycles paired-end. Single cell transcriptomic and TCR data was processed with the 10X Genomics Cell Ranger Pipeline version 2.2.0 with the software-provided GRCh38 reference transcriptomes. After quality control, there was RNAseq profile data available from 6267 immune and 4303 melanoma cells. Downstream processing and visualization was encompassed through Seurat and tSNE plots.

  Dataset EGAD00001006013

• Cryopreservation of human cancers conserves tumour heterogeneity for single-cell multi-omics analysis

  Single-cell RNA-Sequencing of three primary breast cancers, two primary prostate cancers, and a metastatic melanoma sample from Wu et al. (2021) Genome Medicine study. Each tumour was sequenced across different cryopreservation conditions including Fresh Tissue (FT), cryopreserved single-cell suspensions (CCS), cryopreserved solid tissue fragments (CT) and a cryopreserved after overnight cold storage (CO). Data was generated using the Chromium controller (10X Genomics) and sequenced on the NextSeq platform.

  Dataset EGAD00001007030

• PopCol 16S gut microbiome sequencing

  PopCol is a cohort study in Stockholm, Sweden that includes a data-rich set of individuals with data available from bowel symptoms questionnaires, gastroenterology visits and biospecimens (genotype and 16S sequencing from blood and stool samples, respectively). Genotyping was carried out using the Illumina HumanOmniExpressExome-8v1 arrays at the SciLifeLab NGI facility in Uppsala, Sweden. Fecal DNA was extracted from samples kept at -80°C using Qiagen 5 QIAamp DNA Stool Mini Kits and analyzed using 16S rRNA gene amplicon sequencing (in the V1-V2 hypervariable region). This was performed on the Illumina MiSeq platform at the Institute of Clinical Molecular Biology (IKMB) in Kiel, Germany. Of these, six PopCol participants were PPI users and 12 used antibiotics. The study was approved by the local Committee of Research Ethics (Forskningskommitté Syd) at Karolinska Institutet, Stockholm, in November 2001. Written informed consent was obtained from all participants

  Dataset EGAD00001007071

• Dataset for the Pearl study

  Biomarkers to identify patients without benefit from adding everolimus to endocrine treatment in metastatic breast cancer (MBC) are needed. We report the results of the Pearl trial conducted in five Belgian centers assessing 18F-FDG-PET/CT non-response (n=45) and ctDNA detection (n=46) after 14 days of exemestane-everolimus (EXE-EVE) to identify MBC patients who will not benefit. Metabolic non-response rate was 66.6%. Median PFS in non-responding patients (using as cut-off 25% for SUVmax decrease) was 3.1 months compared to 6.0 months in those showing response (HR: 0.77, 95% CI: 0.40-1.50, p=0.44). Difference was significant when using a “post-hoc” cut-off of 15% (PFS 2.2 months vs 6.4 months). ctDNA detection at D14 was associated with PFS: 2.1 months vs 5.0 months (HR-2.5, 95% CI: 1.3-5.0, p=0.012). Detection of ctDNA and/or the absence of 18F-FDG-PET/CT response after 14 days of EXE-EVE identifies patients with a low probability of benefiting from treatment. Independent validation is needed.

  Dataset EGAD00001007979

• Alloreactive T-cell receptor (TCR) repertoire in kidney transplantation

  We analyzed the T-cell receptor (TCR) repertoires from twelve kidney transplant recipients. Six out of the twelve kidney transplant recipients experienced a cellular rejection after kidney transplantation. TCR repertoires of CD4+ and CD8+ positive T-cells were assessed prior to transplantation and after transplantation at time of allograft biopsy using RNA based T-cell receptor beta next generation sequencing (NGS). In addition, the pre-formed alloreactive TCR repertoire for each kidney transplant recipient was identified using mixed lymphocyte reaction and donor reactive T-cells were subjected to TCR beta sequencing. In two out of the six patients with cellular rejection the TCR repertoire of graft infiltrating T-cells was additionally captured. This dataset comprises a total of 98 samples. NGS TCR beta libraries of all samples were sequenced on an Illumina NextSeq 500 and raw sequencing data (in the form of fastq files) as well assembled clonotypes and their counts (in the form of clonotype tables) are provided.

  Dataset EGAD00001007695

• The mutational landscape of human somatic and germline cells

  During the course of a lifetime normal human cells accumulate mutations. Here, using multiple samples from the same individuals we compared the mutational landscape in 29 anatomical structures from soma and the germline. Two ubiquitous mutational signatures, SBS1 and SBS5/40, accounted for the majority of acquired mutations in most cell types but their absolute and relative contributions varied substantially. SBS18, potentially reflecting oxidative damage, and several additional signatures attributed to exogenous and endogenous exposures contributed mutations to subsets of cell types. The mutation rate was lowest in spermatogonia, the stem cell from which sperm are generated and from which most genetic variation in the human population is thought to originate. This was due to low rates of ubiquitous mutation processes and may be partially attributable to a low cell division rate of basal spermatogonia. The results provide important insights into how mutational processes affect the soma and germline.

  Dataset EGAD00001006642

• The mutational landscape of human somatic and germline cells

  During the course of a lifetime normal human cells accumulate mutations. Here, using multiple samples from the same individuals we compared the mutational landscape in 29 anatomical structures from soma and the germline. Two ubiquitous mutational signatures, SBS1 and SBS5/40, accounted for the majority of acquired mutations in most cell types but their absolute and relative contributions varied substantially. SBS18, potentially reflecting oxidative damage, and several additional signatures attributed to exogenous and endogenous exposures contributed mutations to subsets of cell types. The mutation rate was lowest in spermatogonia, the stem cell from which sperm are generated and from which most genetic variation in the human population is thought to originate. This was due to low rates of ubiquitous mutation processes and may be partially attributable to a low cell division rate of basal spermatogonia. The results provide important insights into how mutational processes affect the soma and germline.

  Dataset EGAD00001006643

• The Precision Medicine in Liver Cancer across an Asia-pacific NETwork (PLANET) - Intratumoural immune heterogeneity

  The clinical relevance of immune landscape intratumoural heterogeneity (immune-ITH) and its role in tumour evolution remain largely unexplored. Here, we uncover significant spatial and phenotypic immune–ITH from multiple tumour sectors and decipher its relationship with tumour evolution and disease progression in hepatocellular carcinomas (HCC). Immune–ITH is associated with tumour transcriptomic-ITH, mutational burden, and distinct immune microenvironments. Tumours with low immune–ITH experience higher immunoselective pressure and escape via loss of heterozygosity in human leukocyte antigens and immunoediting. Instead, the tumours with high immune-ITH evolve to a more immunosuppressive/exhausted microenvironment. This gradient of immune pressure along with immune-ITH represents a hallmark of tumour evolution, which is closely linked to the transcriptome-immune networks that contributes to disease progression and immune inactivation. Remarkably, high immune-ITH and its transcriptomic signature are predictive for worse clinical outcome in HCC patients. This in-depth investigation of ITH provides evidence on tumour-immune co-evolution along HCC progression.

