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• A108735A

  Whole genome sequencing for single cells for library A108735A 714 cells; filetype=bam

  Dataset EGAD00001007593

• 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

• WGS data for manuscript titled: Multi-omic features of oesophageal adenocarcinoma in patients treated with preoperative neoadjuvant therapy

  WGS data for manuscript titled: Multi-omic features of oesophageal adenocarcinoma in patients treated with preoperative neoadjuvant therapy

  Dataset EGAD00001008646

• 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

• Alignment BAM files and gene count files of the Illumina Sequencing Data (10 tumor samples)

  Reads were processed with the RNA-seq workflow 1.3.0 developed by the DKFZ Omics IT and Data Management Core Facility (https://github.com/DKFZ-ODCF/RNAseqWorkflow). First, FASTQ reads were aligned via two-pass alignment using STAR 2.5.3a. The STAR index was generated from the 1000 Genomes assembly and GENCODE Version 19 gene models with a sjdbOverhang of 200. Duplicate marking of the resultant main alignment file was done with sambamba 0.6.5. Gene-specific read counting was performed using featureCounts (from Subread 1.5.1) over exon features based on GENCODE Version 19 gene models. Both reads of a paired fragment were used for counting, and the quality threshold was set to 255, indicating that STAR found a unique alignment. Strand-specific counting was also used. For RPKM and TPM calculations, all genes on chromosomes X and Y, the mitochondrial genome, as well as rRNA and tRNA genes were omitted as they are likely to introduce library size estimation biases.

  Dataset EGAD00001008969

• 10x Genomics Single Cell Gene Expression for SA1188

  10x Genomics Single Cell Gene Expression for Telomerase immortalized breast epithelium cell line 184-hTert L9 116.66

  Dataset EGAD00001009114

• 10x Genomics Single Cell Gene Expression for SA604X7XB02089

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA604 passage 7

  Dataset EGAD00001009119

• 10x Genomics Single Cell Gene Expression for SA609X6XB01899

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA609 passage 6

  Dataset EGAD00001009120

• 10x Genomics Single Cell Gene Expression for SA1049AX1XB01417

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1049 passage 1

  Dataset EGAD00001009121

• 10x Genomics Single Cell Gene Expression for SA1052DX1XB01519

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1052 passage 1

  Dataset EGAD00001009122

• 10x Genomics Single Cell Gene Expression for SA1053EX1XB01608

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1053 passage 1

  Dataset EGAD00001009123

• 10x Genomics Single Cell Gene Expression for SA1051AX1XB01452

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1051 passage 1

  Dataset EGAD00001009124

• 10x Genomics Single Cell Gene Expression for SA535X6XB03099

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA535 passage 6

  Dataset EGAD00001009116

• 10x Genomics Single Cell Gene Expression for SA535X4XB05462

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA535 passage 4

  Dataset EGAD00001009115

• 10x Genomics Single Cell Gene Expression for SA1055

  10x Genomics Single Cell Gene Expression for Telomerase immortalized breast epithelium cell line 184-hTERT-22 L9 112.109

  Dataset EGAD00001009111

• 10x Genomics Single Cell Gene Expression for SA1056

  10x Genomics Single Cell Gene Expression for Telomerase immortalized breast epithelium cell line 184-hTERT-22 L9 116.126

  Dataset EGAD00001009112

• 10x Genomics Single Cell Gene Expression for SA1054

  10x Genomics Single Cell Gene Expression for Telomerase immortalized breast epithelium cell line 184-hTERT-22 L9 83.86

  Dataset EGAD00001009113

• 10x Genomics Single Cell Gene Expression for SA604X8XB02164

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA604 passage 8

  Dataset EGAD00001009118

• 10x Genomics Single Cell Gene Expression for SA604X6XB01979

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA604 passage 6

  Dataset EGAD00001009117

• 10x Genomics Single Cell Gene Expression for SA1035X4XB02879

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA1035 passage 4

  Dataset EGAD00001009147

• 10x Genomics Single Cell Gene Expression for SA1050FX1XB01446

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1050 passage 1

  Dataset EGAD00001009125

• 10x Genomics Single Cell Gene Expression for SA1050DX1XB01437

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1050 passage 1

  Dataset EGAD00001009126

• 10x Genomics Single Cell Gene Expression for SA1052BX1XB01516

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1052 passage 1

  Dataset EGAD00001009127

• 10x Genomics Single Cell Gene Expression for SA1053FX1XB01611

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1053 passage 1

  Dataset EGAD00001009128

• 10x Genomics Single Cell Gene Expression for SA1093CX1XB01917

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1093 passage 1

  Dataset EGAD00001009129

• 10x Genomics Single Cell Gene Expression for SA1091AX1XB01790

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1091 passage 1

  Dataset EGAD00001009130

• 10x Genomics Single Cell Gene Expression for SA1053BX1XB01603

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1053 passage 1

  Dataset EGAD00001009131

• 10x Genomics Single Cell Gene Expression for SA1096AX1XB02034

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1096 passage 1

  Dataset EGAD00001009132

• 10x Genomics Single Cell Gene Expression for SA1051DX1XB01482

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1051 passage 1

  Dataset EGAD00001009133

• 10x Genomics Single Cell Gene Expression for SA1052JX1XB01535

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1052 passage 1

  Dataset EGAD00001009134

• 10x Genomics Single Cell Gene Expression for SA1181AX1XB02700

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1181 passage 1

  Dataset EGAD00001009135

• 10x Genomics Single Cell Gene Expression for SA1096CX1XB02039

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1096 passage 1

  Dataset EGAD00001009136

• 10x Genomics Single Cell Gene Expression for SA1096BX1XB02037

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1096 passage 1

  Dataset EGAD00001009137

• 10x Genomics Single Cell Gene Expression for SA1162BX1XB03004

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1162 passage 1

  Dataset EGAD00001009138

• 10x Genomics Single Cell Gene Expression for SA1096A

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient SA1096

  Dataset EGAD00001009139

• 10x Genomics Single Cell Gene Expression for SA1049CX1XB01422

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1049 passage 1

  Dataset EGAD00001009140

• 10x Genomics Single Cell Gene Expression for SA1050EX1XB01442

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1050 passage 1

  Dataset EGAD00001009141

• 10x Genomics Single Cell Gene Expression for SA605X3XB01966

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA605 passage 3

  Dataset EGAD00001009142

• 10x Genomics Single Cell Gene Expression for OV2295

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma cell line OV2295

  Dataset EGAD00001009143

• 10x Genomics Single Cell Gene Expression for OV2295(R2)

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma cell line OV2295(R2)

  Dataset EGAD00001009144

• 10x Genomics Single Cell Gene Expression for SA1184SA

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient SA1184

  Dataset EGAD00001009145

• 10x Genomics Single Cell Gene Expression for SA1047BX1XB01022

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1047 passage 1

  Dataset EGAD00001009146

• 10x Genomics Single Cell Gene Expression for SA1035X8XB03425

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA1035 passage 8

  Dataset EGAD00001009148

• 10x Genomics Single Cell Gene Expression for SA535X6XB03101

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA535 passage 6

  Dataset EGAD00001009149

• 10x Genomics Single Cell Gene Expression for SA1035X6XB03211

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA1035 passage 6

  Dataset EGAD00001009150

• Upper cortical layer-driven network impairment in schizophrenia - 10x genomics v3 snRNA-seq and Visium spatial transcriptomics datasets

  This dataset contains 10x Genomics v3 3’ single nuclei RNA sequencing (24 human schizophrenia and control samples) and 10x Genomics Visium spatial transcriptomics (14 human schizophrenia and control samples) datasets. Files are in .bam format, output of the cellranger v3.1.0 (https://support.10xgenomics.com/single-cell-gene-expression/software/pipelines/3.1/using/count) for snRNA-seq and spaceranger v1.1.0 (https://support.10xgenomics.com/spatial-gene-expression/software/pipelines/1.1/using/count) for Visium samples. Reads were mapped against Release 97 of human genome from Ensembl (http://ftp.ensembl.org/pub/release-97/fasta/homo_sapiens/dna/Homo_sapiens.GRCh38.dna.primary_assembly.fa.gz http://ftp.ensembl.org/pub/release-97/gtf/homo_sapiens/Homo_sapiens.GRCh38.97.gtf.gz). More details on sample processing are available in the biorXiv pre-print (https://doi.org/10.1101/2020.11.17.386458) and upcoming publication in Science Advances. BAM files can be converted to fastq files using bamtofastq tool (https://support.10xgenomics.com/docs/bamtofastq) with downstream remapping using tools and genomes of choice.

