12277 results for ""statistically+reactive"+taxa+in+microbial+community"

in 49.30 milliseconds.

• Analysis of the lung gene expression profile in COPD

  Samples obtained from patients with COPD and from controls by bronchoscopy from the lung were subjected to RNA seq.

  Study EGAS00001001472

• Therapeutic vulnerabilities in the DNA damage response for the treatment of ATRX mutant neuroblastoma

  Whole genome sequencing of ATRX / TP53 knockdown clones of the neuroblastoma cell line SK-N-SH

  Study EGAS00001004550

• Fine-Scale Genomic Analyses Of Admixed Individuals Reveal Unrecognized Genetic Ancestry Components In Argentina

  Study the sub-continental origins of African, European and Native American genetic ancestries of Argentinean populations.

  Study EGAS00001004492

• The mutational landscape of skin tumours in CYLD cutaneous syndrome

  This dataset contains genomic and transcriptomic profiling of skin samples (74) from patients with CYLD cutaneous syndrome

  Dataset EGAD00001005305

• The transcription factor GABP selectively binds and activates the mutant TERT promoter in cancer

  Dataset contains Exome-seq and RNA-seq from 2 GBM patients, as well as RNA-seq from the derived cultured cells (GNS).

  Dataset EGAD00001001359

• Exploring the extracellular transcriptome in seminal plasma for non-invasive prostate cancer diagnosis

  mRNA capture sequencing data of 57 seminal plasma samples.

  Dataset EGAD00001007688

• analysis of T cell receptor repertoirs

  Full information about the T cell receptor (CR) variable regions found in the sequences of the vdj region. Columns: barcode is_cell contig_id high_confidence length chain v_gene d_gene j_gene c_gene full_length productive cdr3 cdr3_nt reads umis raw_clonotype_id raw_consensus_id

  Dataset EGAD00001008109

• Dataset for synovial_sarcoma-WHOLE_GENOME

  Rare cancer sequencing data of 6 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008899

• Whole exome sequencing of trio with primary immunodeficiency (IL2RB)

  Whole exome paired-end sequencing data was performed on a trio (patient + parents) who has primary immunodeficiency to identify the genetic cause of the immunodeficiency. Analysis revealed a novel homozygous mutation in IL2RB.

  Dataset EGAD00001004963

• FFPE CPA Accreditation Study

  FFPE CPA accreditation of genome-scale sequencing in routinely collected formalin-fixed paraffin-embedded (FFPE) cancer specimens versus matched fresh-frozen samples using targeted pulldown capture prior to Illumina sequencing.

  Dataset EGAD00001000678

• RNA-Seq of human CD4 Treg cells

  This dataset maps gene expression regulation in human primary regulatory CD4+ T cells (Tregs). It includes whole transcriptome data for141 samples. The final quality filtered set included 123 individuals with RNA-seq data.

  Dataset EGAD00001004830

• PacBio sequence data

  PacBio sequencing data of HKCI-2, HKCI-C1, HKCI-C2, HKCI-C3, HKCI-4, HKCI-9, HKCI-11, HKCI-5A and MIHA. All the data (9 samples) were saved in pacbio hdf5 format.

  Dataset EGAD00001004475

• Biological and Therapeutic Implications of a Unique Subtype of NPM1 Mutated AML (RNAseq Data)

  This dataset contains 91 RNAseq paired reads, in fastq format. Samples were collected from fresh bone marrow and peripheral blood sample from AML patients.

  Dataset EGAD00001006669

• Triple Negative BC RNA Sequencing

  We propose to definitively characterise the somatic genetics of breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Dataset EGAD00001001339

• NASH RNA-seq data

  This dataset includes transcriptome sequencing of 17 paired NAFLD-HCC samples and adjacent normal tissues. All the experiments were performed on Illumina HiSeq 2000 platform with raw reads stored in fastq format.

  Dataset EGAD00001004326

• Mechanism of action and resistance to Trastuzumab Deruxtecan in patients with metastatic breast cancer: the DAISY trial

  198 exome sequencing samples

  Dataset EGAD00001009853

• Epilepsy related sudden death (2019-08-21)

  These samples include exome sequences of samples from patients who suffered Sudden Unexplained Death in Epilepsy. They all are of European descent. . This dataset contains all the data available for this study on 2019-08-21.

  Dataset EGAD00001005276

• HSP90 inhibitor resistant K562 cells

  K562 cell line has been treated with two different HSP90 inhibtors. After resistance clones emerged, they have been genetically characterized using WES in comparison to the parental K562 cell line.

  Dataset EGAD00001009051

• Chondromyxoid fibroma

  Chondromxoid fibroma is a benign tumour of bone with unknown underlying pathogenesis. To determine pathognomic genomic event in chondromyxoid fibroma whole genome sequencing will be undertaken to reconstruct rearrangements and find underlying mutations.

  Dataset EGAD00001001063

• CASCADE tumour transcriptome data

  RNA-Seq data from 20 fresh-frozen postmortem samples from three patients who participated in the CASCADE rapid autopsy program and died of metastatic castration resistant prostate cancer.

  Dataset EGAD00001009492

• Deep Sequencing of somatic cancer mutations

  We enriched a panel of cancer associated genes using the Custom Sure Select Target Enrichment Kit. Identified mutations were validated with deep sequencing in order to assess mutated allele frequencies more accurately.

  Dataset EGAD00001001313

• Single-cell colony targeted DNAseq

  Targeted DNA sequencing was applied to colonies grown from single-cells of patient A.6. The protocol followed is described in https://doi.org/10.1038/s41467-021-21650-1 and the methods of the manuscript

  Dataset EGAD00001010193

• Single-cell RNA-Seq (Chromium Next GEM Single Cell 3' Reagent Kits v3.1 from 10X Genomics )

  Human data for transcriptome (scRNA-Seq) in CD34+ B cell precursors.

  Dataset EGAD00001010907

• scRNA-seq

  This dataset gather scRNAseq data performed for MM.1S cell line in control and dex conditions at 4h and 24h

  Dataset EGAD00001011139

• RNA-seq dataset of CD34+ HSPCs from LRMDS patients

  To profile transcriptional alterations of HSPCs in LR-MDS patients, 7AAD−CD45+Lin-CD235a−CD34+ cells were isolated from healthy donors and LR-MDS patients for RNA sequencing.

  Dataset EGAD00001015771

• Aggressive genomic features in clinically indolent primary HHV8-negative effusion-based lymphoma

  Genomic profiling of effusion-based fluid samples from 8 HHV8-negative effusion-based lymphoma patients.

  Dataset EGAD00001008364

• Stability of kidney organoids in culture

  A whole genome mutation analysis of cortical kidney tissue, an early passage kidney organoid culture derived from the kidney tissue sample, and a late passage of the same organoid culture.

  Dataset EGAD00001003805

• NGS based viability screening using haploid cell line

  Identification of human deubiquitylating enzymes whose knock out result in hypersensitivity to DNA damaging agents, by comparing the sequence reads of 'barcode region' from mixed cell culture.

  Dataset EGAD00001001428

• Target capture sequence for Primary-recurrent HCC study

  This dataset contains target capture sequence data from 255 samples, including 154 tumors and 101 normal samples. All the experiments were performed on Illumina HiSeq 2000 platform with raw reads stored in fastq format.

  Dataset EGAD00001005450

• sWGS for genome-wide copy number profiling

  Shallow whole-genome sequencing (sWGS) data for the identification of somatic copy number alterations (SCNA) and the estimation of tumor fractions in plasma DNA of metastatic colorectal cancer patients (mCRC).