  Dataset EGAD00001006570

• RNA-seq study of a Princess Margaret Cancer Centre human acute myeloid leukemia patient cohort

  The PMCC AML RNAseq dataset consists of 81 AML patient samples (clinical data in Supplemental Table 11 of manuscript), processed in two batches. These patient samples are able to engraft in the NSG (NOD.Cg PrkdcscidIl2rgtm1Wjl /SzJ) mouse model. Five patients (90543, 598, 90240, 110484, 100500) were included in both batches. Viaably frozen material from the Leukemia Tissue Bank at Princess Margaret Cancer Centre/ University Health Network were thawed by dropwise addition of X-VIVO + 50% fetal calf serum supplemented with DNase (100μg/mL final concentration, Roche). RNA was extracted from bulk peripheral blood mononuclear cells (PBMC) using the RNeasy Micro Kit (Qiagen Inc.). A paired-end 76 base-pair flow-cell lane Illumina High seq 2000 yielded an average of 240 million sequence reads aligning to genome per sample at the Genome Sciences Centre, BC Cancer Agency for cohort 1. Cohort 2 was subjected to 125 bp, paired-end RNA-sequencing on the Illumina HiSeq 2500 with an average of 50 million reads/sample at the Centre for Applied Genomics, Sick Kids Hospital.

  Dataset EGAD00001006576

• Myeloid cell programming in patients with non-medullary thyroid carcinoma

  This dataset contains single-cell RNA sequencing data from patients with thyroid cancer (n=7), multinodal Goiter (n=3) and healthy individuals (n=5). Mononuclear cells were taken from both the peripheral blood and the bone marrow compartments. We used a pooled single-cell design where multiple individuals were pooled in a single sample for sequencing (NextSeq 500-V2) and later demultiplexed using their genotype data. Associated metadata contains information on the phenotypes per individual, the pooling design and the linkage between the supplied files and sequenced pools. Due to limitations from EGA in uploading single-cell data, the raw fastq files were processed as follows: (i) I1/I2/R1/R2 fast files were concatenated over the different lanes. (ii) Concatenated I1 and I2 files were interleaved, as were the concatenated R1 and R2 files to generate two fastq files per pool containing all the information. To interleave the fastq files, the BBmap tool bbmap/reformat.sh was used, which can also be used to de-interleave the files.

  Dataset EGAD00001008108

• Targeted myeloid panel DNA-Sequencing Mutations Matrix Validation Cohort

  Profiling of co-mutations was done by targeted resequencing using the TruSight Myeloid assay (Illumina, Chesterford, UK) covering 54 genes recurrently mutated in AML: BCOR, BCORL1, CDKN2A, CEBPA, CUX1, DNMT3A, ETV6, EZH2, IKZF1, KDM6A, PHF6, RAD21, RUNX1, STAG2, ZRSR2, ABL1, ASXL1, ATRX, BRAF, CALR, CBL, CBLB, CBLC, CDKN2A, CSF3R, FBXW7, FLT3, GATA1, GATA2, GNAS, HRAS, IDH1, IDH2, JAK2, JAK3, KIT, KRAS, MLL, MPL, MYD88, NOTCH1, NPM1, NRAS, PDGFRA, PTEN, PTPN11, SETBP1, SF3B1, SMC1A, SMC3, SRSF2, TET2, TP53, U2AF1 and WT1. For each reaction, 50 ng of genomic DNA was used. Library preparation was done as recommended by the manufacturer (TruSight Myeloid Sequencing Panel Reference Guide 15054779 v02, Illumina). Samples were sequenced paired-end (150 bp PE) on NextSeq- (Illumina) or (300 bp PE) MiSeq-NGS platforms, with a median coverage of 3076 reads (range 824–30565). Sequence data alignment of demultiplexed FastQ files, variant calling and filtering was done using the Sequence Pilot software package (JSI medical systems GmbH, Ettenheim, Germany) with default settings and a 5% variant allele frequency (VAF) mutation calling cut-off. Human genome build HG19 was used as reference genome for mapping algorithms.

  Dataset EGAD00001008506

• Pulmonary atypical carcinoid multi-omic dataset on up to 42 tumours from same patient

  Pulmonary atypical carcinoid. DNA WES and RNA-Seq on 42 tumour samples collected at autopsy, 10x Chromium linked read whole genome sequencing on four tumours plus one normal sample, and targeted DNA sequencing on two clinical biopsies and one blood plasma sample. Note – RNA-Seq dataset features complex batch effect attributable to tissue processing artefacts, as described in "Complex patterns of genomic heterogeneity identified in 42 tumor samples and ctDNA of a pulmonary atypical carcinoid patient" - Robb et al., 2022 and detailed in Supplementary Table S3. Note – RNA-Seq dataset features complex batch effect attributable to tissue processing artefacts, as described in "Complex patterns of genomic heterogeneity identified in 42 tumor samples and ctDNA of a pulmonary atypical carcinoid patient" - Robb et al., 2022 and detailed in Supplementary Table S3.

  Dataset EGAD00001009296

• An atlas of the developing human fetal spine

  The primitive streak emerges during the 14th day of human development and establishes dorsoventral and antero-posterior (craniocaudal) body axes. Segmentation along the craniocaudal axis is governed by Hox genes; four clusters of transcription factors whose 3’ to 5’ expression correlates with position along the axis. The precise utilisation of Hox genes in different cell types remains incompletely characterised in humans. In this study, we applied single-cell and spatial transcriptomics to contiguous regions of the human fetal spine between the 5th and 13th post-conception weeks. We built a detailed developmental atlas to examine the segmental expression of Hox genes across different cell types, observing that the Hox code was displayed by all anatomically fixed cell types along the craniocaudal axis. By contrast, mature derivatives of neural crest cells retained the anatomical Hox code of their origin within the crest, a pattern reproduced across neural crest derivatives in other human fetal organs. These findings indicate that scars of Hox gene expression persist in crest cells which may serve as barcodes of neural crest migration.

  Dataset EGAD00001009801

• Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient

  Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010940

• Genome and transcriptome sequence data from a myoepithelioma patient

  Genome and transcriptome sequence data from a myoepithelioma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010938

• Genome and transcriptome sequence data from a leiomyosarcoma patient

  Genome and transcriptome sequence data from a leiomyosarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010939

• Genome and transcriptome sequence data from a melanoma patient

  Genome and transcriptome sequence data from a melanoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010943

• Genome and transcriptome sequence data from a pancreatic cancer patient

  Genome and transcriptome sequence data from a pancreatic cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010945

• Genome and transcriptome sequence data from a cervical cancer patient

  Genome and transcriptome sequence data from a cervical cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010947

• Genome and transcriptome sequence data from a pancreatic cancer patient

  Genome and transcriptome sequence data from a pancreatic cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010948

• Genome and transcriptome sequence data from a endometrial adenocarcinoma patient

  Genome and transcriptome sequence data from a endometrial adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010949

• Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient

  Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010951

• Genome and transcriptome sequence data from a uveal melanoma patient

  Genome and transcriptome sequence data from a uveal melanoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010956

• Genome and transcriptome sequence data from a leiomyosarcoma patient

  Genome and transcriptome sequence data from a leiomyosarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010957

• Genome and transcriptome sequence data from a metastatic melanoma patient

  Genome and transcriptome sequence data from a metastatic melanoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010958

• Genome and transcriptome sequence data from a metastatic adenocarcinoma patient

  Genome and transcriptome sequence data from a metastatic adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010960

• Genome and transcriptome sequence data from a pancreas adenocarcinoma patient

  Genome and transcriptome sequence data from a pancreas adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010963