  Dataset EGAD00001009173

• MutWP5: CRUK Mutographs of Cancer: Breast: Reduction Mammoplasty (Exome)

  Sequencing of LCM-derived microbiopsies from 10 women who underwent reduction mammoplasty. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Exome data will be used as a driver and clonality screen, highly clonal or driver-containing samples will subsequently be sent for whole-genome sequencing. Results from this portion of the study will be compared to women who are BRCA1/2 germline carriers and those with cancer. . This dataset contains all the data available for this study on 2023-03-08.

  Dataset EGAD00001010110

• MutWP5: CRUK Mutographs of Cancer: BRCA Carriers (WG)(Novaseq)

  Sequencing of LCM-derived microbiopsies from 20 women who underwent risk-reducing reduction mastecomies due to germline BRCA1/2. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Exome data will be used as a driver and clonality screen, highly clonal or driver-containing samples will subsequenctly be sent for whole-genome sequencing. Results from this poriton of the study will be compared to women who had cosmetic breast reduction surgeries and those with cancer. . This dataset contains all the data available for this study on 2023-03-08.

  Dataset EGAD00001010112

• MutWP5: CRUK Mutographs of Cancer: Breast: Reduction Mammoplasty (WG)(Novaseq)

  Sequencing of LCM-derived microbiopsies from 10 women who underwent reduction mammoplasty. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Exome data will be used as a driver and clonality screen, highly clonal or driver-containing samples will subsequenctly be sent for whole-genome sequencing. Results from this poriton of the study will be compared to women who are BRCA1/2 germline carriers and those with cancer. . This dataset contains all the data available for this study on 2023-03-08.

  Dataset EGAD00001010113

• MutWP5: CRUK Mutographs of Cancer: BRCA Carriers (Exome)(Novaseq)

  Sequencing of LCM-derived microbiopsies from 20 women who underwent risk-reducing reduction mastecomies due to germline BRCA1/2. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Exome data will be used as a driver and clonality screen, highly clonal or driver-containing samples will subsequenctly be sent for whole-genome sequencing. Results from this poriton of the study will be compared to women who had cosmetic breast reduction surgeries and those with cancer. . This dataset contains all the data available for this study on 2023-03-08.

  Dataset EGAD00001010115

• MutWP5: CRUK Mutographs of Cancer: Breast: Reduction Mammoplasty (Exome)(Novaseq)

  Sequencing of LCM-derived microbiopsies from 10 women who underwent reduction mammoplasty. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Exome data will be used as a driver and clonality screen, highly clonal or driver-containing samples will subsequenctly be sent for whole-genome sequencing. Results from this poriton of the study will be compared to women who are BRCA1/2 germline carriers and those with cancer. . This dataset contains all the data available for this study on 2023-03-08.

  Dataset EGAD00001010116

• Whole blood RNA sequencing of individuals from Nepal

  This study utilized blood samples collected in Lalitpur, Nepal as part of the Strategic Typhoid Alliance across Africa and Asia (STRATAA) study. The dataset comprises whole blood RNAseq of 376 febrile individuals from Nepal. Blood was collected in PAXgene tubes and sent to Monash University (Melbourne, Australia) where RNA was extracted using the PAXgene Blood RNA kit before being sent to the Wellcome Sanger Institute (Hinxton, UK) for sequencing. Library prep used NEBNext Ultra II RNA custom kits on an Agilent Bravo WS automation platform with poly(A) pulldown. After PCR, plates were purified using Agencourt AMPure XP SPRI beads and libraries were quantified using Biotium Accuclear Ultra high sensitivity dsDNA Quantitative kits. Pooled libraries were normalised to 2.8 nM. Samples were globin depleted using KAPA RNA HyperPrep with RiboErase. Libraries were then subjected to 2x100bp paired-end sequencing on Illumina NovaSeq. Each library was sequenced to an average of 80 million reads. The STRATAA study was approved by the Nepal Health Research Council (NHRC, ref 283 306/2015) and OxTREC (Oxford Tropical Research Ethics Committee, ref 39-15). All participants provided informed consent for human genetic tests.

  Dataset EGAD00001011131

• Methylation biomarker study of magnesium deficiency and colorectal cancer

  Five US studies using the Mg tolerance test, the "gold standard" test of Mg status, indicated that >50% participants had Mg deficiency. In our ongoing US trial, we have found a similar result. In growing recognition of the importance of Mg in human health, very recently, Mg was selected by the US Federal Dietary Reference Intake (DRI) Committee to update the DRI. In US and other populations at high risk of Mg deficiency, high Mg intake has been linked to reduced risk of colorectal neoplasia, insulin resistance, metabolic syndrome, type 2 diabetes, and cardiovascular disease (CVD). Conversely, in populations not at high risk of Mg deficiency, high Mg intake has been related to increased risk of total mortality (e.g. total cancer, colorectal cancer, and CVD), particularly when calcium intake is low. These observations suggest that the associations between high Mg intake and disease risks may completely differ by the underlying Mg status. Due to major limitations, the Mg tolerance test is not used in conventional clinical practice and rarely used in research. Instead, serum Mg is used for clinical diagnosis. However, serum Mg performs very poorly at identifying those with Mg deficiency. There is a great need to develop implementable, sensitive, and specific biomarkers which can be easily used for identifying people with Mg deficiency. Without such a marker, it is impossible to develop effective strategies that minimize adverse effects by targeting those who, as a result of Mg deficiency, are at risk of common diseases. It is known that DNA methylation changes are inducible by environmental exposures, including nutrients, and reversible when the exposure disappears. There are two major types of cytosine modifications in DNA, 5-hydroxymethylcytosine (5-hmC) and 5-methylcytosine (5-mC). 5-mC is often associated with suppressed gene expression. 5-hmC, generated by the oxidation of 5-mC, is specifically enriched in expressed genes and plays a critical role in activating and/or maintaining gene expression. However, current epigenomic profiling platforms cannot distinguish 5-hmC from 5-mC. Just recently, our collaborator, Dr. Chuan He (HHMI Investigator), established a novel and state of the art technique, TAB-Seq and TAB-Array protocol, which can separate 5-hmC from 5-mC in the genome. Our pilot studies indicate that Mg intake or treatment significantly affects methylation capacity, 5-mC and 5-hmC biomarkers. Our findings suggest blood leukocyte 5-hmC/5-mC biomarkers may serve as more sensitive biomarkers to identify Mg deficiency than serum Mg. Thus, a comprehensive epigenome-wide association study (EWAS) may help to identify the most sensitive 5-hmC/ 5- mC biomarkers for Mg deficiency. We propose to identify 5-hmC/5-mC biomarkers for Mg deficiency by a 4- phase EWAS study in the "Personalized Prevention of Colorectal Cancer Trial [PPCCT, R01CA149633; PI, Dai and Yu]" with a total of 240 participants. Mg tolerance test will be used as the gold standard. Finally, using newly identified biomarkers, we will evaluate if 12-week Mg treatment reduces TRPM7 expression, essential in Mg homeostasis and colorectal carcinogenesis, in rectal tissues only among those with Mg deficiency.