  Dataset EGAD00001006384

• Transcriptome profiling of desmoplastic small round cell tumors (DSRCTs)

  RNA sequencing of frozen resected specimens of desmoplastic small round cell tumors (DSRCTs). Four patients have specimens from multiple tissue sites included in this dataset.

  Dataset EGAD00001006388

• Genomic Architecture of Progression and Treatment Response in AMD

  Numerous studies have identified common and rare genetic variation associated with risk of advanced age-related macular degeneration (AMD). However, risk is just one facet of AMD disease architecture. Both disease progression and response to treatment are two critical elements that may also be influenced by genetic variation. The primary aim of this study was to identify genetic variation influencing progression and response to treatment for AMD, with a secondary aim of further elucidating the genetic etiology of AMD risk. We ascertained AMD cases and controls of European ancestry from Vanderbilt Eye Institute (VEI) and the Bascom Palmer Eye Institute (BPEI) and obtained blood samples from all participants. Eyes were examined using standard ophthalmological methods, and graded according the modified Age-Related Eye Disease Study scale (AREDS grades 1-5) using fundus photography. Individuals were re-examined in follow-up exams at regular intervals to assess any change in AMD grade. Eyes with advanced neovascular AMD that were examined using ocular coherence tomography imaging (OCT), treated with anti-angiogenesis therapy and monitored for response to treatment. All individuals ascertained for the study were exome-chipped for genome-wide single nucleotide variation coverage. To target rare genetic variation, whole exome sequencing was performed on individuals at the phenotypic extremes based on 1) AMD grade, 2) rate of progression from intermediate to advanced AMD and 3) response to anti-VEGF treatment for eyes with advanced neovascular AMD.

  Study phs001046

• The Chromatin Landscape of Pathogenic Transcriptional Cell States in Rheumatoid Arthritis

  In this study, we characterized 24 rheumatoid arthritis (RA) synovial tissue chromatin classes (i.e., cell states defined by chromatin accessibility) across 5 cell types (T, B/plasma, myeloid, stromal, and endothelial). We also investigated the transcription factors that may regulate these chromatin classes, their connections to transcriptional cell states in a proposed superstate model, and their interplay with RA pathology through associations with histological parameters and risk variants.As part of the Accelerating Medicines Partnership (AMP) network, we obtained 18 synovial tissue samples from 14 RA and 4 osteoarthritis (OA) patients for this study. Samples were collected from 7 clinical sites. We performed a 10x single cell ATAC-seq experiment on each sample.We further collected synovial tissue samples from 11 RA patients and 1 OA patient from 2 clinical sites; each sample was used for a 10x single cell multimodal ATAC and Gene Expression experiment.For additional support of the proposed superstate model, we also collected peripheral blood mononuclear cells (PBMCs) from 4 RA patients, sorted for 4 populations (CD4+CD127-CD25hi Tregs, CD4+CD127-CD25int Tregs, CD4+CD25-PD1+CXCR5- TPH, CD4+CD25-PD1+CXCR5+ TFH), tagged each population with a hashing antibody, and pooled populations for one multimodal sequencing run.The FASTQ files are available for controlled access via dbGaP. Additional data can be found on Synapse.The presence of pooled subjects inflates the automatically-generated subject count; the actual consented subject count for this data is 34.

  Study phs003417

• RNA Transcriptomic and DNA Methylation Landscape in FTLD-TDP and Controls

  Frontotemporal lobar degeneration (FTLD) is one of the leading causes of dementia in individuals younger than 65 years, with the aggregation of TDP-43 as one of the most common forms of FTLD. FTLD-TDP is clinically, genetically and pathologically heterogeneous, with GRN and C9orf72 as the most common genetic forms (although more than 50% of the cases are genetically unexplained), and A, B and C as the most common pathological subtypes. To investigate the molecular differences between the different forms of FTLD-TDP, we performed bulk RNA sequencing (RNAseq) and reduced representation bisulfite sequencing (RRBS) from different brain regions of FTLD-TDP patients and controls. The RNAseq dataset includes samples from the frontal cortex of 149 individuals, comprising 127 FTLD-TDP cases (genetically unexplained types A (27), B (20) and C (22), 24 GRN mutation carriers, and 34 C9orf72 expansion carriers) and 22 controls. The RRBS dataset includes samples from the frontal cortex of 158 individuals —119 FTLD-TDP cases (genetically unexplained types A (25), B (24), and C (25), 20 GRN mutation carriers, and 25 C9orf72 expansion carriers) and 39 controls; and from the cerebellum of 151 individuals —113 FTLD-TDP cases (genetically unexplained types A (24), B (21), and C (23), 20 GRN mutation carriers, and 25 C9orf72 expansion carriers) and 38 controls. In total, the study consists of data from 183 unique individuals, with some overlap across the different datasets.

  Study phs004075

• Space Associated Stem Cell Hallmarks of Aging in Astronauts

  This study examined the effects of the stress of space, specifically low earth orbit, on hematopoietic stem and progenitor cells (HSPCs) that maintain lifelong hematopoiesis and immune responses. Enriched CD34+ HSPCs were derived from 7 astronauts before, during and after 10 and 21-day ISS missions on the International Space Station. The samples were used as input to whole transcriptome sequencing by bulk RNA-Seq performed at The Scripps Research Institute Next Generation Sequencing Core on Illumina NextSeq 2000 sequencer and single cell RNA-Seq performed at The Salk Institute for Biological Studies on Illumina NovaSeq X Plus sequencer. Subsequent expression, RNA editing, and retrotransposon analyses were performed to assess HSPC and immune subpopulation survival dynamics. Overall, these analyses revealed space-associated stem cell hallmarks of aging (SASHA), including spaceflight dependent alterations in HSPC survival and self-renewal, ADAR1, telomere maintenance, mobilization and cell cycle gene expression, combined with space-induced clonal hematopoietic mutations, APOBEC3C activation and retrotransposon deregulation to warrant countermeasure development to enable long-duration spaceflight. Post-spaceflight analysis revealed increased C-to-T and clonal hematopoiesis-associated mutations, repetitive element and base deaminase deregulation, decreased telomere maintenance gene expression, and decreased self-renewal capacity compared to ground controls. These results demonstrate the space-associated aging effects in HSPCs after month-long exposure to LEO, providing insights into utilizing the LEO environment to model space-accelerated aging and other age-related malignancies.

  Study phs004267

• Identification of RNA biomarkers in Parkinson's disease patients

  Parkinson?s disease (PD) is an age-related, chronic and progressive neurodegenerative disorder characterized by a loss of dopaminergic neurons and subsequent motor symptoms. These overt motor symptoms are often preceded by prodromal non-motor symptoms. Though a number of genetic and environmental factors have been identified to play a role in PD, more exact methods for both diagnosing and assessing prognosis are yet to be discovered. By analyzing the transcriptome of early-stage PD patients, this study aims to identify genes (including important non-coding RNAs) and pathways altered at disease onset that may be used as novel biomarkers for PD diagnosis as well as potential new drug targets. The study consists of three main sources of data: first year blood transcriptomes, second year blood transcriptome and matched neural stem cell (NSC)/neuron transcriptomes. All transcriptome libraries were synthesized and sequenced using no-amplification non-tagging cap analysis of gene expression (nAnT-iCAGE) on the Illumina HiSeq 2500 platform. Resulting data was mapped to the human genome annotation (hg38), processed CAGE tags were clustered ready for differential expression analyses. First year blood sequencing consisted of 22 PD patients and 10 healthy controls across four lanes. In the second year, a further four lanes were sequenced containing 17 PD patients (12 patients from the first year and 5 new patients) along with 10 healthy controls and 5 first year blood samples matching the new second year patients.

