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• Single-Cell DNA Methylation Profiling via scTAMseq

  This dataset comprises single-cell DNA methylation and nuclear genotyping profiles of 7 total bone marrow aspirates (donors A.1-A.7) and 5 CD34+-enriched bone marrow samples (donors B.1-B.5) generated using the scTAMseq protocol. Sequencing was performed on the Mission Bio Tapestri platform, targeting a panel of 448 CpGs to assess epigenetic patterns and We also included 147 genomic regions commonly mutated in clonal hematopoiesis and 20 regions targeting chromosome Y. Samples B.1 & B.5, B.2 & B.4 and A.2 & A.5 were, in pairs, multiplexed into single tapestri lanes.

  Dataset EGAD00001015498

• Circulating Biomarker Laboratory within the Division of Cancer of Imperial College London

  The purpose of the Circulating Biomarker Laboratory within the Division of Cancer of Imperial College London (ICL) is to assist ICL researchers working on solid tumours or/and haematological malignancies with a particular interest in the analysis of liquid biopsies. We are focusing on isolating and analysing single circulating tumour cells (CTCs) and cell-free circulating tumour DNA (ctDNA) from cancer patients' blood samples but also pure tumour poulations from heterogeneous Formalin-fixed paraffin-embedded (FFPE) tissue specimens with a view to monitoring tumour-related changes, such as mutations and copy number alterations at a single cell level.

  Dac EGAC50000000768

• Peruvian Genome Project

  Through the Peruvian Genome Project we generate and analyze the high coverage genomes of 150 individuals where the majority have >90% Native American ancestry and explore questions at the interface of evolutionary genetics, history, anthropology, and medicine. This is the most extensive sampling of high-coverage Native American and mestizo whole genomes to date. Reference: https://doi.org/10.1073/pnas.1720798115

  Dataset EGAD00001007082

• WGS data of paediatric TCF3::PBX1 acute lymphoblastic leukemia (set2)

  The dataset includes FASTQ and BAM files from diagnostic and matched remission (control) samples of one TCF3::PBX1 ALL patient (ALLT-376). Sequencing library was made using PCR free-based WGS library preparation (PCR-), using NEB Next® Ultra™ DNA Library Prep Kit. Both diagnostic (90x) and remission (30x) samples were sequenced using HiSeq X.

  Dataset EGAD50000001795

• WGS data of pediatric TCF3::PBX1 acute lymphoblastic leukemia (set1)

  The dataset includes FASTQ and BAM files from diagnostic and matched remission (control) samples of one TCF3::PBX1 ALL patient (ALLT-335). Sequencing library was made using standard PCR-based WGS library preparation (PCR+), using NEB Next® Ultra™ DNA Library Prep Kit. Both diagnostic (90x) and remission (30x) samples were sequenced using HiSeq X.

  Dataset EGAD50000001796

• WGS data of paediatric BCR::ABL1 acute lymphoblastic leukemia

  The dataset includes FASTQ and CRAM files from diagnostic and matched remission (control) samples of one BCR::ABL1 ALL patient (ALLT-399). Sequencing library was made using PCR free-based WGS library preparation (PCR-), using Novogene NGS DNA Library Prep Set Kit (Cat No. PT004). Both diagnostic (90x) and remission (30x) samples were sequenced using NovaSeqX Plus.

  Dataset EGAD50000002185

• WGS data of paediatric B-other B cell acute lymphoblastic leukemia (set5)

  The dataset includes FASTQ and BAM/CRAM files from diagnostic and matched remission (control) samples of two B-other ALL patients (ALLT-396, ALLK-131). Sequencing library was made using PCR free-based WGS library preparation (PCR-), using Novogene NGS DNA Library Prep Set. Both diagnostic (90x) and remission (30x) samples were sequenced using NovaSeqX Plus.

  Dataset EGAD50000002160

• Hereditary Gastric Cancer Syndromes: An Integrated Genomic and Clinicopathologic Study of the Predisposition to Gastric Cancer

  Gastric cancers are cancers of the stomach. Hereditary cancers are passed from parent to child. Researchers want to gather data about hereditary gastric cancers. Bulk RNA sequencing (RNA-seq) of signet ring cells (SRCs) and adjacent non-SRC epithelium (NEP) was performed on laser-capture microdissected (LCM) regions of interest found in risk-reducing total gastrectomy specimens from hereditary diffuse gastric cancer (HDGC) patients (Clinicaltrials.gov ID: NCT03030404). Twenty patients (6 male, 14 female) with confirmed HDGC were identified. Analysis of differentially expressed genes (DEGs) demonstrated upregulation of certain individual epithelial–mesenchymal transition (EMT) and proliferation genes. SRC regions had significant enrichment in pathways involved in T cell signaling. CIBERSORTx predicted significant increases in the presence of regulatory T cells (Tregs) specific to SRC regions.