  Study phs002037

• Environmental Influences on Child Health Outcomes (ECHO) - PATHWAYS - Conditions Affecting Neurocognitive Development and Learning in Early Childhood (CANDLE)

  Pregnant women are exposed daily to multiple chemical and non-chemical stressors, including air pollutants, phthalates, and psychosocial stress. The Developmental Origins of Health and Disease model (DOHaD) states that exposure to these stressors in pregnancy affects fetal development in a manner that impacts offspring health across the life course. Yet epidemiologic data in these areas is limited, particularly with U.S. samples. It is also poorly understood whether these exposures prenatally affect childhood neurodevelopment and airway health in an independent or combined manner, and likely moderators of effects, such as the sex of the child, are infrequently addressed. We propose to unify three diverse extant pregnancy cohorts: TIDES (N=717, 2010-12), GAPPS (N=1133, 2012-16), and CANDLE (N=1385, 2007-11), for a combined sample size of 3235 mother-child dyads in the PATHWAYS study. PATHWAYS will investigate how chemical (air pollutants and phthalates) and non-chemical (psychosocial stress) exposures during pregnancy are related to placental gene expression (transcriptome) and childhood neurodevelopment and airway health (at ages 4-6, 8-9, and 10-11 years). Each cohort has rich resources of prenatal data and banked specimens (urine, blood, and placenta) that will be harmonized for the PATHWAYS study and will contribute to the ECHO consortium. We will develop a national model with high spatiotemporal resolution of key air pollutants and assess urinary markers of maternal exposure. A composite measure will capture multilevel maternal psychosocial stress across pregnancy, and urinary phthalate and blood stress hormone [Corticotropin-releasing hormone (CRH)] levels in the second and third trimesters will provide individual assessment of those exposures in potential critical periods. We will characterize the placental transcriptome using RNA sequencing (RNA-Seq) and will assess neurodevelopment and airway health prospectively into middle childhood. PATHWAYS will examine how these prenatal exposures are related to the placental transcriptome and child health outcomes in main effect and interactive models, with emphasis on sex-specific associations. For both neurodevelopment and airway health, we propose to measure both phenotypic precursors of health outcomes (i.e. fluid cognition, lung function growth), which yield dimensional tests of proposed associations, as well as clinically meaningful and policy relevant outcomes (i.e. asthma, mental health). Our study is powered to assess interactive effects of chemical and non-chemical stressors and will be the first study to characterize how prenatal environmental exposures relate to placental transcriptome pathways in relation to childhood health outcomes. This represents a significant scientific advance in testing DOHaD hypotheses. Major contributions to the ECHO Consortium include: 1) the development of a state of the art national model of air pollution, 2) a large, diverse pregnancy cohort with extensive biorepositories and extant prenatal and postnatal biomarkers, placental transcriptome, psychosocial and environmental data, and 3) an experienced, interdisciplinary team that will contribute meaningfully to the ECHO program of work.The sequencing data in this submission pertains only to the 794 subjects from the CANDLE study for whom placental tissue transcriptomics was performed.

  Study phs003619

• Environmental Influences on Child Health Outcomes (ECHO) - PATHWAYS - Global Alliance to Prevent Prematurity and Stillbirth (GAPPS)

  Pregnant women are exposed daily to multiple chemical and non-chemical stressors, including air pollutants, phthalates, and psychosocial stress. The Developmental Origins of Health and Disease model (DOHaD) states that exposure to these stressors in pregnancy affects fetal development in a manner that impacts offspring health across the life course. Yet epidemiologic data in these areas is limited, particularly with U.S. samples. It is also poorly understood whether these exposures prenatally affect childhood neurodevelopment and airway health in an independent or combined manner, and likely moderators of effects, such as the sex of the child, are infrequently addressed. We propose to unify three diverse extant pregnancy cohorts: TIDES (N=717, 2010-12), GAPPS (N=1133, 2012-16), and CANDLE (N=1385, 2007-11), for a combined sample size of 3235 mother-child dyads in the PATHWAYS study. PATHWAYS will investigate how chemical (air pollutants and phthalates) and non-chemical (psychosocial stress) exposures during pregnancy are related to placental gene expression (transcriptome) and childhood neurodevelopment and airway health (at ages 4-6, 8-9, and 10-11 years). Each cohort has rich resources of prenatal data and banked specimens (urine, blood, and placenta) that will be harmonized for the PATHWAYS study and will contribute to the ECHO consortium. We will develop a national model with high spatiotemporal resolution of key air pollutants and assess urinary markers of maternal exposure. A composite measure will capture multilevel maternal psychosocial stress across pregnancy, and urinary phthalate and blood stress hormone [Corticotropin-Releasing Hormone (CRH)] levels in the second and third trimesters will provide individual assessment of those exposures in potential critical periods. We will characterize the placental transcriptome using RNA sequencing (RNA-Seq) and will assess neurodevelopment and airway health prospectively into middle childhood. PATHWAYS will examine how these prenatal exposures are related to the placental transcriptome and child health outcomes in main effect and interactive models, with emphasis on sex-specific associations. For both neurodevelopment and airway health, we propose to measure both phenotypic precursors of health outcomes (i.e., fluid cognition, lung function growth), which yield dimensional tests of proposed associations, as well as clinically meaningful and policy relevant outcomes (i.e., asthma, mental health). Our study is powered to assess interactive effects of chemical and non-chemical stressors and will be the first study to characterize how prenatal environmental exposures relate to placental transcriptome pathways in relation to childhood health outcomes. This represents a significant scientific advance in testing DOHaD hypotheses. Major contributions to the ECHO Consortium include: 1) the development of a state of the art national model of air pollution, 2) a large, diverse pregnancy cohort with extensive biorepositories and extant prenatal and postnatal biomarkers, placental transcriptome, psychosocial and environmental data, and 3) an experienced, interdisciplinary team that will contribute meaningfully to the ECHO program of work.The sequencing data in this submission pertain only to the 408 subjects from the GAPPS study for whom placental tissue transcriptomics was performed.

  Study phs003620

• Inorganic Nitrite Delivery to Improve Exercise Capacity in Heart Failure with Preserved Ejection Fraction (INDIE-HFpEF): Heart Failure Network (HFN INDIE-Imaging)

  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. Objective: To determine the effect of inhaled, nebulized inorganic nitrite on exercise capacity in patients with heart failure with preserved ejection fraction.Background: Approximately half of patients with heart failure have a preserved ejection fraction (HFpEF). However, there are no proven effective medical treatments for this syndrome. Evidence suggests that impairments in nitric oxide availability have a potentially important role in the pathophysiology of HFpEF.Unlike organic nitrates, inorganic nitrite is converted to nitric oxide in the presence of hypoxia and acidosis, conditions that develop during exercise. Because the cardiac, vascular, and skeletal muscle abnormalities that limit physical capacity and contribute to symptoms in patients with HFpEF characteristically develop during exercise, inorganic nitrite may provide the best way to target nitric oxide delivery precisely at the time of greatest need. The HFN-INDIE trial was initiated to test the hypothesis that compared to placebo, longer-term use of inhaled, nebulized inorganic nitrite would enhance peak exercise capacity in patients with HFpEF. Participants: A total of 105 participants were randomized. 53 were randomized to receive nitrite first and 52 were randomized to receive placebo first.Design: HFN-INDIE was a multicenter, randomized, double-blind, placebo-controlled, crossover study. After enrollment, patients underwent baseline studies to determine eligibility. All patients were required to display objective exercise limitation, evidenced by reduced peak oxygen consumption (V̇o2) on cardiopulmonary exercise testing of less than 75% predicted, with a respiratory exchange ratio indicative of maximal effort (≥1.0). Following qualifying exercise testing, eligible participants received an open-label, single-dose run-in of inhaled, nebulized sodium nitrite (80 mg) to assess tolerability, symptoms, and orthostatic vital signs. Patients developing hypotension (systolic blood pressure The prespecified primary end point was peak V̇o2, measured as the highest 30-second average during upright cycle ergometry, during the 4-week period in which patients were receiving inorganic nitrite as compared with placebo. Accelerometry, health-related quality-of-life scores on the self-administered Kansas City Cardiomyopathy Questionnaire (score range, 0-100, with higher scores indicating better quality of life), echocardiographic indicators of cardiac filling pressures measured at trough drug levels (E/e′ ratio, estimated pulmonary artery systolic pressure, and left atrial volume index; lower scores indicate better health for all), ventilatory efficiency (VE/V̇co2, lower indicating better health), exercise time (higher indicating better health), and NT-proBNP levels (lower indicating better health) were also collected.Data Availability: Data available from this study includes transthoracic echocardiogram images from multiple timepoints. There are 199 echocardiographic exams available, totaling over 13,100 individual echocardiogram images. Conclusions: Among patients with HFpEF, administration of inhaled inorganic nitrite for 4 weeks, compared with placebo, did not result in significant improvement in exercise capacity.Reference: Borlaug et al., 2018, PMID: 30398602.