  Study JGAS000119

• Genomic Alterations in Gingivo-buccal Cancer: ICGC-India Project_YR01

  As a part of the ICGC, India has undertaken genomic studies on gingivobuccal cancer of the oral cavity, which is the most prevalent form of cancer among men in India. There are various known environmental (life-style) correlates of this cancer, the most important of which are tobacco chewing and HPV infection. Paired DNA samples – isolated from the tumor tissue and from the blood of fifty patients – have been analyzed to catalog germline and somatic mutations. Association between each observed genomic alteration and exposure to environmental risk factors is being explored.Detailed clinical characterization of the patients, collection of data on demographic and environmental exposures, and isolation of DNA samples from blood and tumor tissues collected from each patient are being done at the Advanced Centre for Research, Treatment and Education on Cancer, Mumbai. Exome capture and deep resequencing are being performed at the National Institute of Biomedical Genomics, Kalyani. We have analyzed the exomes of paired blood and tumor DNA samples using two orthogonal platforms – exome capture by Roche-Nimblegen SeqCap Ez kit followed by sequencing on Roche-454 GS FLX, and exome capture by Illumina TrueSeq Exome Enrichment kit followed by sequencing on Illumina HiSeq-2000. Each exome is being sequenced at a mean depth of 30x. In addition, we have used Illumina Omni Quad SNP-chips to generate genotype data at 1.14 million genomic markers. The average concordance between SNP-chip and sequence data is 99.8%.

  Study EGAS00001000249

• Probabilistic cell type assignment of single-cell transcriptomic data reveals spatiotemporal microenvironment dynamics in human cancers

  Single-cell RNA sequencing (scRNA-seq) has transformed biomedical research, enabling decomposition of complex tissues into disaggregated, functionally distinct cell types. For many applications, investigators wish to identify cell types with known marker genes. Typically, such cell type assignments are performed through unsupervised clustering followed by manual annotation based on these marker genes, or via "mapping" procedures to existing data. However, the manual interpretation required in the former case scales poorly to large datasets, which are also often prone to batch effects, while existing data for purified cell types must be available for the latter. Furthermore, unsupervised clustering can be error-prone, leading to under- and over- clustering of the cell types of interest. To overcome these issues we present CellAssign, a probabilistic model that leverages prior knowledge of cell type marker genes to annotate scRNA-seq data into pre-defined and de novo cell types. CellAssign automates the process of assigning cells in a highly scalable manner across large datasets while simultaneously controlling for batch and patient effects. We demonstrate the analytical advantages of CellAssign through extensive simulations and exemplify real-world utility to profile the spatial dynamics of high-grade serous ovarian cancer and the temporal dynamics of follicular lymphoma. Our analysis reveals subclonal malignant phenotypes and points towards an evolutionary interplay between immune and cancer cell populations with cancer cells escaping immune recognition.

  Study EGAS00001003452

• COIN_CRC_GWAS

  Genotype data of 1,950 individuals from the COIN and COIN-B trials of advanced/metastatic colorectal cancer. Data provided in plink format, and has been quality controlled. Control data used was from the WTCCC2 project National Blood Donors (NBS) Cohort (EGAD00000000024).

  Dataset EGAD00010002186

• Single-cell somatic copy number variants in brain using different amplification methods and reference genomes

  This dataset contains 224 paired fastq files (112 single cells) from the following samples: brains from two Multiple System Atrophy patients and one control, and non-brain controls (fibroblasts, NA12878)

  Dataset EGAD50000000030

• Sensitive circulating tumor DNA based residual disease detection in epithelial ovarian cancer

  We analyzed 264 plasma samples collected between June 2016 and September 2021 from 63 epithelial ovarian cancer patients using tumor-guided plasma cell-free DNA analysis to detect residual disease after treatment.

  Dataset EGAD50000000360

• CHIC_TPO3_2023

  Human engineered CRC organoids (APC KO; KRAS G12D; TP53 KO) were grown in glucose, lactate or with DCA. Samples were collected 7 hours after the treatments and processed for bulk CHIC-seq.

  Dataset EGAD50000000090

• MDS PacBio LRTS IsoSeq

  This dataset contains long read transcriptome sequencing of 25 myelodysplastic sndrome (MDS) patients with or without mutation in SF3B1. The BAM files are unaligned CCS reads.

  Dataset EGAD50000000077

• Exome sequencing in HIV+ Viremic Non-Progressors (VNPs) and HIV+ Progressors

  This dataset contains 184 paired fastq files sequences with Illumina NovaSeq600 from 38 participants. Relevant clinical and demographical data is also included.

  Dataset EGAD50000000111

• Shallow dataset

  Associated with Molecular biomarkers in progression from refractory celiac disease to the lethal cancer variety enteropathy associated T cell lymphoma (EATL) Study. shallow Whole Genome Sequencing (sWGS) of 63 samples. sWGS was done to analyze copy number aberration.

  Dataset EGAD50000001165

• Targeted and shallow whole genome sequencing identifies therapeutic opportunities in p53abn endometrial cancers

  Targeted panel sequencing of 188 formalin-fixed paraffin-embedded p53abn endometrial cancer samples.

  Dataset EGAD00001015349

• Reference DNA standards for GCLP pipeline

  The use of reference DNA standards generated from cancer cell lines sequenced in the Cancer Genome Project to establish the sensitivity, specificity, accuracy and reproducibility of the WTSI GCLP sequencing pipeline

  Dataset EGAD00001002015

• sWGS of RCC patients

  Paired end shallow whole genome sequencing (sWGS) data for the identification of somatic copy number alterations (SCNA) and the estimation of tumor fractions in plasma DNA of renal cell carcinoma (RCC) patients (MonRec Cohort)

  Dataset EGAD00001005804

• Genomic variant calling of 32 Chinese SRCCs

  Whole Genome Sequencing has been applied in 32 SRCC patients and the raw data have been subjected to standard procedures. Files with genomic variant calling were obtain at the last step.

  Dataset EGAD00001004045

• Lowpass whole genome sequencing of single circulating tumor cells (CTCs) in ALK-rearranged non-small-cell lung cancer resistant to ALK inhibitors

  Lowpass whole genome sequencing of 43 single CTCs and one tumor biopsy

  Dataset EGAD00001007700

• subset of RNA-Seq data from umbrella study EGAS00001004338, used in EGAS00001004786

  linking 55 samples/74 RNA-Seq runs - out of EGAS00001004338 Umbrella study to EGAS0001004786

  Dataset EGAD00001006615

• DKFZ-St.Jude Medulloblastoma - 6 TB control exomes

  6 control exomes, TB cohort, sequenced on Illumina machines from the paper "Germline Elongator mutations in Sonic Hedgehog medulloblastoma" (Waszak et al. 2020 Nature).

  Dataset EGAD00001006664

• Characterization of a novel MEF2D-BCL9 fusion positive acute lymphoblastic leukemia cell line RNA-Seq

  A novel in-house-made pediatric MEF2D-BCL9 fusion positive acute lymphoblastic leukemia cell line was characterized

  Dataset EGAD00001009759

• scTCR analysis of CD8 T-cells from blood, fat, liver and skin

  CD8 Tcells were FACS sorted and processed with 10x Genomics Chromium Next GEM SingleCell V(D)J Reagents Kits v1.1 sequencing. In total 6 samples were processed. Fastq files are supplied.

  Dataset EGAD00001010005

• mRNA capture sequencing and RT-qPCR for the detection of pathognomonic, novel and secondary fusion transcripts in formalin-fixed paraffin-embedded tissue: a sarcoma showcase

  mRNA capture sequencing data (FASTQ files) of 28 FFPE sarcoma tumors

  Dataset EGAD00001007696

• Whole-exome sequencing and microRNA profiling predicted relapse risk of stage I lung adenocarcinomas

  This dataset contains BAM files for RNA-sequencing of stage I lung adenocarcinomas from Asian patients. In total, there are 107 patients and 107 tumor samples.