  Study phs003422

• Metastatic Colorectal Adenocarcinoma Tumor Purity Assessment from Whole Exome Sequencing Data

  As molecular medicine wields greater and greater influence on cancer patient care, including therapeutic selection, it becomes increasingly important to understand the power and deficiencies of computational tools used in decision making processes. Here we use a set of unselected metastatic colorectal tumor samples in a head-to-head comparison between the calculation of stromal content by a board certified pathologist, versus that derived from whole exome sequencing and purity assessment by a variety of common computational methods. We find that in about 1/2 of the samples the computational methods each do a poor job of assessing the percent stromal contamination, and as a result, tumor variant allele frequencies (VAFs) are low or undetected, whereas analysis of organoids derived from the same tumors yielded much higher VAFs in keeping with their lower stromal content. The whole exome sequence of our samples is available via dbGaP, accession phs003059.v1.p1.

  Study phs003059

• RNA-sequencing of PBMCs from COVID-19 patients experiencing different degrees of the disease (mild and critical), and control patients

  Bulk RNA-sequencing of peripheral blood mononuclear cells collected from mild COVID-19 (n = 4), critical COVID-19 (n = 12) and control (n = 8) patients. Sequencing data is provided as FASTQ files.

  Dataset EGAD50000001405

• Whole genome sequencing of Cas9 repaired cystic fibrosis organoids description

  Three SpCas9-ABE (R785X/R785X) and three xCas9-ABE-repaired organoid clones (F508del/R553X) and their respective unrepaired control organoids were paired-end whole genome sequenced using Illumina Novaseq 6000 system. The reads were mapped to hg19 genome assembly and data is provided as BAM files.

  Dataset EGAD00001005427

• Durvalumab Plus Tremelimumab Alone or in Combination with Low-Dose or Hypofractionated Radiotherapy in Metastatic Non-Small-Cell Lung Cancer Refractory to Previous PD(L)-1 Therapy: an Open-Label, Multicentre, Randomised, Phase 2 Trial