  Study phs003804

• HeartShare - Extant Datasets - Harmonized Clinical Trials Collection

  Heart failure with preserved ejection fraction (HFpEF) prevalence is rising with an aging population and contributing comorbidities, such as obesity and diabetes. The Get With The Guidelines - Heart Failure (GWTG-HF) study showed that the proportion of hospitalized HFpEF patients rose from 2005 to 2010, and this trajectory continued to increase through 2020. HFpEF patients have a poor 5-year outcome with a 75% mortality rate. Taken together, these data suggest that HFpEF may be the dominant HF subtype in the future, affecting approximately 1 in 10 adults during their lifetime.In addition to its increasing prevalence, HFpEF is a heterogeneous syndrome with multiple pathophysiological processes and varied clinical presentations. There is an urgent need to improve understanding of different HFpEF phenotypes to match patients with interventions based on their unique subtype. Phenomapping studies have identified between two and six HFpEF clusters/phenogroups with shared features. Of these, three overlapping phenotypes repeatedly arise: an 'older, vascular aging' phenotype, 'metabolic, obese' phenotype, and 'relatively younger, natriuretic peptide (NP) deficiency' phenotype. Continued refinement of these HFpEF subtypes is needed to identify distinct characteristics and underlying biologic and molecular mechanisms towards therapeutic development and future precision trials with improved diagnostic criteria and treatment including prevention.The HeartShare extant datasets collection consists of selected completed trials on HFpEF which have been harmonized for the purpose identifying and defining subtypes. The goal is to identify HFpEF subtypes that have a common pathophysiology. Through the HeartShare extant datasets collection, users can request access to both the harmonized data and the individual trial datasets.To request access to this study collection, select phs003989 in the dbGaP when submitting a data access request. The following clinical trials and harmonized data is available through this collection:Study NameHandleAccessionConsent GroupsSurgical Treatment for Ischemic Heart FailureBioLINCC_STICHphs003493.v1.p1GRUHeart Failure Network Aldosterone Targeted Neurohormonal Combined with Natriuresis TherapyBioLINCC_HFN_ATHENAphs003506.v1.p1GRUHeart Failure Network - Effectiveness of Ultrafiltration in Treating People With Acute Decompensated Heart Failure and Cardiorenal SyndromeBioLINCC_HFN_CARRESSphs003510.v1.p1GRUHeart Failure Network: Diuretic Optimization Strategies Evaluation in Acute Heart FailureBioLINCC_HFN_DOSEphs003524.v1.p1GRUHeart Failure Network - Xanthine Oxidase Inhibition for Hyperuricemic Heart Failure PatientsBioLINCC_EXACT_HFphs003533.v1.p1GRUHeart Failure Network: Functional Impact of GLP-1 for Heart Failure TreatmentBioLINCC_HFN_FIGHTphs003542.v1.p1GRUHeart Failure Network - Nitrate's Effect on Activity Tolerance in Heart Failure with Preserved Ejection FractionBioLINCC_HFN_NEATphs003548.v1.p1GRUHeart Failure Network - Phosphodiesterase-5 Inhibition to Improve Clinical Status and Exercise Capacity in Diastolic Heart FailureBioLINCC_HFN_RELAXphs003565.v1.p1GRUHeart Failure Network - Renal Optimization Strategies Evaluation in Acute Heart Failure and Reliable Evaluation of DyspneaBioLINCC_HFN_ROSEphs003589.v1.p1GRUHeart Failure: A Controlled Trial Investigating Outcomes of Exercise TrainingBioLINCC_HF_ACTIONphs003599.v1.p1HMBHeart Failure: A Controlled Trial Investigating Outcomes of Exercise TrainingBioLINCC_HF_ACTIONphs003599.v1.p1HMB-NPUGuiding Evidence Based Therapy Using Biomarker Intensified Treatment in Heart FailureBioLINCC_GUIDE_ITphs003621.v1.p1GRUSudden Cardiac Death in Heart Failure TrialBioLINCC_SCD_HeFTphs003654.v1.p1GRUTreatment of Preserved Cardiac Function Heart Failure With an Aldosterone AntagonistBioLINCC_TOPCATphs003665.v1.p1HMB-MDSHeart Failure Network - Inorganic Nitrite Delivery to Improve Exercise Capacity in HFpEFBioLINCC_HFN_INDIEphs003667.v1.p1GRUStudies of Left Ventricular DysfunctionBioLINCC_SOLVDphs003668.v1.p1GRUEvaluation Study of Congestive Heart Failure and Pulmonary Artery Catheterization EffectivenessBioLINCC_ESCAPEphs003782.v1.p1GRU

  Study phs003989

• A_study_of_the_genetic_basis_of_evation_by_Acute_Myeloid_Leukaemia_of_Graft_vs_Leukaemia_effects_after_allogeneic_bone_marrow_transplantation

  Acute myeloid leukaemia (AML) is an aggressive and molecularly diverse disease with a poor overall survival of 20-25%. With an annual incidence of 2.9 per 100,000, AML is currently the commonest myeloid malignancy in Europe, yet the two main therapeutic options for this disease, anthracyclines and purine analogues, have remained unchanged for over 20 years. Currently patients are stratified at diagnosis according to a series of clinicopathological parameters (e.g. age, white cell count and presence/absence of previous clonal haematological disease) and molecular markers (e.g. chromosomal translocations/deletions, aneuploidy and mutations in genes such as FLT3 and NPM1). Patients with adverse prognostic features, whose prognosis is particularly poor (e.g. <15% long-term survival) are offered treatment with allogeneic bone marrow transplantation (allo-BMT) if a sibling or unrelated donor is available. This can significantly improve survival (e.g. up to 40% long-term survival in some contexts), albeit at the expense of significant toxicity and transplant-related mortality (TRM). Allo-BMT is thought to work in part by allowing the delivery of large doses of chemotherapy followed by haemopoietic "rescue" with donor haemopoietic stem cells (haemopoietic failure would otherwise ensue). However, potentially the most potent effect of allo-BMT is the cytotoxic effect of donor lymphocytes against AML blasts, a phenomenon known as graft-vs-leukaemia (GVL) effect. Increasingly, transplants using reduced chemotherapy intensity (mini-allografts) are being used that partially circumvent the toxicity from chemotherapy and rely on GVL to effect cure. Nevertheless, AML relapse after allo-BMT still occurs at a significant rate of up to 80% depending on the type of transplant. There is accumulating evidence that genetic events in residual leukaemic cells enable them to evade immunodetection and therefore survive the GVL effect and expand to cause relapse. The most striking example of this is the loss of HLA antigens after transplants in which donor and recipient are not fully HLA-matched. In these cases, the leukaemia "deletes" the genomic region containing the disparate HLA antigen which was preferentially targeted as "foreign" by the GVL effect. However, the genetic basis of immune evasion in the majority of transplants, which are fully HLA matched, is not known. One possibility is that loss of genes coding for antigens outside the HLA locus but which are also targets of GVL may operate, alternatively genetic events that affect processes downstream of immunological cytotoxicity may be responsible.The identification of genetic events that mediate immune evasion would not only facilitate the understanding of this process but can help plan therapeutic interventions that improve the outcomes of allogeneic transplantation for AML and other disorders. We intend to study this by conducting exome sequencing on 6 cases of AMLs from patients that attend my clinic at Addenbrooke's hospital and have relapsed after allogeneic transplantation. Samples from AML diagnosis, remission/normal and AML relapse (total n=18) will be studied to identify somatic mutations in the primary AML and those acquired by the relapsed clone. The 18 samples will also be studied by array CGH to detect regions of genomic amplification or deletion.