  Dataset EGAD00001006187

• Dataset for cancer_of_unknown_primary-WHOLE_GENOME

  Rare cancer sequencing data of 46 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008869

• Small variant calling for 110 Egyptian individuals

  This data set comprises WGS small variants and structural variants called in a cohort of 110 Egyptian individuals (10 individuals have been sequenced as part of this study and 100 are from EGAD00001001372/EGAD00001001380).

  Dataset EGAD00001006039

• Whole genome sequencing (bam files) of 5 samples of myxofibrosarcoma and 5 matched pairs

  Myxofibrosarcoma (MFS) is a rare subtype of sarcomas in the elderly, whose genetic basis is poorly understood. To elucidate it, the whole genome sequence was performed.

  Dataset EGAD00001007825

• Utility of ctDNA to support patient selection for early phase clinical trials: The TARGET Study

  The TARGET Study consists of 200 BAM files, for the 100 patients discussed in the publication. Each patient has a normal control BAM file and a ctDNA BAM file.

  Dataset EGAD00001004796

• Whole genome shotgun sequencing and somatic mutations data in Hepatocellular carcinoma

  There are 88 paired samples from HCC patients including tumors and matched adjacent normal tissues which were sequencing by Illumina HiSeq 2000 platform.

  Dataset EGAD00001003760

• Next Generation Sequencing in an IBD Pedigree Exome Data

  We perform whole exome sequencing on samples from a large IBD pedigree. The selected samples are from more distantly related family members (healthy and with IBD) and a set of matched population (Ashkenazy Jewish ancestry) samples.

  Dataset EGAD00001000422

• Triple Negative Breast Cancer RNA Sequencing

  We propose to definitively characterise the somatic genetics of triple negative breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Dataset EGAD00001000390

• Hi-C for Junvenile Pilocytic Astrocytomas

  5 Hi-C datasets (4 JPA and 1 LGG). Hi-C data for the remaining 5 JPAs used in our paper as well as all controls have been uploaded to EGA under EGAS00001005476.

  Dataset EGAD00001009044

• Pediatric high grade glioma WES

  We performed whole exome sequencing in DIPG and hemispheric HGG.

  Dataset EGAD00001008279

• Independent development of lymphoid and histiocytic malignancies from a shared early precursor

  Whole Exome Sequencing data from the germline of the patient as well as the tumors in bone marrow (T-ALL), Liver (Histiocytic Sarcoma) and ileum (non-Langerhans Cell Histiocytosis).

  Dataset EGAD00001001596

• RNA-seq

  Stranded RNA-seq libraries were performed for 150 ng of mRNA using the TruSeq library kit (Illumina, San Diego, CA, USA). Libraries were sequenced on a NextSeq 2000 (Illumina) in a 2x50bp length.

  Dataset EGAD00001010841

• BIOCLOCK Phenotype Information Dataset

  This dataset contains phenotypic metadata from participants in the BIOCLOCK endurance exercise intervention and epigenetic aging study. It includes intervention status, cardiorespiratory fitness (VO2 max), body composition, estimated leukocyte proportions, and other relevant traits linked to epigenetic aging outcomes.

  Dataset EGAD00001015799

• m6A profiling in Lung Adenocarcinoma

  Applying a refined m6A RNA immunoprecipitation method, we profiled the m6A epitranscriptome on 10 non-neoplastic lung (NL) tissues and 53 lung adenocarcinoma tumors.

  Dataset EGAD00001008026

• MP-WGS and WES from CCND1-negative MCL

  BAM files from 5 CCND1-negative MCL cases. 4 BAM files corresponded to long insert size Mate Pair-WGS and 3 to WES. In 2 of the cases both technologies were performed.

  Dataset EGAD00001004161

• sWGS of tumor samples for HGSOC copy-number signatures study

  This dataset contains 319 bam files of shallow WGS data (0.1X) aligned to human genome assembly GRCh37 (hg19) from 300 tumor samples sequenced on HiSeq2500 in SE-50bp mode.

  Dataset EGAD00001004174

• ChIP-seq and Hodgkin lymphoma

  ChIP-seq data (H3K4Me3, H3K27Ac histone modifications) of Hodgkin lymphoma cell line L-428. Samples were processed as previously described (Sud et al., 2018). The files are in bam format, aligned to build 37 of the human genome.

  Dataset EGAD00001004322

• Next Generation Children Project

  Whole genome sequencing of sick children in neonatal and paediatric intensive care units. Datasets EGAD00001007780 (GRCh37) and EGAD00001007868 (GRCh38) are extentions of this dataset.

  Dataset EGAD00001004357

• Ewing's Sarcoma Whole Genome Sequencing

  54 WGS Ewing's sarcoma samples sequenced at The Hospital for Sick Children Toronto (Adam Shlien's lab) and published on Science 2018. Reference Anderson et al. "Rearrangement bursts generate canonical gene fusions in bone and soft tissue tumors"

  Dataset EGAD00001004589

• Her2 BC WGS dataset

  We propose to definitively characterise the somatic genetics of breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Dataset EGAD00001001334

• African evolutionary history inferred from whole genome sequence data of 44 indigenous African populations

  Whole genome sequencing of 92 individuals from 44 African indigenous populations. Sequences made with Illumina HiSeq 2000 sequencing system; data uploaded in BAM format.

  Dataset EGAD00001005019

• Whole genome sequencing of cfDNA

  random whole-genome shotgun sequencing of cfDNA in control samples (NPH*) and late-stage cancer samples. First letter denotes primary cancer tissue (C: Colon, B: Breast, P: Prostate)

  Dataset EGAD00001005343

• Whole genome sequence of Primary-recurrent HCC study

  This dataset contains whole genome sequence data from 24 samples, including 16 tumors and 8 normal samples. All the experiments were performed on Illumina HiSeq 2000 platform with raw reads stored in fastq format.

  Dataset EGAD00001005451

• PFA ependymoma study -RNA-seq data

  RNA-seq fastq files for the 16 samples used in Michealraj et al. Cell 2020. The samples include PFA and ST ependymoma tissues, normal pediatric brain as control and PFA ependymoma lines.

  Dataset EGAD00001006046

• RNA sequencing of osteoarthritis patients in subchondral bone

  This dataset contains RNA-seq (Illumina Hiseq 4000) from macroscopically preserved and lesioned OA subchondral bone of patients that underwent joint replacement surgery due to OA (N=48).

  Dataset EGAD00001006197

• Biological and Therapeutic Implications of a Unique Subtype of NPM1 Mutated AML (ATACseq Data)

  This dataset contains 18 ATACseq reads, in fastq format. Samples were collected from fresh bone marrow and peripheral blood sample from AML patients.

  Dataset EGAD00001006670

• Segmental Cherry Angioma case

  Cherry angiomas are common benign blood vessel growths on the skin. In this study we characterise mutational profile of a cherry angioma and adjacent skin biopsied from a patient with multiple lesions with segmental presentation.

  Dataset EGAD00001015641

• DNA Double Strand Breaks in KMT2A-Rearranged AML patients

  DNA breakage at specific rearrangement-participating genes, which are more sensitive to a range of environmental and chemotherapeutic agents than other regions of the human genome, contributes to the generation of leukemia-causing rearrangements, and can be used as a predictor of susceptibility to cancer caused by gene rearrangements. As a direct proof-of-principle regarding the feasibility of employing fragile site breakage to identify and monitor high-risk populations to allow personalized treatments, genome-wide DNA break mapping/sequencing was used to determine whether preferential DNA breaks are generated at the major breakpoint regions of KMT2A in AML remission patients with previously diagnosed KMT2A rearrangement. We are submitting break mapping data from three patients with KMT2A rearrangements and three non-fusion patients, with and without etoposide treatments.