  Brief SummaryThis randomized phase II trial studies the side effects of durvalumab and tremelimumab and to see how well they work with or without high or low-dose radiation therapy in treating patients with colorectal or non-small cell lung cancer that has spread to other parts of the body (metastatic). Immunotherapy with durvalumab and tremelimumab, may induce changes in body's immune system and may interfere with the ability of tumor cells to grow and spread. Radiation therapy uses high energy x-rays to kill tumor cells and shrink tumors. Giving durvalumab and tremelimumab with radiation therapy may work better in treating patients with colorectal or non-small cell lung cancer.Detailed DescriptionPRIMARY OBJECTIVES:I. To assess safety and tolerability of combined checkpoint blockade with MEDI4736 (durvalumab) and tremelimumab alone or with high or low-dose radiation in non-small cell lung cancer (NSCLC). (NSCLC Cohort) II. To compare the overall response (excluding the irradiated lesion[s]) between combined checkpoint blockade with MEDI4736 and tremelimumab alone or combined checkpoint blockade with low or high dose radiation. (NSCLC Cohort) III. To assess safety and tolerability of combined checkpoint blockade with MEDI4736 and tremelimumab with high or low-dose radiation. (Colorectal Cohort) IV. To determine the overall response rate (excluding the irradiated lesion[s]) with combined checkpoint blockade with MEDI4736 and tremelimumab with either low or high dose radiation. (Colorectal Cohort)SECONDARY OBJECTIVES:I. To estimate median progression-free survival and overall survival. (NSCLC Cohort) II. To determine local control within the irradiated field(s) and abscopal response rates. (NSCLC Cohort) III. To evaluate associations between PD-L1 expression as well as levels of infiltrating CD3+, CD8+ T-cells and overall response. (NSCLC Cohort) IV. To explore changes in PD-L1 expression, circulating T-cell populations, T-cell infiltration, ribonucleic acid (RNA) expression, spatial relationship of immune markers, and mutational burden as a result of low or high dose radiation. (NSCLC Cohort) V. To estimate median progression-free survival and overall survival. (Colorectal Cohort) VI. To determine local control within the irradiated field and abscopal response rates. (Colorectal Cohort) VII. To evaluate associations between PD-L1 expression as well as levels of infiltrating CD3+ CD8+ T-cells and overall response. (Colorectal Cohort) VIII. To evaluate changes between PD-L1 expression as well as levels of infiltrating CD3+, CD8+ T-cells induced by targeted low or high dose radiation. (Colorectal Cohort) IX. To explore changes in circulating T-cell populations, T-cell infiltration, RNA expression, spatial relationship of immune markers, and mutational burden as a result of low or high dose radiation. (Colorectal Cohort)OUTLINE: Patients are assigned to 1 of 2 cohorts. NOTE: This Study is only for Cohort 1. Please see phs003294 for Cohort 2COHORT 1: Patients with NSCLC are randomized to 1 of 3 arms.ARM A: Patients receive tremelimumab and durvalumab and as in Arm C. Beginning at week 2, patients receive high dose radiation therapy once per day (QD) over 10 days for up to 3 fractions.ARM B: Patients receive tremelimumab and durvalumab and as in Arm C. Beginning at week 2, patients receive low dose radiation therapy every 6 hours twice per day (BID) on weeks 2, 6, 10 and 14.ARM C: Patients receive tremelimumab intravenously (IV) and durvalumab IV over 60 minutes every 4 weeks for up to 16 weeks in the absence of disease progression or unacceptable toxicity. Patients then receive durvalumab IV over 60 minutes 4 weeks after last combination dose for up to 9 additional doses.COHORT 2: Patients with CRC are randomized to 1 of 2 arms.ARM A: Patients receive tremelimumab intravenously (IV) and durvalumab IV over 60 minutes every 4 weeks for up to 16 weeks in the absence of disease progression or unacceptable toxicity. Patients then receive durvalumab IV over 60 minutes 4 weeks after last combination dose for up to 9 additional doses. Beginning at week 2, patients receive high dose radiation therapy once per day (QD) over 10 days for up to 3 fractions.ARM B: Patients receive tremelimumab intravenously (IV) and durvalumab IV over 60 minutes every 4 weeks for up to 16 weeks in the absence of disease progression or unacceptable toxicity. Patients then receive durvalumab IV over 60 minutes 4 weeks after last combination dose for up to 9 additional doses. Beginning at week 2, patients receive low dose radiation therapy every 6 hours twice per day (BID) on weeks 2, 6, 10 and 14.After completion of study treatment, patients are followed for up to 12 weeks.Official TitleA Phase 2 Study of MEDI4736 (Durvalumab) and Tremelimumab Alone or in Combination With High or Low-Dose Radiation in Metastatic Colorectal and NSCLC Conditions Metastatic Colorectal CarcinomaMetastatic Lung Non-Small Cell CarcinomaStage IV Colorectal Cancer AJCC v7Stage IV Lung Non-Small Cell Cancer AJCC v7Stage IVA Colorectal Cancer AJCC v7Stage IVB Colorectal Cancer AJCC v7 Intervention/Treatment Biological: DurvalumabRadiation: Radiation TherapyBiological: Tremelimumab Other Study ID Numbers NCI-2016-01325NCI-2016-01325 ( Registry Identifier ) (REGISTRY: CTRP (Clinical Trial Reporting Program))17-71910021 ( Other Identifier ) (OTHER: Dana-Farber - Harvard Cancer Center LAO)10021 ( Other Identifier ) (OTHER: CTEP) Molecular Technologies / AssaysCyTOFIHCmIFOlinkRNAseqWES

  Study phs003295

• Single-cell RNA sequencing of CML patients

  This dataset contains 15 single-cell RNA sequencing samples from 6 CML patients before and after TKI-cessation. The raw data is available as fastq files.

  Dataset EGAD00001012842

• Genomic Evolution of Breast Cancer Metastasis and Relapse

  Recurrent breast cancer is almost universally fatal. We characterize 170 patients locally relapsed or distant metastatic cancers using massively parallel sequencing. We identify that the relapse-seeding clone disseminates late from the primary tumor. TP53 and AKT1 appear to be enriched in ER-positive cancers predisposed to relapse. Mutation acquisition continues at relapse as the same mutation signatures continue to operate and new signatures, such as that caused by radiotherapy appear de novo. In 49% of cases we identify drivers mutations private to the relapse and these are sampled from a wider range of cancer genes, including SWI-SNF complex and JAK-STAT signaling.