• Genome and transcriptome sequence data from a leiomyosarcoma patient

  Genome and transcriptome sequence data from a leiomyosarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010965

• Genome and transcriptome sequence data from a metastatic chondrosarcoma patient

  Genome and transcriptome sequence data from a metastatic chondrosarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010966

• Genome and transcriptome sequence data from a primary unknown patient

  Genome and transcriptome sequence data from a primary unknown patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010968

• WGS dataset of Mutational Mechanisms in Multiply Relapsed Pediatric Acute Lymphoblastic Leukemia

  Pediatric acute lymphoblastic leukemia (ALL) is marked by low mutational load at initial diagnosis, which increases at relapse. The elevated mutational load at relapse can partly be explained by at least two therapy-related effects and a combination of therapy and underlying mismatch repair deficiency. However, our understanding of the type and timing of mutational mechanisms in relapsed ALL is limited, and it is unclear to what extent mutational processes contribute to disease progression. We collected a cohort of 29 Dutch ALL patients across multiple treatment protocols who had multiple relapses. Using whole genome sequencing of the sequential tumor samples of each patient we were able to distinguish the mutational processes active in relapsed ALL and could track the activity of mutational processes over time. This allowed us to investigate whether subtype-specific mutational processes at diagnosis can continue in relapse or emerge at relapse if absent in initial diagnosis. Furthermore, we assessed whether the activity of mutational processes contributed to disease development and relapse.

  Dataset EGAD00001015401

• Kids First: Genomic Studies of Orofacial Cleft Birth Defects

  The Gabriella Miller Kids First Pediatric Research Program (Kids First) is a trans-NIH effort initiated in response to the 2014 Gabriella Miller Kids First Research Act and supported by the NIH Common Fund. This program focuses on gene discovery in pediatric cancers and structural birth defects and the development of the Gabriella Miller Kids First Pediatric Data Resource (Kids First Data Resource). Both childhood cancers and structural birth defects are critical and costly conditions associated with substantial morbidity and mortality. Elucidating the underlying genetic etiology of these diseases has the potential to profoundly improve preventative measures, diagnostics, and therapeutic interventions. WGS and phenotypic data from this study are accessible through dbGaP and kidsfirstdrc.org, where other Kids First datasets can also be accessed. The Kids First study of nonsyndromic orofacial cleft birth defects (OFCs) is a whole genome sequencing study of 415 White parent-case trios drawn from ongoing collaborations led by Dr. Mary L. Marazita of the University of Pittsburgh Center for Craniofacial and Dental Genetics, including collaborations with Dr. George Wehby of the University of Iowa, Dr. Jacqueline Hecht of the University of Texas, and Dr. Terri Beaty of Johns Hopkins University. Sequencing was done by the Washington University McDonell Genome Institute. The case in each of the Kids First trios has cleft lip (CL, Figure A), cleft palate (CP, Figure B), or both (CL+CP, Figure C): OFCs are genetically complex structural birth defects caused by genetic factors, environmental exposures, and their interactions. OFCs are the most common craniofacial anomalies in humans, affecting approximately 1 in 700 newborns, and are one of the most common structural birth defects worldwide. On average a child with an OFC initially faces feeding difficulties, undergoes 6 surgeries, spends 30 days in hospital, receives 5 years of orthodontic treatment, and participates in ongoing speech therapy, leading to an estimated total lifetime treatment cost of about $200,000. Further, individuals born with an OFC have higher infant mortality, higher mortality rates at all other stages of life, increased incidence of mental health problems, and higher risk for other disorders (notably including breast, brain, and colon cancers). Prior genome-wide linkage and association studies have now identified at least 18 genomic regions likely to contribute to the risk for nonsyndromic OFCs. Despite this substantial progress, the functional/pathogenic variants at OFC-associated regions are mostly still unknown. Because previous OFC genomic studies (genome-wide linkage, genome-wide association studies (GWAS), and targeted sequencing) are based on relatively sparse genotyping data, they cannot distinguish between causal variants and variants in linkage disequilibrium with unobserved causal variants. Moreover, it is unknown whether the association or linkage signals are due to single common variants, haplotypes of multiple common variants, clusters of multiple rare variants, or some combination. Finally, we cannot yet attribute specific genetic risk to individual cases and case families. Therefore, the goal of the current study is to identify specific OFC risk variants in Whites by performing whole genome sequencing of parent-case trios.

  Study phs001168

• National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) Gene Discovery in Autosomal Dominant Focal Segmental Glomerulosclerosis (FSGS)

  Focal segmental glomerulosclerosis (FSGS) is a frequent cause of end-stage renal disease. The pathogenesis of FSGS has not been precisely defined and there are no consistently effective treatments. Recent studies identifying causal genes in rare, inherited FSGS, including our own study, have associated mutations in at least six genes with familial FSGS, and each discovery has clarified molecular mechanisms of glomerular injury. To build on this productive line of inquiry, we have ascertained and carefully characterized 118 families with familial FSGS. We have screened the remainder of our families for mutations in genes known to cause FSGS and identified the causal mutations in an additional 6 kindreds; the genetic basis of disease in the remaining 111 families is unknown. The objective of this proposal is to use this valuable and unique family resource to systematically identify causal genes for familial FSGS. Limitations of current conventional linkage and positional cloning approaches include their requirement for large, multiplex families. In addition, narrowing candidate areas in traditional linkage analysis can be difficult due to large regions that lack recombination events and hence these regions have required cumbersome and lengthy screening for causative mutations. Powerful new genetic tools can facilitate this screening process and improve variant discovery in smaller families. In particular, efficient whole-exome sequencing, the targeted capture of protein-coding gene sequences, should be particularly useful in our studies since most Mendelian disorders are caused by mutations affecting exomes of the target gene. Thus, by combining genome-wide linkage analysis (GWLS) and whole-exome sequencing, we can maximize impact of our family data and accelerate identification of novel mutations in FSGS. In preliminary studies, we have used this combination to identify a novel variant in the WT1 (Wilms' Tumor-1) gene in one FSGS family, and we have evidence suggesting it is the causal mutation. This success provides proof-of-concept and provides a roadmap of how genes will be identified and evaluated in the proposed studies. Our hypothesis is that causes of inherited FSGS in our cohort of families will be sequence variants in the coding region of genes not previously associated with familial FSGS. We aim to: 1) Use GWLS and whole-exome sequencing to identify genetic variants associated with familial FSGS. 2) Characterize functional consequences of candidate causative mutations and 3) Determine the prevalence in the Duke FSGS dataset of these new causative mutations identified in Aim 2. Any genes found to have causative mutations will be sequenced in the remaining families and take full advantage of our family resource. By combining genome-wide linkage analysis (GWLS), whole-exome sequencing, and characterization of variants' functional consequences, we will significantly improve understanding of normal glomerular biology and of the pathogenesis of FSGS and related glomerular diseases. Moreover, our discoveries are likely to reveal new opportunities to improve therapy for a disease that currently has few effective treatments.