  Study phs002804

• GWAS in an Amerindian Ancestry Population Reveals Novel Systemic Lupus Erythematosus Risk Loci and the Role of European Admixture

  The study comprises SLE patients recruited from specialist rheumatology clinics from the United States, Mexico, Argentina, Chile and Peru. Two strategies were used to enrich samples for Native American ancestry: a. previously genotyped Hispanic and Latin American and US Native American individuals were selected according to their ancestry based on 253 ancestry informative markers as part of the Lupus Large Association 2 Study. The approximate 35% of the samples were primarily of European and Native American admixture was selected; b. the recruitment of patients took place primarily in countries with little African admixture. All samples were genotyped on the HumanOmni1-Quad BeadChip using manifest H at the Oklahoma Medical Research Foundation. The Illumina clustering algorithm with GenomeStudio v2011.1 was used.

  Study phs001025

• Multimodal Mapping of the Immune Landscape in Human Pancreatic Cancer

  Pancreatic ductal adenocarcinoma (PDA) is characterized by an immune-suppressive tumor microenvironment that has rendered it largely refractory to immunotherapy. We used single-cell RNA sequencing on patient tumors and matched blood, and we uncovered a previously unappreciated, complex environment of immune-suppressive cellular interactions. These experiments reveal immune checkpoint expression heterogeneity on individual patient T cells, with corresponding ligands on neoplastic and myeloid cells. TIGIT was upregulated on tumor infiltrating CD8+ T cells and was the only checkpoint receptor consistently expressed by exhausted CD8+ T cells. Clinical annotation of the samples revealed that the exhausted signature is most prominent in patients with advanced stages of disease. Our findings suggest individualized combination therapy, involving anti-TIGIT therapies, may be necessary to extend the benefits of immunotherapy to pancreatic cancer patients.

  Study phs002071

• Transcriptomics of Liver and PBMCs in Alcohol-Associated Liver Disease

  This study was designed to characterize the transcriptome of alcohol-associated hepatitis using RNA sequencing (RNA-seq) technology for both liver tissue biopsies and peripheral blood mononuclear cells (PBMCs) extracted from blood samples, in order to identify expressed genes that are markers of the disease. To distinguish genes that differentiate alcohol-associated hepatitis from other inflammatory liver diseases, we compared the RNA-seq data generated from participants with alcohol-associated hepatitis, alcohol-associated cirrhosis, chronic hepatitis C infection, non-alcohol-associated fatty liver disease, and healthy controls. We utilized computational approaches to demonstrate that gene expression data generated from either liver tissue or blood samples can be used to identify a small set of gene biomarkers to distinguish between these liver diseases. The raw RNA-seq data will be available through dbGaP.

  Study phs003112

• Somatic Mutations in Epilepsy: Whole Genome Sequence Analysis of Single Neurons

  Low-coverage whole-genome sequencing was performed on single-cells from resected brain tissues obtained from an individual with hemimegalencephaly (HMG) along with a somatic copy number variant (sCNV) of chromosome 1q in order to characterize the sCNV at the single cell level. Single neuronal nuclei and non-neuronal nuclei were isolated by fluorescence-activated cell sorting (FACS) using NeuN immunoreactivity to identify neurons. 46 neurons and 30 non-neuronal cells, as well as a batch of 10 and a batch of 100 cells from each group, were genome amplified using multiple displacement amplification (MDA) and sequenced on an Illumina HiSeq 2000 sequencer. Thirty-two samples were multiplexed into each HiSeq lane for single-end 50 bp runs, obtaining ~5 million pass-filter reads per sample.

  Study phs002615

• Single-Cell Sequencing Reveals Distinct Microenvironment Cell Types Associated with Response to High Dose Melphalan and Autologous Stem Cell Transplant in Multiple Myeloma

  The aim of this study is to understand the transcriptome of microenvironment cells in pre- and post- autologous stem cell transplantation (ASCT) samples between patients with complete response and partial response to transplant. Here, we studied immune cells from 40 multiple myeloma patients who have undergone ASCT. Samples were collected from 40 multiple myeloma patients before and after ASCT. Samples were sorted using magnetic activated cell sorting (MACS) and the non-tumor CD138- fraction underwent 3' single cell RNA-sequencing (scRNA-seq) or 5' scRNA-seq + 5' T cell receptor sequencing (TCRseq), to determine the scRNA transcriptome and TCR repertoire. This study includes 24 samples with 3' scRNA-seq, 56 samples with 5' scRNA-seq, and 56 samples with 5' TCRseq data.

  Study phs003219

• Nala TAS-LRS PGx Study

  Sequencing was performed on the PromethION Flow Cell R10 (M version) using the P2 Solo Sequencer (MinION release 24.02.16). The library was divided into three portions and loaded in a tapered manner across three time points. At the first time point, the initial portion of the library was loaded, and sequencing began in whole-genome mode (without adaptive sampling), to monitor QC (N50 within the expected range). After one hour, adaptive sampling was activated. A custom BED file was used to define the target regions (N=326). Each region was extended by 20 kb upstream and downstream, and overlapping regions were merged into non-redundant intervals using bedtools43, covering a total of 1.3% of the human genome. At the second time point (20–24 hours after sequencing began, or when fewer than 2000 pores remained active), the flow cell was washed following ONT’s Flow Cell Wash Kit protocol, and the second portion of the library was loaded. At the third time point (40–48 hours), the second portion of the library was retrieved, and merged with the third portion. The flow cell was washed and reloaded with the mixed library. POD5 files were basecalled using Dorado v0.8.1 in super-accuracy (SUP) mode with the dna_r10.4.1_e8.2_400bps_SUP@v5.0.0. Reads from the initial 1 h Whole Genome Sequencing (WGS) and subsequent 72 h adaptive sampling were filtered for Q-scores >10. Passing reads were demultiplexed using Dorado’s demux function, then combined per sample and mapped to the GRCh38 reference genome using Minimap2 v2.22. Files were converted to CRAM using samtools.

  Dataset EGAD50000001609

• ECM-free patient-derived organoids preserve diverse prostate cancer lineages and uncover in vitro-enriched cell types

  Patient-derived organoids (PDOs) hold promise for modeling various cancers, yet their application in prostate cancer (PCa) has been limited due to low culture success and the predominance of non-tumor-like cells. Using 164 PCa samples and optimizing culture conditions, we demonstrate that an extracellular matrix (ECM)-free culture method improves PDO take-rates, fostering cell populations with luminal and PCa-specific characteristics. Single-cell RNA sequencing (scRNA-seq) reveals that these ECM-free PDOs closely mirror their original tumors at the transcriptomic level and maintain a diverse array of tumor cell types, unlike traditional Matrigel-based cultures which predominantly yield benign-like cells. This study introduces a PCa PDO single-cell atlas, providing a valuable resource for advancing prostate cancer research.

  Study EGAS50000000807

• A collection of 142 samples used to evaluate the sensitivity and specificity of small-scale variation detection in exome-capture data with a particular focus on indel detection.