  Study EGAS00001000145

• Patient Registry for Primary Pulmonary Hypertension (PPH Registry-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 Establish a patient registry to evaluate the natural history, etiology, pathogenesis and treatment of primary pulmonary hypertension. Specific aims included the characterization of the demographic, medical history, family history, physical and laboratory findings of patients at time of diagnosis, and to characterize the survival duration of patients by traits evaluated at diagnosis and by medical interventions. Background There are several known causes of pulmonary hypertension: chronic obstructive pulmonary disease, congenital heart disease, mitral stenosis, left ventricular dysfunction and recurrent pulmonary emboli. Primary Pulmonary Hypertension is a disorder of unknown etiology which is diagnosed only after the known causes of pulmonary hypertension have been eliminated. Prior to the PPH registry, little was known regarding the epidemiology, etiology, natural history or ultimate survival among patients with PPH. In 1973, the WHO met to review the current state of knowledge on PPH and proposed the establishment of a multicenter collaborative study. The NHLBI PPH registry enrolled patients in the registry from 1981 to 1985. Participants Participants were enrolled into the registry from 32 medical centers throughout the US. Pulmonary hypertension was defined as a mean pulmonary arterial pressure of >25 mmHg at rest or 30 mmHg with exercise at catheterization. The diagnosis of primary pulmonary hypertension was only accepted after the following secondary causes of pulmonary hypertension had been excluded: pulmonary hypertension within the first year of life, congenital abnormalities of the heart, lungs, or diaphragm, pulmonary thromboembolic disease, diagnosis of sickle cell anemia, history of intravenous drug abuse, obstructive lung disease, interstitial lung disease, arterial hypoxemia, collagen vascular disease, parasitic disease affecting the lungs, pulmonary artery or valve stenosis, or pulmonary venous hypertension. Baseline and follow-up data collected on participants include demographic characteristics, chest radiograph, pulmonary function tests, lung perfusion scan or pulmonary angiogram, intracardiac left-to-right shunt, pulmonary hemodynamics, as well as a history, physical findings and other laboratory measurements. Participants were followed for approximately 5 years. Conclusions There were 1.7 females for each male in the registry, and females tended to present with more severe symptoms. The mean time from onset of symptoms to diagnosis was 2 years. Right ventricular hypertrophy was found in 87% of participants and right atrial pressure was elevated in 72% of participants. The estimated median survival was 2.8 years with single year survival rates of: 1 year, 68%; 3 years, 48%; and 5 years, 34%. (Ann Intern Med, 1987; 107:216-23, Ann Intern Med, 1991; 115:343-49).

  Study phs004275

• 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 - Gene Environment Association Studies Initiative (GENEVA)

  For the GENEVA CARDIA project, three genotype call sets were generated from a single set of array scans as a consequence of DNA sample quality problems. These call sets are designated "Birdsuite-1", "Birdsuite-2" and "Beaglecall". ("Beaglecall" used both Birdseed and BEAGLECALL calling algorithms.) An analysis-ready genotypic data set is provided in PLINK format for the "Beaglecall" set only, because it performs very well in QC analyses. Only raw CHP and ALLELE_SUMMARY files are provided for the two Birdsuite call sets because they have significant quality issues. Use of the Beaglecall set is highly recommended. Users of the other two call sets should proceed with caution. More details are given in the genotypic QC report. The CARDIA study, sponsored by the National Heart, Lung and Blood Institute (NHLBI), is a prospective, multi-center investigation of the natural history and etiology of cardiovascular disease in African-Americans and Whites 18-30 years of age at the time of initial examination. The initial examination included 5,115 participants selectively recruited to represent proportionate racial, gender, age, and education groups from 4 communities: Birmingham, AL; Chicago, IL; Minneapolis, MN; and Oakland, CA. Participants from the Birmingham, Chicago, and Minneapolis centers were recruited from the total community or from selected census tracts. Participants from the Oakland center were randomly recruited from the Kaiser-Permanente health plan membership. From the time of initiation of the study in 1985-1986, five follow-up examinations have been conducted at years 2, 5, 7, 10, 15, and 20. The Year 25 examination is scheduled to begin in 2010. This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org) funded by the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors associated with variation in longitudinal blood pressure profiles during the critical transition period from young adulthood to early middle-age; and to characterize their interactions with relevant environmental factors, such as body weight profiles. Genotyping was performed at the Broad Institute of MIT and Harvard, a GENEVA genotyping center. Data cleaning and harmonization were performed at the GEI-funded GENEVA Coordinating Center at the University of Washington.

  Study phs000309

• Type 1 Diabetes Genetics Consortium (T1DGC): Multi-Ethnic ImmunoChip Study

  Type 1 diabetes (T1D) is characterized by an autoimmune attack that destroys the insulin-producing pancreatic beta cells and is driven by diverse genetic and environmental factors. Between 8-100 chromosome regions are known to contain variants that alter T1D risk, substantially fewer than many other common diseases. Less is known about the contribution of T1D risk alleles in non-European populations, despite recent increases in T1D diagnoses in multiple non-European ancestry groups. To address these gaps in T1D genetics, we doubled the sample size from the previous largest T1D association study, genotyped ancestrally diverse T1D cases, controls, and affected families with the Illumina ImmunoChip array, and imputed additional variants using a large haplotype reference panel. After quality filtering, a total of 61,427 participants and 140,333 genotyped ImmunoChip variants were included in analysis, providing dense coverage in 188 autosomal regions ("ImmunoChip regions") and sparse genotyping in other regions of the genome. Each participant was assigned to one of five ancestry groups using k-means clustering of ImmunoChip genotype principal components: European (EUR, N = 47,319), African Admixed (AFR, N = 4,290), Finnish (FIN, N = 6,991), East Asian (EAS, N = 588) and Other Admixed (AMR, N = 2,239). In total, 16,159 T1D cases, 25,386 controls (unrelated) and 6,143 trio families (i.e., an affected child and both parents) were genotyped and included in association analyses. Imputation with the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) multi-ethnic reference panel was used to improve discovery power and fine-mapping resolution. After imputation, the number of variants in ImmunoChip regions with imputation R-squared > 0.8 and MAF > 0.005 in each ancestry group was 322,084 (AFR), 166,274 (EUR), 163,612 (FIN), 137,730 (EAS) and 188,550 (AMR). Imputed genotypes were compared in the same participants who have whole genome sequencing data, resulting in high concordance. Unrelated cases and controls (N = 41,545) were analyzed initially, assuming an additive inheritance model. T1D trio families (N = 6,143 trios, some trio families were multiplex and analyzed as multiple trios) were analyzed separately, with meta-analysis of case-control and trio results used for discovery of regions associated with T1D (p < 5×10-8). Summary-level data at each SNP (genotype and imputed) for type 1 diabetes (outcome) are provided in dbGaP.

  Study phs002468

• Phase II Study of Cryoablation and Post-Progression Immune Checkpoint Inhibition in Metastatic Melanoma

  Percutaneous cryoablation guided by imaging is a well-established, minimally invasive treatment for oncological conditions. We posited that cryoablation could alter the immune microenvironment by directly influencing the tumor, potentially eliciting an anti-tumor response in cases resistant to immune checkpoint inhibition (ICI). In this non-randomized phase II single-center study (NCT03290677), individuals with unresectable melanoma experiencing progression on ICI underwent cryoablation in a single progressing metastasis, while ICI was continued for at least two additional cycles. The main objectives were to assess safety and feasibility and to evaluate tumor response in non-ablated lesions. Between May 2018 and July 2020, 17 patients participated in the study. The treatment regimen proved safe, revealing an objective response rate of 23.5% and a disease control rate of 41% (comprising 4 partial responses and 3 stable diseases). In our investigation into the factors influencing response to cryoablation therapy in ICI-resistant melanoma, we conducted single-cell RNA sequencing (scRNA-seq) using both 10x Genomics and Smart-seq2 technologies on biopsies from metastatic sites of 15 patients. We collected pre-treatment samples from all patients and post-treatment samples from 5 patients, totaling 20 samples. After quality control, excluding cells specific to anatomical sites or rare cell types (e.g., alveolar type II, neurons), and batch correction, we analyzed 49,071 single cells spanning melanocyte, endothelial, stromal, T, myeloid, and B/plasma cell lineages. Differential gene expression (DGE) analysis between myeloid cells identified the genes MARCKS and IL10, two genes involved in anti-inflammatory responses that can inhibit macrophages activation to be associated with failed response. Moreover, DGE analysis of T cells identified the gene TXK, which acts as a Th1 transcription factor, and the gene CMKLR1 (chemerin-like-receptor-1), which triggers migration of CD8 T-cells to be upregulated in patients who benefited from cryoablation treatment. In contrast, MTHFD2 and GGH, two genes involved in one-carbon metabolism and the folate cycle, were upregulated in T cells from patients who did not respond to therapy. Our analysis revealed a significant increase in B/plasma cells in patients who responded positively to the therapy combination, along with an enrichment of oxidative phosphorylation in T cells among non-responsive patients with progressive disease. These findings advocate for further investigation into this innovative and synergistic therapeutic approach.