  Study phs000777

• Surveillance, Epidemiology and End Results (SEER) Formalin Fixed Paraffin Embedded (FFPE) Tissue Feasibility Study

  Next Generation Sequencing (NGS) technologies are being used for detection of somatic mutations in tumors and studies of germline variation. However, most NGS studies used DNA isolated either from whole blood or fresh frozen tissue specimens. Meanwhile, the tissue specimens available from most National Cancer Institute (NCI) funded cohorts and the Surveillance, Epidemiology and End Results (SEER) registries (http://seer.cancer.gov/biospecimen) are primarily formalin fixed paraffin embedded (FFPE). There are limited data, on a small number of FFPE tissue samples, which suggest NGS is feasible. Much less is known about the feasibility of these technologies for large scale studies or using older FFPE specimens (e.g. 5-30 years old). The SEER cancer registries cover approximately 28% of the United States population, providing high quality demographic, clinical, pathologic, and survival data. The SEER Residual Tissue Repository (RTR) program was established in 2003. The RTR maintains biospecimens obtained from three of SEER' population-based cancer registries: Iowa, Hawaii, and Los Angeles. Investigators at government, academic, and nonprofit institutions may apply to the program to obtain annotated FFPE tumor tissue specimens to study biomarkers, etiology, and other aspects with a population-based sample of cancer cases. The main objective of this project was to conduct a pilot study to determine whether the DNA obtained from archival FFPE tissue from 3 SEER Registries is of sufficient quality and quantity to conduct NGS. For Exome sequencing, sixty high-grade serous ovarian adenocarcinomas from FFPE tissues which were between 7 and 31 years old were obtained from three SEER registries. DNA was extracted, quantified, quality assessed, and subjected to whole exome sequencing. DNA extraction (yields and quality) and whole exome sequencing (depths of coverage and exome coverage obtained) results from this study will be presented. For RNA-sequencing, sixty-seven high-grade serous ovarian adenocarcinomas from FFPE tissues which were between 7 and 31 years old were obtained from three SEER registries. Total RNA was extracted, quantified, quality assessed, and subjected to whole transcriptome sequencing. Ultimately data derived from this analysis could serve as the basis for determining the utility of archival FFPE biospecimens for characterization and discovery projects utilizing NGS technologies instead of relying on frozen biospecimens.

  Study phs000950

• San Francisco Bay Area Latina Breast Cancer Study

  The genome-wide association study (GWAS) includes participants enrolled into two different studies. The first study, the San Francisco Bay Area Cancer Study (SFBCS) is a population-based case-control study of breast cancer conducted in the San Francisco Bay Area and included women ages 35-79 years from three racial/ethnic groups: Non-Hispanic whites, African Americans, and Hispanics/Latinas. For the GWAS, only Hispanic/Latina women were included. Women diagnosed with invasive breast cancer between 1995 and 2002 were identified through the Greater Bay Area Cancer Registry. Controls were identified by random digit dialing and were frequency-matched to cases by age in 5 year increments and by race/ethnicity. Hispanic/Latina ethnicity was assessed by self-report. 175 Hispanic/Latina cases and 307 Hispanic/Latina controls from the SFBCS had given adequate consent and provided biospecimens that were used in the GWAS to be included in this data submission. The second study is the Northern California site of the Breast Cancer Family Registry (NC-BCFR). This population-based family study recruited breast cancer cases ages 18-64 years diagnosed from 1995-2009 that were identified through the Greater Bay Area Cancer Registry. Cases included all women at increased genetic susceptibility for breast cancer who met one or more of the following criteria: (a) being diagnosed with breast cancer at age <35 years; b) having a personal history of ovarian cancer or childhood cancer; (c) being diagnosed with two different breast cancers (bilateral breast cancers), with the first one diagnosed at age <50 years; and d) having one or more first-degree relatives with breast cancer, ovarian cancer or childhood cancer. Cases not meeting these criteria were randomly sampled and racial/ethnic minorities were oversampled. Controls were recruited by random digit dialing and were matched by 5-year age increments and by race/ethnicity. For the current GWAS only Latina/Hispanic cases and controls were included. Latina/Hispanic ethnicity was assessed by self-report. 631 Hispanic/Latina cases and 61 Hispanic/Latina controls from the NC-BCFR had given adequate consent and provided biospecimens that were used in the GWAS to be included in this data submission.

  Study phs000912

• Coronary Artery Risk Development in Young Adults (CARDIA) Study - Cohort

  CARDIA is a study examining the etiology and natural history of cardiovascular disease beginning in young adulthood. In 1985-1986, a cohort of 5115 healthy black and white men and women aged 18-30 years were selected to have approximately the same number of people in subgroups of age (18-24 and 25-30), sex, race, and education (high school or less and more than high school) within each of four US Field Centers. 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), and 2010-2011 (Year 25); the proportions of the surviving cohort that have returned for the seven follow-up examinations were 90%, 86%, 81%, 79%, 74%, 72%, and 72%, respectively. In addition to the follow-up examinations, participants are contacted regularly for the ascertainment of information on out-patient procedures and hospitalizations experienced between contacts. Within the past five years, 95% of the original surviving cohort has been contacted. While the specifics of each examination has differed somewhat, data have been collected on a variety of factors believed to be related to heart disease. These include conditions with clear links to heart disease such as blood pressure, cholesterol and other lipids. Data have also been collected on physical measurements such as weight and skinfold fat as well as lifestyle factors such as substance use (tobacco and alcohol), dietary and exercise patterns, behavioral and psychological variables, medical and family history, and other chemistries (e.g., insulin and glucose). In addition, subclinical atherosclerosis was measured via echocardiography during Years 5, 10, and 25, computed tomography during Years 15 and 20, and carotid ultrasound during Year 20. The CARDIA Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the "Sub-studies" box located on the right hand side of this top-level study page phs000285 CARDIA Cohort. phs000236 PAGE_CALiCo_CARDIA phs000309 GENEVA_CARDIA phs000399 GO-ESP HeartGO_CARDIA phs000613 CARDIA_CARe

  Study phs000285

• National Heart Lung and Blood Institute (NHLBI) GO-ESP: Heart Cohorts Component of the Exome Sequencing Project (ARIC)

  The NHLBI "Grand Opportunity" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the "exome") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. HeartGO is a consortium of six well-phenotyped NHLBI cohorts: Atherosclerosis Risk in Communities (ARIC) study, the Coronary Artery Risk Development in Young Adults (CARDIA) study, the Cardiovascular Health Study, the Framingham Heart Study, the Jackson Heart Study, and the Multi-Ethnic Study of Atherosclerosis. Together, these cohorts have provided DNA and phenotype datasets from a diverse cohort of individuals of African-American, Caucasian, Asian, and Hispanic ancestry to be made available for use by qualified investigators in dbGaP. HeartGO investigators will conduct genotype-phenotype analyses for phenotypes related not only to heart disease but with other variables that will be contributed to dbGaP. The HeartGO dataset provides investigators with genotype-phenotype analytic opportunities for traits not only related to heart disease but also associated with ancillary variables that will be contributed to dbGaP, including disease endpoints, risk factors, biomarkers, and subclinical disease measures. The phenotypes planned for investigation as part of the GO-ESP HeartGO project include early-onset myocardial infarction (EOMI), low density lipoprotein (LDL) cholesterol, body mass index/type 2 diabetes (BMI/T2D), blood pressure and ischemic stroke. Results of the proposed analyses as well as relevant replication/follow-up analyses will be reported in peer-reviewed journals. This study phs000398 contains the Atherosclerosis Risk in Communities (ARIC) subset of GO-ESP/Heart-GO. Additional GO-ESP data is also available via dbGaP.