  The dataset includes exome sequencing data and 704 Sanger sequencing validations for the 142 samples. The 704 Sanger sequencing validations are comprised of 416 variants and 288 sites known to be negative, including 293 indels and 247 negative indel sites. DNA libraries were prepared from genomic DNA using the Illumina TruSeq sample preparation kit. DNA was fragmented using Covaris technology and the libraries were prepared without gel size selection. Target enrichment was performed in pools of six libraries using the Illumina TruSeq Exome Enrichment kit. The captured DNA libraries were PCR amplified using the supplied paired-end PCR primers. Sequencing was performed with an Illumina HiSeq2000 (v3 flow cell, one pool per lane) generating 2x101-bp reads. Technology – Illumina HiSeq 2000

  Study EGAS00001001332

• Ex vivo RNA-seq in moderate COVID-19 monocytes

  This dataset was used to compare gene expression profiles of ex vivo isolated classical CD14+ monocytes from patients with moderate COVID-19 to those of healthy individuals. Blood samples were taken from patients with moderate COVID-19 admitted to hospitals in London (Hammersmith Hospital, Charing Cross Hospital, Saint Mary’s Hospital) 3-14 days after disease onset and 0-2 days after hospitalization and positive PCR, and before study treatment initiation. Moderate patients displayed mild or moderate COVID-19 pneumonia, defined as grade 3 or 4 WHO severity. Samples were collected from March 2020 to February 2021. Healthy donors were Imperial College staff with no prior diagnosis of or recent symptoms consistent with COVID-19, and where possible, were matched in age and sex distribution with COVID-19 patients. None of the participants of this study were COVID-19 vaccinated. Peripheral blood mononuclear cells (PBMCs) were isolated by Ficoll Hypaque (GE Healthcare) gradient centrifugation <4 hours after blood collection. CD14+ monocytes were isolated using a positive selection magnetic sorting kit (StemCell Technologies, UK) from total PBMC and stimulated with vehicle, UV-inactivated SARS-CoV-2 (CoV-2). RNA was isolated using the RNeasy Micro Plus Kit (QIAGEN) following the manufacturer’s guidelines. RNA-sequencing was performed by the Oxford Genomics Centre. PolyA-enriched strand- specific libraries were prepared using NEBNext Ultra II Directional RNA Library Prep Kits (Illumina). All samples were pooled together and 150bp PE reads were sequenced on a Novaseq 6000 system.

  Dataset EGAD00001009800

• Transcriptional and DNA binding profiling of CEBPE in REH acute lymphoblastic leukaemia cells using shRNA RNA-Seq and ChIP-Seq

  ChIP-Seq - CEBPE - REH. The ETV6/RUNX1 translocated acute lymphoblastic leukaemia cell line. REH was used to perform ChIP-Seq using a CEBPE antibody. Cells were fixed in 1% formaldehyde for 10mins, prior to preparation of chromatin using Active Motif Express ChIP-IT. 2ug of antibody (anti CEBPE Atlas Antibodies HPA002928)was added to 25ug of chromatin O/N at 4C with rotation. Duplicate reactions were pooled and purified. 10ng of ChIP’d and input DNA used for Illumina NGS preparation (NEBNext ChIP-Seq Library kit; New England Biolabs), CEBPE and Input DNA ChIP samples were sequenced on a MiSeq using 150bp Kit v3 paired end and a HiSeq 2500 using 2x101 version 4 paired end (Illumina) respectively. Reactions performed in duplicate. shCEBPE RNA-Seq - REH. REH cells were lentivirally transduced with a pTRIPZ shRNA vector for transcriptional profiling of CEBPE. Two controls (empty and non-targeting) and two CEBPE shRNAs (V3THS_150517(A13), V3THS_404312(G3) Dharmacon, GE) were transduced into REH cells. Cells were treated with 1ug/ml doxycyclin for 144hrs and total RNA purified using Qiagen RNeasy. Knock down of CEBPE was validated by qRT. RNA integrity >7.7 for all samples. Libraries were prepared using NEBNext Ultra II Directional RNA Library Prep Kit and sequenced on an Illuimna HiSeq 2500 using 2x101 version 4 paired end chemistry. 3 biological replicates of each samples were prepared.

  Dataset EGAD00001004084

• Clonally resolved single-cell multi-omics identifies routes of cellular differentiation in acute myeloid leukemia

  In this study we generated single-cell whole transcriptome and surface marker expression data for 24 samples of 19 AML patients as well as one healthy donor. We followed the CITEseq protocol with the 3' 10x Genomics scRNAseq kit version 3.1 To increase the coverage of the mitochondrial genome we generated mitochondrial libraries following a protocol termed Optimized 10x. Based on TAPseq, we generated libraries to increase the coverage of selected nuclear SNVs. Exome sequencing was generated for 15 patients to identify nuclear variants. Bulk ATAC was obtained for 9 samples to facilitate the discovery of mitochondrial SNVs. MutaSeq (modified version of SmartsSeq2) was performed on cells from 3 patients. Targeted DNAseq from single-cell derived colonies was generated for 1 patient.

  Study EGAS00001007078

• Center for Common Disease Genomics [CCDG] - Cardiovascular: The Genetics of Atrial Fibrillation

  This study is a part of NHGRI's Center for Common Disease Genomics, which is a collaborative large-scale genome sequencing effort to comprehensively identify rare risk and protective variants contributing to multiple common disease phenotypes. Current estimates anticipate that the CCDG program will sequence approximately 140K whole genomes and 225K whole exomes during the life of the project. The Cardiovascular Disease working group of the CCDG considered five diseases: early-onset coronary artery disease (EOCAD), stroke, atrial fibrillation, congestive heart failure and type 2 diabetes. Atrial fibrillation will affect between 6-12 million individuals in the US by 2050. AF also is associated with increased risks of stroke, dementia, heart failure, death, and high health care costs. Many risk factors for AF have been identified, including advancing age, cardiovascular disease (CVD), and CVD risk factors. However, there is little knowledge how to prevent AF. Furthermore, therapies for AF are only partially effective, and are themselves associated with substantial morbidity. Previously, heritable forms of AF have been considered rare; yet in the last decade, it has been established that AF, and in particular early-onset forms of AF, are heritable. Genome-wide association studies (GWAS) provide a powerful tool to identify common variants underlying disease risk. The AFGen Consortium currently consists of investigators from more than 25 studies with >20,000 individuals with AF and >100,000 without AF. In the latest analyses, 14 loci have been identified for AF1 . Broadly, the loci implicate genes related to cardiopulmonary development, cardiac-expressed ion channels, and cell signaling molecules.Source: https://ccdg.rutgers.edu/sites/default/files/CCDG_CVD_EOAF_FINAL_w_link.pdfFor this study, The Broad Institute of MIT and Harvard generated genetic data for UWO Genetic Investigation of Supraventricular Tachycardias.Patients confirmed to possess a supraventricular tachycardia and/or an accessory pathway at the time of invasive electrophysiology study at the London Health Sciences Centre, London, Ontario, Canada were eligible for enrollment. Potential supraventricular tachycardias included atrioventricular nodal reentrant tachycardia (AVNRT), atrioventricular reentrant tachycardia (AVRT), atrial tachycardia, junctional tachycardia, atriofascicular tachycardia, nodofascicular tachycardia, and nodoventricular tachycardia. Patients that did not have inducible supraventricular tachycardia, but had an accessory pathway that conducted antegrade, retrograde, or both, were also eligible for enrollment. All patients additionally underwent, at minimum, a clinical history, physical examination, 12-lead ECG, and echocardiogram. Study participants provided informed written consent under a protocol approved by the research ethics board of Western University.Raw sequencing data, metadata, vcf and phenotype data at individual level are available at https://anvilproject.org/data For questions about availability contact help@lists.anvilproject.org.