  Study phs003579

• Lung Health Study (LHS-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 determine the effects of Special Care, compared to Usual Care, on rate of decline in pulmonary function in a group of cigarette smokers identified as having mild abnormalities in pulmonary function. In addition, the study sought to determine if participants with chronic obstructive pulmonary disease, who were assigned to inhaled corticosteroids had a lower rate of decline in lung function and lower incidence of respiratory morbidity compared to participants assigned to placebo. Also, the study sought to determine the long-term effects of smoking cessation and continued smoking, on cardiopulmonary morbidity, mortality, and the rate of decline in the one second forced expiratory volume in men and women with early chronic obstructive lung disease who have been followed prospectively for 12 to 15 years.Participants: A total of 5887 participants were enrolled.Conclusions: Participants in the two smoking intervention groups showed significantly smaller declines in Forced Expiratory Volume 1 (FEV1) than did those in the control group. Most of this difference occurred during the first year following entry into the study and was attributable to smoking cessation, with those who achieved sustained smoking cessation experiencing the largest benefit. The small noncumulative benefit associated with use of the active bronchodilator vanished after the bronchodilator was discontinued at the end of the study. The authors concluded that an aggressive smoking intervention program significantly reduced the age-related decline in FEV1 in middle-aged smokers with mild airways obstruction. Use of an inhaled anticholinergic bronchodilator resulted in a relatively small improvement in FEV1 that appeared to be reversed after the drug was discontinued. Use of the bronchodilator did not influence the long-term decline of FEV1. Additionally, the study showed that lung function decline in the participants treated with the inhaled corticosteroid was statistically no different from that in the placebo group. Corticosteroid use did, however, result in 25 percent fewer respiratory symptoms and nearly 50 percent fewer outpatient visits for respiratory problems. However, after three years, bone density in the hip and back was lower in the corticosteroid group.

  Study phs004013

• Losartan Effects on Emphysema Progression (LEEP-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 evaluate the efficacy of losartan, an angiotensin receptor blocker, to reduce emphysema progression in patients with COPD and mild to moderate emphysema. Background Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease comprising chronic bronchitis and emphysema. COPD is a major cause of morbidity and mortality. Smoking cessation slows the progression of the disease, and bronchodilators can provide sustained improvement in lung function, but there are no pharmacologic agents that clearly modify emphysema progression. Angiotensin receptor blockers (ARBs) have been suggested as potential drugs to slow the progression of COPD. A few trials have shown that patients treated with ARBs had slower progression of radiographic emphysema. The LEEP study was initiated to test the hypothesis that the ARB losartan would reduce the progression of emphysema in patients with COPD with mild to moderate emphysema.ParticipantsA total of 220 participants were enrolled. 108 participants were randomized to receive losartan, and 112 participants were randomized to receive the placebo.Design LEEP was a randomized, placebo-controlled multicenter trial. Participants were randomly assigned (1:1) to receive losartan or placebo. The dose was 50 mg losartan or placebo given as one capsule daily for 2 weeks, and, if well tolerated and the systolic blood pressure was >90 mm Hg, it was increased to two capsules. Participants and site investigators were masked to treatment assignment. Participant responses to the St George's Respiratory Questionnaire, the modified Medical Research Council dyspnea scale, the COPD Assessment Test, and the Physical Function–Short Form 20a were collected. The number and severity of COPD exacerbations were recorded. COPD exacerbations were defined as two or more new or worse symptoms for ≥3 days and classified by treatment as mild (neither antibiotics nor oral steroids), moderate (an antibiotic or oral steroid), or severe (hospitalization). The primary outcome measure was the change in quantitative whole-lung emphysema score after 48 weeks measured by the percentage of lung voxels less than -950 Hounsfield units (PCT950) on full inspiratory HRCT. Conclusions Losartan does not prevent progression of emphysema in patients with COPD who have mild to moderate pulmonary emphysema.

  Study phs004313

• Genome_Diversity_in_Africa_Project___GemCode_libraries

  Globally, human populations show structured genetic diversity as a result of geographical dispersion, selection and drift. Understanding this genetic variation can provide insights into the evolutionary processes that shape both human adaptation and variation in disease. Populations from Africa have the highest levels of genetic diversity. This characteristic, in addition to historical genetic admixture, can lead to complexities in the design of studies assessing the genetic determinants of disease and human variation. However, such studies of African populations are also likely to provide new opportunities to discover novel disease susceptibility loci and variants and refine gene–disease association signals. A systematic assessment of genetic diversity within Africa would facilitate genomic epidemiological studies in the region.The Genome Diversity in Africa Project (GDAP) will extend and expand the African Genome Variation (AGV) project, an international collaboration aimed to produce a comprehensive catalogue of human genetic variation in Sub-Saharan Africa (SSA). Using a sequencing-based approach, GDA project aims to capture human genetic variation in Africa, including single nucleotide polymorphisms (SNPs), structural variants, and haplotypes. This resource will make a substantial contribution to understanding patterns of genetic diversity within and among populations in Africa, as well as providing a global resource to help design, implement and interpret genomic studies in African populations and studies comprising globally diverse populations, complementing existing genomic resources. Specifically, we plan to carry out whole genome sequencing at high depth (30x) of up to 1000 individuals across Africa (25 individuals from each ethnolinguistic group). We have already completed sequencing from 5 ethno-linguistic groups and we are now adding others.Our scientific objectives are to: 1) develop a resource that provides a comprehensive catalogue of genetic variation in populations from Africa accessible to the global scientific community; 2) characterise population genetic diversity, structure, gene flow and admixture across Africa; 3) develop a cost-efficient, next-generation genotype array for diverse populations across Africa; and 4) facilitate whole genome-sequencing association studies of complex traits and diseases by developing a reference panel for imputation and resource for enhancing fine-mapping disease susceptibility loci. These scientific objectives will be supported by cross-cutting operational activities, including network and management of the consortium, research ethics, and research capacity building in statistical genetics and bioinformatics.

  Study EGAS00001001589

• Clinical and Molecular Investigation of Familial CEBPA-mutated Acute Myeloid Leukaemia

  Myelodysplastic syndromes (MDS) and acute myeloid leukaemia (AML) are clonal diseases arising from the sequential acquisition of genetic aberrations in haematopoietic stem cells. Whilst the aetiology is predominantly sporadic, rare reports describe the autosomal dominant inheritance of MDS and AML (familial MDS/AML), often presenting in younger patients (<40 years of age) with a germline mutation in one of three haematopoietic transcription factors: RUNX1, CEBPA and GATA2. The clinical recognition of familial disease can be challenging due to wide variations in phenotype, latency and transmission, complicated further by the patients’ awareness and reporting of affected relatives. Distinct clinical manifestations have however been reported for each genetic subtype and whilst RUNX1 and GATA2 mutations can harbour prolonged dysplastic or cytopenic phases, germline CEBPA mutations universally present with AML de novo. Our group were the first to describe germline CEBPA mutations in 3 related individuals, all of whom developed AML between 10-30 years of age. The initial pedigree together with those described in the intervening period, were predominantly isolated case reports with limited follow up, hence long term outcomes for this group of patients remain poorly defined. This contrasts with CEBPA mutations occurring in 10-15% of sporadic AML with normal karytoype (NK-AML), where double mutations (CEBPAdm, found in approximately 50% of all CEBPA-AML) are considered a unique molecular entity, associated with favourable clinical outcomes. In sporadic and familial CEBPAdm AML, N’ terminal mutations enforce translation of the shorter P30-kDa isoform and are typically accompanied by C’ terminal insertions or deletions (disrupting the DNA-binding and/or Leucine zipper domains). Definition of the full molecular landscape awaits extensive whole exome sequencing, although GATA2 mutations (targeting the Zinc Finger 1, ZF1, domain) have been reported in 20-40% of sporadic CEBPAdm AML and recent targeted resequencing analysis revealed a further association with WT1 mutations. With minimal clinical and molecular information available for familial CEBPA-AML, we are often consulted regarding the management of this unique patient population. To address this need, we have investigated a multi-centre cohort of families with germline CEBPA mutations, providing extended clinical follow up, whole exome profiling of secondary mutations and molecular analysis of relapsed disease.