  Study phs000398

• Genetic Factors associated with Conversion from Active Surveillance to Treatment for Prostate Cancer

  This is a genome-wide association study (GWAS) of conversion from active surveillance (AS) for prostate cancer (PC) to treatment. AS is the monitoring with screening tests and/or biopsies over time of men usually with low-risk, early-stage PC to avoid harmful side effects of PC treatment. "Conversion" refers to patients who withdraw from AS (switch to active treatment) due to changes in their cancer development, anxiety about delayed treatment, or other reasons. Patients who converted because of anxiety alone were censored in the GWAS analysis. The overall goal of this study is to develop an easily measurable, germline-based panel of genetic variants to aid in selecting PC patients appropriate for AS and/or the intensity of monitoring. In total, 6,324 PC patients from 28 collaborating institutions are included in this study. Patients are those with PC who are either on AS or who have previously converted from AS to treatment. In this study, 70% of all subjects were diagnosed with very low-risk, low-risk, or low-volume intermediate-risk PC (Kryvenko and Epstein, 2016; PMID: 26709152) and have been enrolled in an AS program. DNA was extracted from blood, saliva, or formalin-fixed, paraffin-embedded (FFPE) tissue collected from the study subjects at the participating sites. Genotyping, quality control processes, and imputation were performed at the Center for Inherited Disease Research (CIDR) at Johns Hopkins University. CIDR used the Illumina Infinium Multi-Ethnic Global Array (MEGA) version 1, which included genome-wide tag SNPs and 10,000 SNPs selected with custom content. Quality control and assurance (QC/QA) checks on genotyped data involved four domains: sample-level checks, batch effects, SNP-level checks, and preliminary association tests. Samples and SNPs passing the QC/QA checks were imputed to appropriate reference panels (HRC r1.1 for patients of European ancestry) using the Michigan Imputation Server (PMID: 27571263). Unmeasured genetic variants were imputed using the Trans-Omics for Precision Medicine (TOPMed) Imputation Server, with 97,256 reference samples and 308,107,085 SNPs. Variants with imputation quality (INFO) score < 0.3 were excluded, leaving a total of 22,691,641 SNPs successfully imputed. After QC steps, a total of 5,936 samples genotyped at CIDR remained for inclusion in the GWAS.

  Study phs002056

• National Heart Lung and Blood Institute (NHLBI) GO-ESP: Heart Cohorts Component of the Exome Sequencing Project (FHS)

  The NHLBI "Grand Opportunity" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the "exome") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. HeartGO is a consortium of six well-phenotyped NHLBI cohorts: Atherosclerosis Risk in Communities (ARIC) study, the Coronary Artery Risk Development in Young Adults (CARDIA) study, the Cardiovascular Health Study, the Framingham Heart Study, the Jackson Heart Study, and the Multi-Ethnic Study of Atherosclerosis. Together, these cohorts have provided DNA and phenotype datasets from a diverse cohort of individuals of African-American, Caucasian, Asian, and Hispanic ancestry to be made available for use by qualified investigators in dbGaP. HeartGO investigators will conduct genotype-phenotype analyses for phenotypes related not only to heart disease but with other variables that will be contributed to dbGaP. The HeartGO dataset provides investigators with genotype-phenotype analytic opportunities for traits not only related to heart disease but also associated with ancillary variables that will be contributed to dbGaP, including disease endpoints, risk factors, biomarkers, and subclinical disease measures. The phenotypes planned for investigation as part of the GO-ESP HeartGO project include early-onset myocardial infarction (EOMI), low density lipoprotein (LDL) cholesterol, body mass index/type 2 diabetes (BMI/T2D), blood pressure and ischemic stroke. Results of the proposed analyses as well as relevant replication/follow-up analyses will be reported in peer-reviewed journals. This study phs000401 contains the Framingham Heart Study (FHS) subset of GO-ESP/Heart-GO. Additional GO-ESP data is also available via dbGaP.

  Study phs000401

• Effect of Crohn's Disease Risk Alleles on Enteric Microbiota

  This UH2/UH3 demonstration project entitled "Effects of Crohn's disease risk alleles on enteric microbiota" is focused on characterizing intestinal associated microbiota in patients with ileal Crohn's disease (ileal CD), ulcerative colitis (UC) and control patients without inflammatory bowel diseases (non-IBD). We hypothesize that genetic factors that affect Paneth cell function, contribute to compositional changes in intestinal microbiota. These changes in microbiota may lead to reduction of protective commensal organisms and increased numbers of aggressive organisms that incite intestinal inflammation. This hypothesis is being tested by high throughput 16S rRNA sequence analysis of de-identified ileal and colonic tissues that have been archived at Washington University St. Louis, University of North Carolina, Mount Sinai Hospital and the Cleveland Clinic. Multivariate analysis of the metagenomic data will be conducted with genotyping metadata (highly reproducible CD risk alleles, including NOD2 and ATG16L1) and phenotyping metadata (e.g. age, gender, race, body mass index, medications and smoking.) Shotgun sequencing will be performed on selected fecal specimens linked to ileal tissues to identify additional, or auxiliary, or synergistic pathogenic factors or other functional changes in the microbiome. Because members of this research team have observed that a chronic viral infection is required for the Paneth cell defect in Atg16l1 hypomorphic mice, a major focus of these studies will be towards identifying potential viral triggers for the defective Paneth cell phenotype in individuals harboring the ATG16L1 risk allele. Novel genetic probes for protective and aggressive organisms will be developed by mining bacterial genome and shotgun sequencing data. Genomic sequences will be produced for candidate protective and aggressive strains (e.g. adherent-invasive strains of E. coli) isolated from human intestinal tissues where there is limited existing genome information. Quantitative qPCR assays using the novel as well as established genetic probes will be conducted to test the hypothesis that an imbalance between protective and aggressive organisms is associated with genetic factors that affect Paneth cell function. Our combined expertise in multiple disciplines across multiple institutions, our demonstrated ability to collect a large number of well-phenotyped samples with longitudinal clinical information that will be linked to host response and morphologic studies, and our consortium's capacity for high-throughput sequencing will be used to investigate how alterations in human microbiome relate to CD risk alleles and CD pathogenesis.

  Study phs000255

• National Heart Lung and Blood Institute (NHLBI) GO-ESP: Heart Cohorts Component of the Exome Sequencing Project (JHS)

  The NHLBI "Grand Opportunity" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the "exome") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. HeartGO is a consortium of six well-phenotyped NHLBI cohorts: Atherosclerosis Risk in Communities (ARIC) study, the Coronary Artery Risk Development in Young Adults (CARDIA) study, the Cardiovascular Health Study, the Framingham Heart Study, the Jackson Heart Study, and the Multi-Ethnic Study of Atherosclerosis. Together, these cohorts have provided DNA and phenotype datasets from a diverse cohort of individuals of African-American, Caucasian, Asian, and Hispanic ancestry to be made available for use by qualified investigators in dbGaP. HeartGO investigators will conduct genotype-phenotype analyses for phenotypes related not only to heart disease but with other variables that will be contributed to dbGaP. The HeartGO dataset provides investigators with genotype-phenotype analytic opportunities for traits not only related to heart disease but also associated with ancillary variables that will be contributed to dbGaP, including disease endpoints, risk factors, biomarkers, and subclinical disease measures. The phenotypes planned for investigation as part of the GO-ESP HeartGO project include early-onset myocardial infarction (EOMI), low density lipoprotein (LDL) cholesterol, body mass index/type 2 diabetes (BMI/T2D), blood pressure and ischemic stroke. Results of the proposed analyses as well as relevant replication/follow-up analyses will be reported in peer-reviewed journals. This study phs000402 contains the Jackson Heart Study (JHS) subset of GO-ESP/Heart-GO. Additional GO-ESP data is also available via dbGaP.