  Study phs002811

• Population Architecture Using Genomics and Epidemiology (PAGE): Epidemiologic Architecture for Genes Linked to Environment (EAGLE) - BioVU Cancer Project

  As part of Population Architecture using Genomics and Epidemiology PAGE study (Phase I), the Epidemiologic Architecture using Genomics and Epidemiology (EAGLE I) project accessed both epidemiologic- and clinic-based collections. The epidemiologic-based collection of EAGLE I included the National Health and Nutritional Examination Surveys (NHANES), ascertained between 1991-1994 (NHANES III), 1999-2002, and 2007-2008. NHANES is a population-based cross-sectional survey now conducted every year in the United States to assess the health status of Americans at the time of ascertainment and to assess trends over the years of survey. Genetic NHANES consists of 19,613 DNA samples linked to thousands of variables including demographics, health and lifestyle variables, physical examination variables, laboratory variables, and exposures. NHANES is diverse with almost one-half of the samples (46.4%) coming from self-reported Mexican Americans and non-Hispanic blacks. In contrast to NHANES, BioVU is a clinic-based collection of >150,000 DNA samples from Vanderbilt University Medical Center linked to de-identified electronic medical records (EMRs). Approximately 12% of BioVU's overall DNA sample collection is from African American, Hispanic, and Asian patients. The overall goals of PAGE I and EAGLE I were broad and several-fold: Replicate genome-wide association study (GWAS)- identified variants in European Americans; Identify population-specific and trans-population genotype-phenotype associations; Identify genetic and environmental modifiers of these associations. NHANES is an excellent resource for the study of quantitative traits associated with common human diseases. However, given that the age range of NHANES spans childhood to late adulthood and not all diseases are surveyed, NHANES is less useful for the study of adult-onset diseases such as major cancers. Therefore, under American Recovery and Reinvestment Act (ARRA) funding, EAGLE as part of PAGE I defined eight major cancers sites for genetic analysis in BioVU, Vanderbilt's biorepository linked to de-identified EMRs. The eight major cancers defined for this study included melanoma, breast, ovarian, prostate, colorectal, lung, endometrial, and Non-Hodgkin's lymphoma (NHL). Cancer cases were defined using a combination of ICD-9 codes and tumor registry entries. Controls include BioVU participants without cancer and encompassing the age and gender distributions of cancer cases. Targeted genotyping of GWAS-identified variants for these diseases (124 SNPs) and ancestry informative markers (128 AIMs) was performed by the Center for Human Genetics Research Vanderbilt DNA Resources Core. After quality control, a total of 116 cancer-associated SNPs and 122 AIMs were available for downstream analyses.

  Study phs000559

• Genomics of Kidney Transplantation

  We have an established consortium consisting of 5 clinical centers which do a total of >800 kidney transplants/year. We have developed a quality-controlled multicenter database with high quality data, and obtained DNA samples and clinical data on 962 recipients and 442 donors. Using our developed infrastructure, we propose to study whether genetic variants are, in part, responsible for the differing outcomes of transplant recipients treated with contemporary immunosuppressive protocols. Our central hypotheses are that the genetic variation is associated with a) kidney transplant outcome, and b) immunosuppressive drug disposition and toxicity. Our long-term goals are to determine whether it is possible to individualize immunosuppressive therapy, based on genetics. At the same time, our studies may elicit new information on pathways important in the immune response or in immunosuppressive drug efficacy, disposition, and toxicity.Our application consists of 3 cores (Genetics Core, Clinical Core, and Administrative Core). We will do a genome wide association study (GWAS). Significant single nucleotide polymorphisms (SNPs) will be identified using the GWAS.Project 1 has 2 specific aims.Aim 1: To identify recipient SNPs that are associated with kidney allograft outcomes, including acute rejection, chronic graft dysfunction, and graft failure. Aim 2: To identify living donor SNPs that are associated with kidney allograft outcomes. Project 2 has 4 specific aims. Aim 1: To identify SNPs that are associated with tacrolimus blood levels.Aim 2: To identify SNPs that are associated with early tacrolimus-related nephrotoxicity and immune suppressant-related new onset diabetes.Aim 3: To identify SNPs that are associated with mycophenolate-related toxicity. Aim 4: To establish the relationships between candidate recipient SNPs, enzyme activity and mRNA expression of the pharmacologic targets of mycophenolate and calcineurin inhibitors. The projects use the genotyping data, which were provided by the Genetics Core, and clinical information, which were collected and entered into the multicenter database by the Clinical Core. Further, biostatistical support (Clinical Core) and administrative oversight and support (Administrative Core) will facilitate data collection, data entry, and data analyses for both projects. The Administrative Core will also facilitate interaction between Sites, Cores, and Projects.Technical note: Regarding to the study design, all transplant recipients should be unrelated. Given the nature of transplantation, some donors may be related to recipients. The donor-recipient relationships are reported in the demographic file under the "related" column. As we did not collect full pedigree information for the related donor-recipient pairs, we have included a IBD file (calculated using PLINK) with the genotype data.

  Study phs001667

• Women's Environmental Cancer and Radiation Epidemiology (WECARE) Study

  Study population The WECARE Study is an international multicenter population-based case-control study of cases with asynchronous contralateral breast cancer (CBC) and individually matched controls with unilateral breast cancer (UBC). Recruitment and data collection for the WECARE Study were conducted in two phases, herein referred to as WECARE I (2001–2004) and WECARE II (2009–2012). The study design of the first phase (WECARE I) has been described in detail elsewhere [Bernstein JL, et al 2004, PMID: 15084244]; the second phase (WECARE II) employed a nearly identical approach [Langballe R, et al 2016, PMID: 27400983]. Participants in each phase were identified through eight population-based cancer registries, including six in the United States that contribute to the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) program: Los Angeles County Cancer Surveillance Program; Cancer Surveillance System of the Fred Hutchinson Cancer Center (Seattle region, WA); State Health Registry of Iowa; Cancer Surveillance Program of Orange County/San Diego-Imperial Organization for Cancer Control (Orange County/San Diego, CA); the Greater Bay Area Cancer Registry (San Francisco Bay Area region and Santa Clara region, CA); and the Sacramento and Sierra Center Registry (Sacramento region, CA). Participants were additionally identified using the Ontario Cancer Registry (Canada) and the Danish Breast Cancer Cooperative Group Registry, supplemented by data from the Danish Cancer Registry. The study protocol was approved by the institutional review or regulatory ethics boards at each study site. Data collection Study participants were interviewed by telephone using a structured questionnaire aimed at evaluating known or suspected breast cancer risk factors, including personal demographics, medical history, menstrual and reproductive history, family history of cancer, use of hormones, smoking, and alcohol intake. Risk factor status was assessed during the period prior to first diagnosis, as well as between first diagnosis and reference date (i.e., the at-risk period for CBC). Detailed data on treatment and tumor characteristics were obtained directly from cancer registry records or by abstracting medical records, including pathology and surgical reports, radiation oncology clinic notes, and systemic adjuvant treatment data. Complete medical treatment history information was collected, and for all women who received radiotherapy, the radiation dose to the contralateral breast was reconstructed using radiotherapy records and radiation measurements. Biospecimens were collected from study participants for genotyping: blood collected from WECARE I women; and saliva collected from WECARE II women.