  Study EGAS00001000949

• Conjunctival fibrosis and the innate barriers to Chlamydia trachomatis intracellular infection: a genome wide association study

  This data comes from a genome-wide association study in 1090 cases of scarring trachoma and 1531 controls from a non-selected multi-ethnic sampling of The Gambia. The data constitutes hard base calls at 1457295 features from the HumanOmni2.5-8 (Omni2.5) BeadChip. Three genotype-calling algorithms were used : Illuminus (Bioinformatics 2007, 23:2741–6), GenCall (Patent US7035740, 2006) and GenoSNP (Bioinformatics 2008, 24:2209–14). Data from each calling algorithm was filtered to retain only SNPs with a call rate ≥ 0.98. To obtain a merged set of SNPs, all genotypes that matched across call-sets were retained, whilst those that mismatched between call-sets were set to missing. Genotypes that were present in one call set and missing in others were also retained. The merged SNP set contained 1467876 SNPs, which were filtered for call rate ≥ 0.99 and Hardy-Weinberg equilibrium P value < 5 x 10-8. The case and control groups were approximately equivalent with respect to gender and ethnicity. 70% of cases and 63% of controls were female. Self-described ethnic composition of the cases was 29% Jola, 27% Mandinka, 21% Wolof, 10% Fula and 13% other/no data. In controls the composition was 25% Jola, 24% Mandinka, 21% Wolof, 8% Fula and 22% other/no data. Median age was 49 (range 32-60) in cases and 37 (range 12-52) in controls (t = -3.6019, P = 0.0003). This data set has substantial levels of population structure, which reflects extensive networks of pairwise kinship between participants. First pass tests of association in EMMAX (Nat Genet 2010, 42:348–54) led to genome-wide deflation of the test statistics (λ = 0.982 SE = 1.74e-05) that could be directly attributed to the differing age and gender distributions between cases and controls. Modelling the phenotype to adjust for age and gender successfully controlled for this and no genome-wide deviation from the null was subsequently observed (λ = 1.001, SE = 8.7 x 10-7). Neither principal components analysis (PCA) nor tests of proportional identity by state (IBS) variance in PLINK identified significant levels of within or between group genetic variance. The phenotypes submitted in the phenotypes file include both uncorrected (case/control status) and corrected (age and gender corrected case/control status) phenotypes, as well as age and self-described ethnicity.

  Study EGAS00001001516

• UK10K RARE COLOBOMA

  In the UK10K project we propose a series of complementary genetic approaches to find new low frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will analyse directly quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches. Ocular coloboma is the most common significant developmental eye defect with an incidence of ~1 in 5,000 live births. It results from failure of optic fissure closure during embryogenesis. The position and extent of the fusion failure dictates the clinical appearance and functional effect. ~30% of coloboma cases are associated with other systemic malformations. These UK10K samples will mostly comprise isolated coloboma cases without systemic involvement (aka non-syndromal coloboma). There is strong evidence from family studies that coloboma has a major genetic component with autosomal dominance being the most common pattern of inheritance. However, many cases are isolated or show complex patterns of familial clustering. The genes responsible for isolated coloboma are largely unknown, but in a small number of families mutations in SHH, CHX10, and PAX6 have been identified indicating marked genetic heterogeneity. Thus in addition to the clinical benefits of achieving a molecular diagnosis there are also major scientific advantages to identifying coloboma genes, as these are likely to provide insights into the complex process of optic fissure closure, that is critical to normal eye development. In the longer term, understanding the molecular basis of the disease may provide clues to therapeutic strategies.For further information with regard to this cohort please contact David Fitzpatrick (david.fitzpatrick@ed.ac.uk).

  Study EGAS00001000127

• UK10K_OBESITY_SCOOP

  In the UK10K project we propose a series of complementary genetic approaches to find new low frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will analyse directly quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches.The SCOOP samples are part of the Obesity group and will undergo exome sequencing. Severe Childhood Onset Obesity Project (SCOOP) is a sub-cohort of the Genetics Of Obesity Study (GOOS) cohort established by Sadaf Farooqi and Steve O’Rahilly at the University of Cambridge over the last 12 years. The GOOS cohort contains >4,000 patients of diverse geographic origin, many of whom have monogenic and syndromic forms of obesity, and includes patients that are offspring of consanguineous union. SCOOP is a subset of >1500 UK Caucasian patients with severe, early onset obesity (all patients have a BMI Standard Deviation Score (SDS) > 3 and obesity onset before the age of 10 years), in whom all known monogenic causes of obesity have been excluded. GWAS data on the SCOOP cohort will be available (WTCCC2 independent study) at the time of the start of this study. Data from this cohort has demonstrated that the prevalence of the common obesity risk alleles in FTO, MC4R and NEGR1 are amongst the highest within SCOOP, demonstrating its value also in the study of genetic variants with an impact on more common obesity. For further information with regard to this cohort please contact Sadaf Farooqi (isf20@medschl.cam.ac.uk).

  Study EGAS00001000124

• DNA methylation changes associated with hyperglycemia in type 1 diabetes

  This dataset includes DNA methylation profiles from 112 young with Type 1 Diabetes (T1D) at T1D diagnosis, who were longitudinally monitored for hyperglycemia over an average duration of 3 years. These datasets were generated using whole-genome bisulfite sequencing. It includes 1872 fastq files (i.e. 936 paired-end fastq files) generated through 150 bp paired-end sequencing on Illumina HiSeqX.

  Dac EGAC50000000237

• DAC for Human exome sequencing data from three family members reported in the publication

  Germline variants in UHRF1 are associated with multi-locus imprinting disturbance in humans and mice. Eguzkine Ochoa, Ilona Zvetkova, Sunwoo Lee, Nozomi Takahashi, Benoit Lan-Leung, Emma Hobson, Mahmoud Issa, Bryndis Yngvadottir, France Docquier, Fay Rodger, Dounia Foster-Hall, Graeme Clark, Ana Toribio, Ezequiel Martin, Leonardo Bottolo, Anne C Ferguson-Smith, Wolfgang Fischle, Miguel Constancia, Eamonn R Maher

  Dac EGAC50000000710

• Cancer Research UK Manchester Institute/ Cancer Research UK National Biomarker Centre Data Access Committee

  Cancer Research UK Manchester Institute/Cancer Research UK National Biomarker Centre Data Access Committee is created to • Review and approve data access requests. • Ensure data security and compliance with institutional and legal obligations. • Maintain accurate records of access decisions For questions or further information, please contact: Chair of the Data Access Committee: Caroline Wilkinson Email: dac@cruk.manchester.ac.uk

  Dac EGAC50000000795

• Early-onset Colorectal Cancer Study TOGETHER Data Access Committee

  The Early-onset Colorectal Cancer Study TOGETHER Data Access Committee (DAC) is responsible for reviewing requests to access sequencing and clinical data from the study. Access to the data is restricted to researchers with approved ethical clearance and scientifically valid research projects. Each request will be evaluated by the DAC to ensure compliance with participants’ informed consent and all applicable data protection regulations.

  Dac EGAC50000000752

• DAC Wachten Laboratory and Toma Laboratory, University of Bonn/University Hospital Bonn

  DAC for collaborative projects of the Wachten Laboratory (Institute of Innate Immunity, University of Bonn, University Hospital Bonn) and the Toma Laboratory (Institute of Pathology, University Hospital Bonn). Contact: Prof. Dr. Dagmar Wachten dwachten@uni-bonn.de Institute of Innate Immunity, University Hospital Bonn, University of Bonn, Germany Prof. Dr. Marieta I. Toma Marieta.Toma@ukbonn.de Institute of Pathology, University Hospital Bonn, Germany

  Dac EGAC50000000916

• Somatic copy number alterations profiling in non-small cell lung cancer and their correlation with clinical efficacy in first-line treatment

  Genomic data from FFPE tumor samples of 258 patients with non-small cell lung cancer (NSCLC), profiled by shallow whole-genome sequencing (sWGS) at 1x. The study aimed to characterize somatic copy number alterations (SCNAs) and SCNA burden to assess their clinical relevance for patient stratification across different first-line treatments.