  Study phs000402

• National Heart Lung and Blood Institute (NHLBI) GO-ESP: Heart Cohorts Component of the Exome Sequencing Project (CHS)

  The NHLBI "Grand Opportunity" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the "exome") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. HeartGO is a consortium of six well-phenotyped NHLBI cohorts: Atherosclerosis Risk in Communities (ARIC) study, the Coronary Artery Risk Development in Young Adults (CARDIA) study, the Cardiovascular Health Study, the Framingham Heart Study, the Jackson Heart Study, and the Multi-Ethnic Study of Atherosclerosis. Together, these cohorts have provided DNA and phenotype datasets from a diverse cohort of individuals of African-American, Caucasian, Asian, and Hispanic ancestry to be made available for use by qualified investigators in dbGaP. HeartGO investigators will conduct genotype-phenotype analyses for phenotypes related not only to heart disease but with other variables that will be contributed to dbGaP. The HeartGO dataset provides investigators with genotype-phenotype analytic opportunities for traits not only related to heart disease but also associated with ancillary variables that will be contributed to dbGaP, including disease endpoints, risk factors, biomarkers, and subclinical disease measures. The phenotypes planned for investigation as part of the GO-ESP HeartGO project include early-onset myocardial infarction (EOMI), low density lipoprotein (LDL) cholesterol, body mass index/type 2 diabetes (BMI/T2D), blood pressure and ischemic stroke. Results of the proposed analyses as well as relevant replication/follow-up analyses will be reported in peer-reviewed journals. This study phs000400 contains the Cardiovascular Health Study (CHS) subset of GO-ESP/Heart-GO. Additional GO-ESP data is also available via dbGaP.

  Study phs000400

• Genetic Epidemiology of COPD (COPDGene) Funded by the National Heart, Lung, and Blood Institute

  Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of death in the United States and the only leading cause of death that is steadily increasing in frequency. This project will establish a racially diverse cohort that is sufficiently large and appropriately designed for genome-wide association analysis of COPD. A total of 10,000 subjects will be recruited, including control smokers, definite COPD cases (GOLD Stage 2 to 4), and subjects not included in either group (GOLD 1 or GOLD-Unclassified). This cohort will be used for cross-sectional analysis, although long-term longitudinal follow-up will be a future goal. The primary focus of the study will be genome-wide association analysis to identify the genetic risk factors that determine susceptibility for COPD and COPD-related phenotypes. Detailed phenotyping of both cases and controls, including chest CT scan assessment of emphysema and airway disease, will allow identification of genetic determinants for the heterogeneous components of the COPD syndrome. The hypotheses to be studied are: 1) Precise phenotypic characterization of COPD subjects using computed tomography, as well as clinical and physiological measures, will provide data that will enable the broad COPD syndrome to be decomposed into clinically significant subtypes. 2) Genome-wide association studies will identify genetic determinants for COPD susceptibility that will provide insight into clinically relevant COPD subtypes. 3) Distinct genetic determinants influence the development of emphysema and airway disease. The initial phase of genome-wide association analysis included 500 COPD cases and 500 control subjects (all non-Hispanic White) genotyped with the Illumina Omni-1 chip. The second phase genotyped the entire study cohort using the Illumina Omni-Express chip. Unique aspects of the study include: 1) Inclusion of large numbers of African American subjects (approximately 1/3 of the cohort); 2) Obtaining chest CT scans (including inspiratory and expiratory images); and 3) Inclusion of the full range of disease severity. The COPDGene_v6 Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the "Sub-studies" box located on the right hand side of this top-level study page phs000179 COPDGene_v6 Cohort. phs000296 ESP LungGO COPDGene phs000765 COPDGene_Geno

  Study phs000179

• Changes in Oral and Gut Microbiota and Incidence and Severity of Patient-Reported Symptoms in Pre- and Post-Kidney Transplant Patients

  This novel prospective cohort explores the relationships between oral and fecal microbiome features (alpha and beta diversity, differential relative abundances of bacterial taxa, and functional genes) and the incidence and severity of psychoneurological symptoms (e.g., pain, fatigue, depression, anxiety, and sleep disturbance) before and after patients receive a kidney transplant from a live donor. Thirty-five subjects provided fecal and saliva specimens for shotgun metagenomic sequencing of gut and oral microbiomes at 3 timepoints: 1) within 4 weeks prior to the transplant surgery (at end-stage kidney disease), 2) 1-3 weeks after the transplant surgery, and 3) at 3 months after the transplant (after restoration of kidney function). Subjects were enrolled between October, 2018, to November, 2021, and all study visits were completed by March, 2022. Data collected includes: Demographic (age, biological sex at birth, race/ethnicity, marital status); clinical data (body mass index, dialysis status, type of dialysis, high vs. low risk immune-suppression protocol, antibiotics during study period); laboratory data (serum creatinine; estimated glomerular filtration rate; serum blood urea nitrogen; immunosuppression trough levels), and outcome data (symptoms such as pain interference, pain intensity, fatigue, anxiety, depression, sleep disturbance, acute rejection, delayed graft failure, graft loss, post-transplant infections, and health-related quality of life). Incidence and severity of symptoms, including pain interference, pain intensity, fatigue, sleep dysfunction, and anxiety/depression-like symptoms, were measured using the Patient Reported Outcome Measurement Systems (PROMIS) 57 v2.1. Health related quality of life was assessed using the Kidney Disease Quality of Life Short Form (KDQOL-SF v1.3). The objective of this longitudinal study is to characterize changes in microbial features at baseline, before restoration of kidney function, and over time, after restoration of kidney function via kidney transplantation, and to identify relationships between microbiome features and transplant outcomes (rejection, infection, delayed graft function, graft failure), symptom burden, and health-related quality of life. Shotgun metagenomic sequencing of the oral and gut microbiomes will allow a higher-resolution examination of the gut microbiome compared to 16S rRNA gene amplicon sequencing, and will provide direct evidence of metabolic capabilities of the microbiota. This approach will allow us to explore the dynamic nature of symptom burden, and the effects of demographic and clinical variables on the oral and gut microbiomes before and after restoration of kidney function.