  Dataset EGAD00001002697

• Bulk and single-cell RNA sequencing of LCP1-mutated patients

  This dataset contains bulk RNA-seq and single-cell RNA-seq (scRNA-seq) of bone marrow obtained from 2 patients diagnosed with severe congenital neutropenia (SCN) attributed to LCP1 mutations. This is the first dataset of its kind. Moreover, the dataset also contains scRNA-seq of bone marrow derived from a healthy control.

  Dataset EGAD00001015698

• PPIL4 is essential for brain angiogenesis and implicated in intracranial aneurysm in humans

  Rupture of intracranial aneurysms (IAs) leads to subarachnoid hemorrhage (SAH), a sudden-onset disease often causing severe disability or death. Using whole exome sequencing, we identified significant enrichment of rare, deleterious mutations in PPIL4 in both index and familial IA cases. Ppil4 depletion causes intracerebral hemorrhage, defects in cerebrovascular morphology, and impaired Wnt signaling in vivo. Wild type, but not IA-mutant PPIL4, potentiates Wnt signaling by binding JMJD6, a known angiogenesis regulator and Wnt activator. These findings identify a novel PPIL4-dependent Wnt signaling mechanism involved in brain-specific angiogenesis and maintenance of cerebrovascular integrity, and implicate PPIL4 gene variation in the pathogenesis of human IA.

  Study EGAS00001005518

• Long-read single-cell RNA-seq in COVID-19

  We report the first application of long-read single-cell RNA sequencing on nasopharyngeal swabs from COVID-19 patients and healthy controls to resolve transcript-level changes across cell types. Samples were collected from three patients with moderate COVID-19, six patients with critical COVID-19, and three healthy controls. Single-cell libraries were generated using the 10x Genomics Chromium 3' protocol, producing unfragmented cDNA. Libraries were sequenced on the Oxford Nanopore Technologies PromethION platform. Basecalling was performed with Guppy (v1.6), generating a single FASTQ file per sample.

  Dataset EGAD50000001836

• ImmunAID

  The ImmunAID study is a multi-center research program aimed at improving the diagnosis and understanding of systemic autoinflammatory diseases. The study integrates immunological, and molecular data from patients across several European cohorts. Its objective is to identify biomarkers and biological pathways that characterize disease mechanisms and help differentiate between inflammatory conditions. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 779295. The project has generated genomic datasets, which are available through the European Genome-phenome Archive (EGA). In addition, it has produced several non-genomic datasets, listed below. All datasets have been fully anonymized in accordance with applicable ethical and regulatory frameworks. These non-genomic data are available upon request. To request access to these datasets, please contact: immunaid2024@gmail.com Your request will be studied by the Data Access Committee, and data will be made available upon approval. Non-genomic datasets available: Flow cytometry (general immune phenotype) — Dataset ID: ICKD2021569, size: 23 GB, 342 patients Somascan proteomics data — Dataset ID: ICKD2021570, size: 59 MB, 444 patients ELISA panel (Ferritin, CRP, HO1, IL-1B, IL-6, IL-8, IL-10, IL-12, IL-18, IFN-γ, TNF-α) — Dataset ID: ICKD2021571, size: 295 KB, 439 patients Mass spectrometry (MS/MS) — Dataset ID: ICKD2021572, size: 1.8 TB, 447 patients ELISA (CRP/ SAA) — Dataset ID: ICKD2021573, size: 321 KB, 443 patients Flow cytometry (inflammasome activity) — Dataset ID: ICKD2021574, size: 899 KB, 307 patients Plasma lipidomics — Dataset ID: ICKD2021575, size: 1.1 MB, 427 patients Urine lipidomics — Dataset ID: ICKD2021576, size: 833 KB, 368 patients ELISA (alarmins) — Dataset ID: ICKD2021577, size: 129 KB, 108 patients ELISA (IL-18 / IL-1) — Dataset ID: ICKD2021578, size: 271 KB, 330 patients Flow cytometry (NK cell alterations) — Dataset ID: ICKD2021579, size: 14 GB, 216 patients Chemokine measurements — Dataset ID: ICKD2021580, size: 489 KB, 404 patients Luminex (multiple analyte measurements) — Dataset ID: ICKD2021581, size: 759 KB, 369 patients

  Study EGAS50000001393

• Genetic Analysis of Syndromic Orofacial Clefting

  The goal of this study is to identify previously unknown genetic causes of human syndromic cleft lip/palate by using genome sequencing. Many previous studies have shown that isolated cleft lip and/or palate are not often likely to be monogenic or Mendelian diseases. We hope that by focusing on syndromic presentations, we will find novel causes of disorders which include orofacial clefting among their phenotype(s). Data provided will be fastq files from sequencing partners.