  Dac EGAC50000000929

• WTCCC case-control study for Inflammatory Bowel Disease, T1D and RA - combined cases

  WTCCC genome-wide case-control association study using three disease collections together with the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000008

• RNA-seq and scRNA/TCR-seq data for publication: "Pharmacological inhibition of nonsense-mediated mRNA decay enhances anti-tumour immunity"

  RNA-seq and scRNA/TCR-seq data from patient-derived fragments (PDFs) analysed in publication by R. Vendramin, H. Fu, S. Fernandez Patel, Y. Zhao et al.

  Study EGAS50000001208

• Integrative modeling of tumor genomes and epigenomes for enhanced cancer diagnosis by cell-free DNA.

  3784 whole genome sequencing bam files were generated from plasma cell-free DNA of healthy individuals and patients with cancer. Paired reads were mapped to hg19 human reference genome.

  Study EGAS00001006553

• Prospective Lynch Syndrome Database entries

  These data have been used to produce cancer incidence results for https://pubmed.ncbi.nlm.nih.gov/37181409/ , https://pubmed.ncbi.nlm.nih.gov/40231433/ and https://plsd.eu as available in March 2026. The tables contain demographic information at individual level, individual cancer events with given age, as well as prophylactic and therapeutic surgeries to remove organs. The data have been de-identified to ensure anonymity.

  Dataset EGAD50000002468

• Integrated whole-genome and transcriptome sequencing reveals divergent evolutionary processes across biliary tract cancer subtypes (WTS data from biliary tract cancer molecular subtype study)

  WTS data for biliary tract cancer samples (Consensus molecular subtypes define distinct evolutionary trajectories of biliary tract cancers). The dataset includes tumour bam files sequenced on Illumina HiSeq/NovaSeq and aligned against GRCh38 (n=85 tumours)

  Dataset EGAD50000002529

• Bulk 3' mRNA-Sequencing of human ASC-derived kidney tubuloids

  Bulk 3' mRNA-Seq raw files (FASTQ) from human kidney tubuloids derived from 4 separate donors in collagen-based dome culture and suspension culture. Samples were collected for sequencing on day 7 of passage 3, 4, and 5. Total = 24 samples.

  Dataset EGAD50000002335

• Transcriptomics for UPST-SCCHN3 cohort

  Transcriptomics of Tumor samples on UPST-SCCHN3 cohort

  Dataset EGAD50000002179

• Spatial Dynamics of the Developing Human Heart

  68 paired-end raw FASTQ files obtained from 38 tissue sections across 16 hearts, spanning embryonic human heart development between 5.5 and 14 postconceptional weeks. Some libraries were re-sequenced for better coverage. The tissue sections were processed using the 10x Genomics Visium Gene Expression kit, and libraries were paired-end sequenced using Nextseq2000 (Illumina).

  Dataset EGAD50000001615

• scRNAseq dataset of myeloid cells from secondary lymphoid organs from lymphoma patients and controls

  This dataset contains fastq files from scRNAseq dataset of myeloid cells from secondary lymphoid organs (lymph nodes and tonsil) from lymphoma patients (3 FL and 3 DLBCL) and controls (3 reactive tonsils and 3 reactive lymph nodes). For HTO libraries, demultiplexing barcodes are available in samples descriptions.

  Dataset EGAD50000001629

• Human Paraganglioma

  This dataset comprises single-nucleus transcriptomic profiles from 9 human paraganglioma samples. Nuclei were isolated and processed using the SMART-Seq2 protocol to enable full-length, high-resolution RNA sequencing at the single-nucleus level. cDNA libraries were generated and sequenced on the Illumina HiSeq 2500 platform. The resulting raw sequencing data are provided as .fastq files for downstream analysis.

  Dataset EGAD50000001689

• Human Neuroblastoma

  This dataset comprises single-nucleus transcriptomic profiles from 10 human neuroblastoma samples. Nuclei were isolated and processed using the SMART-Seq2 protocol to enable full-length, high-resolution RNA sequencing at the single-nucleus level. cDNA libraries were generated and sequenced on the Illumina HiSeq 2500 platform. The resulting raw sequencing data are provided as .fastq files for downstream analysis.

  Dataset EGAD50000001596

• 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

• ResolveCRPS study - Transcriptomics

  Transcriptome profiling of CRPS-affected skin using low-input total RNA-seq (paired-end mode with 54 and 68 nt read length for R1 and R2 respectively, Illumination NextSeq2000). 42 snap-frozen skin biopsies were analyzed together with longitudinal clinical data. The dataset contains FASTQ files, the processed read count matrix, and the corresponding clinical metadata.

  Dataset EGAD50000001545

• ScRNA-seq of kidney organoids expressing different APOL1 variants and treated with IFN-γ

  This dataset includes scRNA-seq fastq files and Seurat counts and metadata for 3 samples of hiPSC-derived kidney organoid cells cultured in vitro in presence of IFN-γ. Samples were obtained from kidney organoids with APOL1 G1G1 variant, APOL1 G2G2 variant and an isogenic control.

  Dataset EGAD50000001743

• Citeseq of human bone marrow

  CITE-seq dataset of human bone marrow from four healthy donors. Single-cell RNA sequencing was performed using the 10x Genomics 3’ v3 platform. Approximately 7,000–10,000 cells were loaded in each 10x channel, after which the single-cell libraries were prepared according to manufacturer’s instructions, except for the added CITE-seq steps. Demultiplexed FASTQ files are provided.

  Dataset EGAD50000001211

• Saliva_Fulani_Database

  In total, 90 DNA samples were genotyped on the Illumina Infinium H3Africa Consortium array (designed for 2,271,503 SNPs; using BeadChip type: H3Africa_2019_20037295_B1). Genotyping was performed at the SNP&SEQ Technology Platform (NGI/SciLifeLab Genomics, Sweden). Saliva Fulani dataset includes individuals from the following populations: 30 individuals from Senegal_FulaniLinguere, 30 individuals from Mauritania_FulaniAssaba, and 30 individuals from Mali_FulaniInnerDelta.

  Dataset EGAD50000000653

• Metadata associated with sequencing

  Associated metadata for sequencing data.

  Dataset EGAD50000000528

• 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

• Synergy study: "Tissue resident CD8+ T cell clonal expansion in advanced triple negative breast cancer is associated with response to chemoimmunotherapy"

  Dataset of the study "Synergy study: "Tissue resident CD8+ T cell clonal expansion in advanced triple negative breast cancer is associated with response to chemoimmunotherapy". This dataset contains the cellranger's gene-expression matrices for the 5 prime single-cell RNA sequencing experiments

  Dataset EGAD50000000748

• Malagasy Genomics University of Antananarivo Dataset

  Mid-pass whole genome sequencing was performed for 264 Malagasy individuals across three geographic regions across the island of Madagascar (west coast, central highlands, and southern highlands). This dataset includes the VCF from joint variant calling with reference populations as specified in the associated publication.

  Dataset EGAD50000000708

• Cas9-targeted-based long-read sequencing for genetic screening of RPE65 locus

  The dataset includes sequencing data from five inherited retinal dystrophies (IRD) patients using three diferent platforms: Clinical Exome (CES), Long-read sequencing of RPE65 locus, and 3) whole genome sequencing.

  Dataset EGAD50000000847

• RNAseq RPKM

  RNA-seq data from ILC samples. This dataset includes counts normalized for sequencing depth and gene length.

  Dataset EGAD50000000828

• RNA_TPO3_2023

  Human engineered CRC organoids (APC KO; KRAS G12D; TP53 KO) were grown in either glucose or lactate, in the presence and absence of DCA or BRD4 inhibition (JQ1). Samples were collected and processed for bulk RNA-seq.

  Dataset EGAD50000000089

• Methylation Array data for: Three-dimensional patient-derived models of glioblastoma retain intra-tumoral heterogeneity

  3 sets of matched patient-derived-organoids (PDOs),  -neurospheres (PDNs), and parent glioblastoma tissue (9 samples total) underwent methylation array analysis. 200ng of each sample DNA extracted via a commercial kit (Qiagen) and loaded onto the Illumina EPIC v2.0 array. Data is provided as raw red and green .idat files.

  Dataset EGAD00010002745