  Study phs002199

• Acute Respiratory Distress Network (ARDSNet) Studies 06 and 08 Prospective, Randomized, Multicenter Trial of Aerosolized Albuterol Versus Placebo for the Treatment of Acute Lung Injury (ALTA) (ARDSNet-ALTA-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. Biospecimens Access to Biospecimens is through the NHLBI Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). Biospecimens from ARDSNet-ALTA include Plasma, DNA, Urine, and BAL. Please note that use of biospecimens in genetic research is subject to a tiered consent. Objectives This clinical trial was designed to test the hypothesis that an aerosolized beta-2-agonist, albuterol, would improve clinical outcomes in participants with acute lung injury (ALI) and acute respiratory distress syndrome (ARDS). Background In participants with acute lung injury and acute respiratory distress syndrome (ALI/ARDS), inflammation of the pulmonary circulation increases vascular permeability. Fluid leaks from blood vessels into the pulmonary interstitium and alveoli. Recovery from this form of acute respiratory failure requires that the pulmonary edema resolve. The resolution of alveolar edema is driven by active transport of sodium and chloride ions from the luminal space across both type I and type II alveolar epithelial cells, creating an osmotic gradient for the reabsorption of water. In the ex vivo human lung, the rate of alveolar fluid clearance can be doubled by treatment with a cyclic AMP beta-2 adrenergic receptor agonist. On the basis of the preclinical observations that treatment with beta-2-agonists could reduce pulmonary edema and accelerate the rate of alveolar fluid clearance, the ALTA study was designed and undertaken with the hypothesis that treatment of participants with ALI/ARDS with beta-agonist therapy would accelerate the resolution of alveolar edema and improve clinical outcomes. Participants There were 282 participants. Design Study staff conducted a multicenter, randomized, placebo-controlled clinical trial in which participants were randomized to receive aerosolized albuterol (5 mg) or saline placebo every 4 hours for up to 10 days. The primary outcome variable for the trial was ventilator-free days. Conclusions Ventilator-free days were not significantly different between the albuterol and placebo groups. The results suggest that aerosolized albuterol does not improve clinical outcomes in participants with ALI. Routine use of beta-2 agonist therapy in mechanically ventilated participants with ALI cannot be recommended (Matthay, et al., 2011, PMID: 21562125).

  Study phs003743

• dbGaP Collection: Compilation of Individual-Level Genomic Data for General Research Use

  This dbGaP Collection contains all authorized individual-level genomic datasets currently in dbGaP that are approved for General Research Use (GRU) and have no further limitations beyond those outlined in the model Data Use Certification Agreement. Access to this study will include any additional authorized individual-level GRU datasets that become available. Renewal of this study is required annually. Data Included in this Study Individual-level genomic data designated for general research use with no further use limitations or restrictions, that is, Data use does not require approval by an Institutional Review Board for secondary analyses Data have no publication embargo Data have no other use limitations (e.g., requirement for collaboration or publication; restricted for use by academic or not-for-profit organizations; restricted to health, medical, and/or biomedical research) In response to requests from the scientific community, the NIH implemented a change in the procedures for accessing individual-level GRU genomic data. Under the modified procedures, interested investigators can request GRU individual-level genomic datasets with a single application. However, please note that these data have not been harmonized. Additionally, to help expedite the processing of requests for individual-level GRU genomic datasets, the requests will be reviewed by a single, central Data Access Committee. The process for requesting these datasets is identical to the request process for non-GRU individual-level, controlled-access data, such as the expectation that investigators will abide by the NIH Policy for Sharing of Data Obtained in NIH Supported or Conducted Genome-Wide Association Studies and Data Use Certification Agreement. Effective April 24, 2018, the Data Use Limitations (DUL) for the Genes and Blood Clotting Study (GABC) (phs000304) was updated to Health/Medical/Biomedical, Not-for-profit Use Only (HMB-NPU). Additionally, the submitting institutions have requested the removal of the National Heart, Lung, and Blood Institute (NHLBI) "Grand Opportunity" Exome Sequencing Project (GO-ESP) Lung Cohorts Exome Sequencing Project: Genetic modifiers of Pseudomonas aeruginosa (Pa) lung infection acquisition in cystic fibrosis (phs000254) from the dbGaP Compilation of Individual-Level Genomic Data for General Research Use (dbGaP Compilation) (phs000688). As such, data from studies phs000304 and phs000254 are no longer available as part of the dbGaP Compilation (phs000688). Investigators must submit separate Data Access Requests (DARs) for the two studies and be approved by the NHLBI Data Access Committee.

  Study phs000688

• Study of Clinical Efficacy of Antimicrobial Therapy Strategy Using Pragmatic Design in Idiopathic Pulmonary Fibrosis (CleanUP IPF-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 investigate whether the addition of antimicrobial treatments improves outcomes compared to usual care alone among patients with idiopathic pulmonary fibrosis. Background Idiopathic pulmonary fibrosis (IPF) is a chronic progressive lung disease. Lung dysbiosis, characterized by increased bacterial load and/or loss of diversity, has been reported in patients with IPF and may contribute to hospitalization and death. Clinical trials investigating other chronic disorders suggest that antimicrobial therapy favorably alters the lung microbial community. The CleanUP IPF study was initiated to determine if an antimicrobial treatment reduces respiratory hospitalization or death among patients with IPF. Participants A total of 513 participants were enrolled. 254 participants were randomized to receive antimicrobials, of those 128 were randomized to receive co-trimoxazole and 126 were randomized to receive doxycycline. 259 participants were randomized to receive usual care alone. Design CleanUP IPF was a randomized, unblinded, multicenter study. Patients were randomized to receive antimicrobials in addition to usual care or usual care alone. Antimicrobials included co-trimoxazole (trimethoprim 160 mg/sulfamethoxazole 800 mg twice daily plus folic acid 5 mg daily) or doxycycline (100 mg once daily if body weight Data collected included diffusion capacity of lungs for carbon monoxide (DLCO), forced vital capacity (FVC), and occurrence of severe adverse events. Several questionnaires were administered to assess quality of life, including the impacts of shortness of breath, fatigue, and chronic cough on participants. The primary end point was time to first nonelective respiratory hospitalization or all-cause mortality. The study was terminated early due to futility. Conclusions Among adults with idiopathic pulmonary fibrosis, the addition of co-trimoxazole or doxycycline to usual care, compared with usual care alone, did not significantly improve time to nonelective respiratory hospitalization or death. Martinez FJ, Yow E, Flaherty KR, et al. Effect of Antimicrobial Therapy on Respiratory Hospitalization or Death in Adults With Idiopathic Pulmonary Fibrosis: The CleanUP-IPF Randomized Clinical Trial. JAMA. 2021;325(18):1841-1851. doi:10.1001/jama.2021.4956

  Study phs004314

• Clinical outcomes in ctDNA-positive urothelial carcinoma patients treated with adjuvant immunotherapy

  Minimally invasive approaches to detect residual disease after surgery are urgently needed to select patients at highest risk for metastatic relapse for additional therapies. Circulating tumour DNA (ctDNA) holds promise as a biomarker for molecular residual disease (MRD) and relapse,1-3 but its clinical value has yet to be demonstrated in a randomised clinical trial. We evaluated outcomes in post-surgical ctDNA-positive (+) patients in a randomised phase III trial of adjuvant atezolizumab versus observation. IMvigor010 enrolled 809 patients with muscle-invasive urothelial carcinoma and did not meet its primary endpoint of disease-free survival (DFS) in the intent-to-treat population. Within the study, an exploratory planned analysis of prospectively collected plasma was performed, which tested the utility of ctDNA to identify patients who may benefit from adjuvant atezolizumab treatment. ctDNA was measured at the start of therapy (cycle 1 day 1; C1D1) and at week 6 (cycle 3 day 1; C3D1), and 581 patients were evaluable for ctDNA. The prevalence of ctDNA positivity at C1D1 was 37% (n=214), and ctDNA positivity identified patients with poor prognosis (observation arm DFS HR= 6.19 (4.29, 8.91), p<0.0001). Here we show that ctDNA(+) patients had improved DFS and overall survival (OS) with atezolizumab versus observation (DFS HR= 0.56 (0.41-0.77); p=0.0003 and OS HR= 0.58 (0.4-0.86); p=0.0063). No difference in DFS or OS between arms was noted for ctDNA-negative patients. The rate of ctDNA clearance was higher with atezolizumab (18%) versus observation (4%) (p=0.0041). Transcriptomic analysis revealed that tumours from ctDNA(+) patients had higher expression of cell cycle and keratin genes. Within the ctDNA(+) patient population in the atezolizumab arm, non-relapsing patients were further enriched in prominent immune response signatures including PD-L1, IFNG, CXCL9, and high tumour mutational burden, whereas relapse was associated with angiogenesis and fibroblast-transforming growth factor-beta signatures (F-TBRS). TCGA molecular subset analysis revealed increased efficacy of atezolizumab in patients with basal-squamous tumours, consistent with underlying tumour-immune contexture. Together these findings suggest that adjuvant atezolizumab may be associated with improved outcomes compared with observation in this high-risk ctDNA(+) population. These findings, if validated in other settings, would shift approaches to post-operative cancer care.