  Study phs002997

• CLUSTER Consortium RNAseq CD19 Dataset of pre-methotrexate UK JIA patients cohort

  This is the RNAseq CD19 dataset (paired FASTQ files, n = 83 paired files) generated from pre-methotrexate treatment JIA patients cohort samples. CD19 cells were sorted from isolated total PBMC by cell sorter (BD FACSAriaTM III, BD Biosciences). Clinical metadata is also included in this dataset. Samples were sequenced on the NovaSeq6000 instrument (Illumina, San Diego, US) at 300pM, using a 100bp paired read run with corresponding 8bp dual sample index and 5bp or 8bp unique molecular index reads. Run data were demultiplexed and converted to FASTQ files using Illumina’s BCL Convert Software v3.75.

  Dataset EGAD50000001459

• CLUSTER Consortium RNAseq CD14 Dataset of pre-methotrexate UK JIA patients cohort

  This is the RNAseq CD14 dataset (paired FASTQ files, n = 80 paired files) generated from pre-methotrexate treatment JIA patients cohort samples. CD14 cells were sorted from isolated total PBMC by cell sorter (BD FACSAriaTM III, BD Biosciences). Clinical metadata is also included in this dataset. Samples were sequenced on the NovaSeq6000 instrument (Illumina, San Diego, US) at 300pM, using a 100bp paired read run with corresponding 8bp dual sample index and 5bp or 8bp unique molecular index reads. Run data were demultiplexed and converted to FASTQ files using Illumina’s BCL Convert Software v3.75.

  Dataset EGAD50000001458

• CLUSTER Consortium RNAseq CD8 Dataset of pre-methotrexate UK JIA patients cohort

  This is the RNAseq CD8 dataset (paired FASTQ files, n = 85 paired files) generated from pre-methotrexate treatment JIA patients cohort samples. CD8 cells were sorted from isolated total PBMC by cell sorter (BD FACSAriaTM III, BD Biosciences). Clinical metadata is also included in this dataset. Samples were sequenced on the NovaSeq6000 instrument (Illumina, San Diego, US) at 300pM, using a 100bp paired read run with corresponding 8bp dual sample index and 5bp or 8bp unique molecular index reads. Run data were demultiplexed and converted to FASTQ files using Illumina’s BCL Convert Software v3.75.

  Dataset EGAD50000001456

• CLUSTER Consortium RNAseq CD4 Dataset of pre-methotrexate UK JIA patients cohort

  This is the RNAseq CD4 dataset (paired FASTQ files, n = 86 paired files) generated from pre-methotrexate treatment JIA patients cohort samples. CD4 cells were sorted from isolated total PBMC by cell sorter (BD FACSAriaTM III, BD Biosciences). Clinical metadata is also included in this dataset. Samples were sequenced on the NovaSeq6000 instrument (Illumina, San Diego, US) at 300pM, using a 100bp paired read run with corresponding 8bp dual sample index and 5bp or 8bp unique molecular index reads. Run data were demultiplexed and converted to FASTQ files using Illumina’s BCL Convert Software v3.75.

  Dataset EGAD50000001455

• Profiling of 27 type 2 diabetes GWAS loci using next-generation (NG) capture C in a human beta-cell model

  Most type 2 diabetes association signals are due to variants that impact gene regulation but identifying the genes they impact is challenging. We generated interaction profiles at 27 T2D GWAS loci using next-generation (NG) capture C in a human beta-cell model ( EndoC-betaH1) and contrasted our maps with public Hi-C/promoter capture Hi-C maps in EndoC-betaH1 cells or human islets.

  Study EGAS00001006105

• A Study to Evaluate Denosumab in Young Patients With Primary Breast Cancer (D-Beyond)

  This is a prospective, single arm phase IIa trial in which patients with early breast cancer will receive pre-operatively two doses of denosumab 120mg subcutaneously one week apart (maximum 12 days) followed by surgery. Tumor, normal breast tissue and blood samples will be collected at baseline and at surgery. Post-operative treatment will be at the discretion of the investigator.Primary objective: to determine if a short course of RANKL inhibition with denosumab can induce a decrease in tumor proliferation rates as determined by Ki67 immunohistochemistry (IHC) in newly diagnosed, early stage breast cancer in pre-menopausal women.

  Study EGAS00001003252