  Study phs003945

• Neurodevelopmental Genomics: Trajectories of Complex Phenotypes

  This study is a collaboration between the Center for Applied Genomics (CAG) at Children's Hospital of Philadelphia (CHOP) and the Brain Behavior Laboratory at the University of Pennsylvania (Penn). The cohort consists of youths aged 8-21 years who consulted the CHOP network and volunteered to participate in genomic studies of complex pediatric disorders. All participants underwent clinical assessment, including a neuropsychiatric structured interview and review of electronic medical records. They were also administered a neuroscience based computerized neurocognitive battery (CNB) and a subsample underwent neuroimaging. These are described separately below. Clinical Testing: GOASSESS, a computerized, structured screener developed from a modified version of the Kiddie-Schedule for Affective Disorders and Schizophrenia (K-SADS, Kaufman et al. 1997, PMID: 9204677). Components of the interview include a timeline of life events, demographics and medical history, Global Assessment of Functioning, and Interviewer Observations. A psychopathology symptom and criterion-related assessment of mood disorders (depression, mania/hypomania), anxiety disorders (overanxious/generalized-, separation-, social-anxiety, specific phobia, panic disorder, agoraphobia, obsessive compulsive disorder, post-traumatic stress disorder), behavioral disorders (attention deficit hyperactivity disorder, oppositional defiant disorder, conduct disorder), psychosis spectrum (psychosis and prodromal symptoms), eating disorders, suicidal thinking and behavior, and treatment history. This is also based on K-SADS. An abbreviated Family Interview for Genetics Studies (FIGS) to assess major domains of psychopathology in the proband's first-degree relatives. Computerized Neurocognitive Battery: The CNB, developed for large-scale studies, yields measures of accuracy and speed for domains of executive-control functions (abstraction, attention, working memory), episodic memory (verbal, facial, spatial), complex cognitive processing (language reasoning, nonverbal reasoning, spatial processing), social cognition (emotion identification, emotion intensity differentiation, age differentiation) and sensorimotor and motor speed. The following neurobehavioral domains were assessed: Penn Conditional Exclusion Test is a measure of abstraction and concept formation. Participants decide which of 4 objects does not belong with the other 3, based on one of three sorting principles, which change. Feedback is used. Attention: The Penn Continuous Performance Test. Participants respond to a set of 7-segment displays whenever they form a digit or letter. Working Memory: The Letter N-back Test displays sequences of uppercase letters with a stimulus duration of 500 ms (ISI 2,500 ms.) In the 0-back condition, participants respond to a single target (i.e., X). In the 1-back condition they respond if the letter is identical to that preceding it. In the 2-back condition, they respond if the letter is identical to that presented two trials back. Verbal Memory: The Penn Word Memory Test presents 20 target words that are then mixed with 20 distracters equated for frequency, length, concreteness and low imageability. A 20 min delayed recall procedure is also administered. Face Memory: The Penn Face Memory Test presents 20 digitized faces that are then mixed with 20 distracters equated for age, gender and ethnicity. The procedure is repeated at 20 min delay. Spatial Memory: The Visual Object Learning Test uses Euclidean shapes as stimuli with the same paradigm as the word and face. Language and Analogical Reasoning: The Penn Verbal Reasoning consists of verbal analogy problems. Spatial Processing: Penn Line Orientation Test presents two lines at an angle, and participants click on a button that makes one line rotate until it has the same angle as the other. Emotion Processing: Facial displays of 4 emotions (Happy, Sad, Anger, Fear) and Neutral faces, 8 each, are presented and the subject identifies the emotion in a multiple-choice format. The facial stimuli are balanced for gender, age, and ethnicity. Sensory-motor Processing Speed: The task requires moving the mouse and clicking on a green square that disappears after the click. The square gets increasingly small and appears in unpredictable locations. Neuroimaging Protocol: Studies were performed at Penn using a Siemens Trio (Erlangen, Germany) 3T scanner equipped with 40mT/m gradients and 200 mT/m/s slew-rates. RF transmission utilized a quadrature body-coil, and reception a 12-channel head coil optimized for parallel imaging. Total image acquisition time was about 45 min. Structural Imaging: The T1-weighted protocol utilized a 3D, inversion-recovery, and magnetization-prepared rapid acquisition gradient echo. Relevant imaging procedures include: Structural magnetic imaging Diffusion tensor imaging ASL perfusion BOLD fMRI Neuroimaging tasks: Fractal N-Back Task of Spatial Working Memory Face Emotion Identification Task Neuroimages: The current data release includes over 9700 MRI images that may be downloaded through Authorized Access.

  Study phs000607

• Lung Tissue Research Consortium (LTRC-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 LTRC include DNA, Plasma, Serum, Tissue - FFPE Cassettes, Tissue – RNALater Frozen, and Tissue - Snap Frozen. Please note that use of biospecimens in genetic research is subject to a tiered consent. Objectives: The LTRC was a biobank resource established by the NHLBI to collect and distribute lung tissue, blood samples, clinical data, and radiographic studies from participants with chronic obstructive pulmonary disease (COPD), idiopathic pulmonary fibrosis (IPF), other related idiopathic interstitial pneumonias (IIP) and interstitial pneumonias associated with connective tissue diseases who undergo medically-indicated lung resection. All tissue and blood specimens and clinical data were banked centrally and stored for distribution to external investigators who have approved study proposals to investigate the pathogenesis or management of lung diseases. The ultimate goal of this program was to enable research that illuminates the pathobiology of lung diseases and leads to novel interventional treatments for these conditions. Background: Chronic lung diseases are a main cause of death and disability in the United States. COPD affects over 14 million individuals in the United States and represents the third leading cause of mortality. Cigarette smoking is a major risk factor. However, only one of six individuals who smoke develops COPD. This could imply either an individual susceptibility or an additional immunologic or infectious injury to lung cells. Current treatments offer symptomatic relief, but do not prevent disease progression. Better understanding of disease pathogenesis, including the potential roles of lung parenchymal cell apoptosis, immunologic injury, and inflammation may lead to therapies that improve survival and quality of life. Interstitial pneumonias, including IPF and those associated with connective tissue disease, are less common than COPD, but for many of these diseases there are poor outcomes. For example, IPF has a 50% survival rate 2-3 years following diagnosis, and currently no treatment exists which prolongs survival. The prevalence of IPF is approximately 28 cases per 100,000. The underlying histology of IPF is usual interstitial pneumonia (UIP), which can also occur in connective tissue diseases. The incidences of other interstitial pneumonias such as non-specific interstitial pneumonia (NSIP) or acute interstitial pneumonia (AIP) are less frequent but also occur as an expression of interstitial lung disease in the connective tissue diseases. Moreover, there is significant crossover of these three interstitial pneumonias so that cases of IPF/UIP may also reveal fibrotic NSIP and be complicated by episodes of AIP. This implies common injuries but dissimilar histological responses. All of these processes are characterized by epithelial injury, uncontrolled fibroproliferation and the deposition of collagen, irrespective of the histology. It is clear that a better understanding of the genesis of the interstitial pneumonias is required before effective interventions can be developed. Participants: A total of 4,486 participants were enrolled, and lung tissue was obtained from 3,333 of these participants.Design: Written informed consent of each participant was required before any LTRC procedure was performed. Phenotypic data were then obtained that included recording of relevant medical information, a limited exposure history, radiological evaluation, and pulmonary physiological and lung function testing. Questionnaires were administered to determine the extent of symptoms, associated medical illnesses, smoking, environmental and occupational exposures, and quality of life. Laboratory testing included pulmonary function testing, a six-minute walk test, and chest x-ray CT. Blood specimens were collected both for defining the clinical phenotype of donors and to obtain serum, plasma, and DNA for later investigative purposes. At the time of surgery, lung tissues were collected and processed for long-term storage. The LTRC collected only the 'non-tumorous' portions of lung tissue from surgical procedures performed for primary or metastatic lung tumors and received those specimens only after the local pathologist had procured all tissue required for clinical care. Samples of appropriate size were cut and placed in formalin, RNAlater, glutaraldehyde, or liquid nitrogen within 30 minutes of excision (approximately 5% of cases exceeded this target time). Blood and tissue specimens were subsequently shipped to a central Tissue Repository for further processing and long-term storage. A Radiology Center provided quality control and quality assessment of CT data. A Data Coordinating Center managed study operations and maintained a repository of study data. Conclusions: LTRC established a biospecimen collection that is unique in its size, diseases included, standardization of methods, and extent of phenotypic data, serving as a valuable resource to facilitate research on the pathobiology of lung diseases.

  Study phs003913