  Study EGAS00001004997

• Exceptional Outcomes in a Phase Ib Study Combining PARP and MEK Inhibition, With or Without Anti-PD-L1, for BRCA-Wildtype Platinum-Sensitive Recurrent Ovarian Cancer

  To evaluate regimens combining PARP and MEK inhibition, with or without PD-L1 inhibition, for BRCA-wildtype platinum-sensitive recurrent ovarian cancer (PSROC).

  Study EGAS00001007496

• MDACC Lymphoma & Myeloma WGS of Tumor and Non-tumor Cells in Multiple Myeloma

  FastQ files from paired tumor and non-tumor WGS data from patients diagnosed with newly diagnosed (n = 6), refractory/relapsed multiple myeloma (n = 3) or plasma cell leukemia (n = 1). These samples presented >95% tumor PCs in bone marrow aspirates. Plasma cells and T cells (non-tumor cells) were isolated from bone marrow aspirates using a magnetic approach.

  Dac EGAC50000000282

• Mutational Profile in Newly Diagnosed Diffuse Large B-Cell Lymphoma: Insights from the GAINED Study

  The GAINED study (NCT01659099) is a randomized phase 3 trial comparing obinutuzumab (G) to rituximab (R) in combination with ACVBP or CHOP14 induction, followed by PET-guided consolidation. This post-hoc analysis focuses on primary mediastinal B-cell lymphoma (PMBL) patients, confirmed through expert pathological review and characterized using gene-expression profiling (GEP) and Next-Generation Sequencing (NGS).

  Dac EGAC50000000540

• DAC for Cornell-NCI DLBCL NGS Genomic Project

  Genome-wide sequencing experiments were conducted on 103 DLBCL biopsy samples, of which the datasets (called Cornell-NCI DLBCL cohort) are available for authorized scientists. The Center of Technology Licensing at Cornell University is in charge of this data access policy and approval. Particularly, Cornell University will email a DAA to each requestor to have their institution sign before access is granted

  Dac EGAC50000000704

• BCL11B Enhancer Hijacking by t(14;16)(q32;q24) Translocation Defines a Novel High-Risk Subtype of T-ALL

  We performed integrated analysis of pediatric and adult T-ALL and mixed phenotype acute leukemias (MPALs) by whole-genome and whole-transcriptome sequencing.

  Study EGAS50000001254

• Whole-genome sequencing data of metastatic salivary gland cancer

  This dataset contains whole-genome sequencing data of three patients with metastatic salivary gland cancer who underwent autopsy to harvest tumor biopsies from spatially separated metastatic sites and biopsies from healthy skin as a control. Two patients had the subtype adenoid cystic carcinoma (patients 1 and 4) and one patient had the subtype myoepithelial carcinoma.

  Dataset EGAD50000002056

• DCIS_FF_RNAseq

  This RNAseq dataset contains full transcriptome data on n=77 pure DCIS samples. The RNA is derived from fresh-frozen DCIS samples, obtained from two hospital based cohorts (NKI cohort and Oslo cohort). The libraries were sequenced with 54 bp paired end reads using a Novaseq instrument (Illumina). We share fastq data files of paired end sequencing (two files per sample).

  Dataset EGAD50000002123

• Baseline epigenetic clock measures in the Northern Ireland Cohort for the Longitudinal Study of Ageing (NICOLA)

  Epigenetic clock measures for a subset of 1,870 participants within the NICOLA cohort. The following epigenetic clocks were generated: (±PC)PhenoAge, (±PC)GrimAge, (±PC)Horvath1, (±PC)Hannum, PCDNAmTL and DunedinPACE. +PC represents the use of the principal component adjusted version of the clock.

  Dataset EGAD50000002063

• Whole exome sequencing data of matched pairs of primary tumour and normal frozen tissue of seven osteosarcoma patients

  This dataset contains whole exome sequencing data of matched pairs of primary tumour and normal frozen tissue of seven osteosarcoma patients. Whole exome sequencing with a minimum coverage of 100x was performed using the Illumina Novaseq6000 platform and the Agilent SureSelect Human All Exon V7 kit.

  Dataset EGAD50000002264

• Single-cell whole-genome sequencing dataset of sorted CD3+, CD33+, and CD34+ cells from aplastic anemia

  This dataset contains raw single-cell whole-genome sequencing data generated from a single patient with aplastic anemia using the BioSkryb platform. Single cells were isolated based on surface marker expression (CD3+, CD33+, and CD34+) and subjected to whole-genome amplification followed by sequencing on an Illumina platform.

  Dataset EGAD50000002195

• Dataset for single cell transcriptome sequencing

  This datasets contains single cell transcriptome sequencing of 10 control samples. Sequencing has been performed on Illumina NovaSeq 6000 using 10xGenomics Chromium Next GEM Single Cell 5 Reagent Kits. Sequencing was always paired. This dataset additionally contains a .QS file from Seurat Analysis performed in R, generated as described in the related publication.

  Dataset EGAD50000001549

• WGS of Newly Diagnosed and Refractory/Relapsed Multiple Myeloma

  This dataset includes paired tumor and non-tumor WGS data from patients diagnosed with newly diagnosed (n = 6), refractory/relapsed multiple myeloma (n = 3) or plasma cell leukemia (n = 1). These samples presented >95% tumor PCs in bone marrow aspirates. Plasma cells and T cells (non-tumor cells) were isolated from bone marrow aspirates using a magnetic approach.

  Dataset EGAD50000001177

• TOTHER3 dataset

  This dataset contains the FASTQ and BAM files for TOTHER3 study. Targeted DNA-Seq experiment were realized with 49 samples. Since this data was obtained with a panel of genes protected by Intellectual Property (IP), these files only contain information to validate the results published and, in consequence, sensible data had to be specifically removed.

  Dataset EGAD50000000562

• Total RNA sequencing of fibroblasts from an control individual

  Total RNA sequencing of fibroblasts from an individual with 30-55x GCC repeats in the FMR1 5'UTR. Libraries were prepared with total RNA with Ribo-Zero ribosomal RNA depletion (illumina), and sequenced paired-end, 75bp on a NextSeq 550 system. This dataset contains three RNA-sequencing replicates from the same cell line.

  Dataset EGAD50000000922