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• Reconstructed VDJ sequences from Smart-seq2 data

  The dataset contains reconstructed VDJ sequences (fasta files) and accompanying metadata for each cell (csv file) from scRNA-seq data generated with the Smart-seq2 protocol. The VDJ sequences were reconstructed with the computational tool BraCeR using raw fastq files as input. The dataset contains sequences from 355 IgA+ peripheral blood B-lineage cells of two untreated celiac disease patients. The sequences comprise both IgA+ transglutaminase 2-specific and other IgA+ B cells.

  Dataset EGAD50000000341

• Roifman_DAC

  This Data Access Committee (DAC) will be set up to review applications, and render decisions for requests submitted to EGA to access data deposited into ega-box-1592 by Dr. Chaim Roifman at the Hospital for Sick Children in Toronto, Canada. Contact: Dr. Chaim Roifman. email:chaim.roifman@sickkids.ca

  Dac EGAC50000000243

• snRNAseq prostate cancer

  single-nucleus RNA seq characterization of human fresh frozen prostate cancer samples and non-malignant controls for the same patients. Biopsies were sectioned in 100 micron thick sections, adjacent to those used for spatial transcriptomics.

  Dataset EGAD50000001633

• Dataset for "HPV integration induces gene fusions" (ONT)

  ONT whole-genome sequencing data for "HPV integration induces gene fusions" . We sequenced five HPV-positive head and neck cancer samples using Oxford Nanopore platform. The sequences was submitted in fastq format.

  Dataset EGAD50000001302

• Multiple Myeloma treated with anti-BCMA T-cell-redirecting therapy (1st Batch)

  Bone marrow samples were collected from patients treated with either anti-BCMA CART and/or anti-BCMA TCE. All samples were sorted using the StemCell EasySep Human CD138 positive selection kit II (StemCell, Cambridge, MA). The positive CD138+ were submitted for WGS, using peripheral blood mononuclear cells as normal matched. WGS was carried out by the Molecular Genomics Core Facility at Moffitt Cancer Center contingent on the availability of high-quality pre-treatment samples. Germline DNA was obtained from peripheral blood mononuclear cells, while tumor DNA was extracted from CD138-enriched bone marrow aspirate specimens using magnetic bead-based selection. Genomic DNA was isolated using the AllPrep DNA/RNA/miRNA Universal Kit (Qiagen). For library preparation, 100 ng of genomic DNA was fragmented using the Covaris ML230 focused ultrasonicator (Covaris, Inc.), followed by library construction with the TruSeq DNA Nano Library Prep Kit (Illumina) in accordance with manufacturer instructions. Library quality and fragment size distribution were assessed via Agilent TapeStation, and quantification was performed using the Kapa Library Quantification Kit (Roche). Sequencing was conducted on the Illumina NovaSeq 6000 system using S4-300 reagent kits with a 2×150 bp paired-end configuration. Tumor samples were sequenced to a median coverage of 60×, and matched germline controls to 30×. Reference Genome: GRCh38.

  Dataset EGAD50000002632

• CD49f single-cell methylomes

  Single-cell DNA methylation has emerged as a powerful tool to study molecular heterogeneity within cellular populations. We report the development of a bisulfite based whole genome protocol suitable for use on single index sorted primary mammalian cells. Application of this protocol to human hematopoietic stem cells provided quantitative DNA methylation measurements of up to 5.7 million CpGs in a single cell. Analysis of cis CpG methylation states in single cells revealed a loss of concordance beyond 2kb, which supported the development of a new analytical framework (PDclust) for single-cell DNA methylation datasets that considers heterogeneity of methylation states at single CpG resolution. PDclust identified epigenetically distinct subpopulations within highly purified and functionally defined human stem cell populations. In silico merging of the methylation states from the single cells allowed us to ascribe function to these epigenetically distinct subpopulations on the basis of their epigenetic states.

  Study EGAS00001002789

• The DIRECT study: A roadmap for ctDNA-based risk prediction, molecular profiling and MRD detection in Diffuse Large B Cell Lymphoma

  DIRECT was a prospective, multisite study assessing the feasibility and utility of circulating tumor DNA (ctDNA) in 188 patients with aggressive B-cell non-Hodgkin lymphoma using capture panel sequencing and an open-source computational pipeline. The aims of the study were 1)baseline risk stratification, 2)genetic profiling and 3)ultrasensitive minimal residual disease (MRD) assessment. This study highlighted the considerable potential, but also the caveats and limitations, of ctDNA technology when applied to aggressive B-cell lymphoma.

  Study EGAS50000000968

• Estimating transcription factor variability in PC-9 cells using scRNA-seq

  PC-9 cells were barcoded following protocol from Chang et al. Nature Biotech. 2021, which does not affect downstream analysis. PC-9 cells were trypsinized into single-cell suspensions and processed using Chromium Single Cell Gene Expression 3’ Library and Gel Bead Kit V2.0 following the manufacturer’s instructions (10X Genomics). Cells were counted and checked for viability using Vi-CELL XR cell counter (Beckman Coulter), and then injected into microfluidic chips to form Gel Beads-in-Emulsion (GEMs) in the 10X Chromium instrument. Reverse transcription was performed on the GEMs, and RT products were purified and amplified. Expression libraries were made from the cDNA and profiled using the Bioanalyzer High Sensitivity DNA kit (Agilent Technologies) and quantified with Kapa Library Quantification Kit (Kapa Biosystems). Illumina HiSeq2500 (Illumina) was used to sequence the libraries.

  Dataset EGAD00001011041

• Germline Genetics of Myelodysplastic Syndromes (MDS) and Acute Myeloid Leukemia (AML)

  Myelodysplastic syndromes (MDS) are part of a heterogeneous and overlapping group of clonal diseases that arise in the hematopoietic stem or progenitor cells and also include acute myeloid leukemia (AML), myeloproliferative neoplasms (MPN), and the hybrid MDS/MPN entities. Individuals with MDS have a high risk of progressing to leukemia, with approximately 30% expected to develop AML. This study evaluates genetic susceptibility to myeloid malignancy using data from population-based case control studies of myelodysplastic syndromes and acute myeloid leukemia in adults (ages 18-85 years) and pediatric MDS cases with banked samples at the Center for International Blood and Marrow Transplant Research (CIBMTR). Adult cases were identified through the Minnesota Cancer Reporting System and controls were recruited from the State Driver's License/Identification Card list. DNA samples were collected via mouthwash collection kits (AML cases and controls) or Oragene saliva collection kits (adult MDS cases and controls). Pediatric MDS samples were banked at CIBMTR prior to receipt of a transplant and DNA was extracted from isolated T cells or whole blood samples. Genotyping data were generated using the Illumina Global Diversity array and quality control and genotype calling was conducted using established best practices. Our primary analyses investigated the contribution of genetic variation to MDS risk and evaluated the role of the killer cell immunoglobulin receptors (KIR) on incidence and survival.

  Study phs002962

• Transcriptome analysis of Hepatitis B for drug discovery and clinical applications

  We analyzed blood transcriptome of HBV positive untreated patients (men) using the CAGE technology.

  Study JGAS000053

• Profiling of human fecal microbiota for succinate consumption

  Enrichments of human stool samples in culture medium containing succinate as the main carbon source and the corresponding stool samples.

  Dataset EGAD50000000740

• LabExMI_SNP_genotyping

  Genotype data for 5,699,237 genotyped and imputed SNPs in the 816 healthy donors of the Milieu Intérieur cohort

  Dataset EGAD00010001489

• Dataset for Parkinson's disease target re-sequencing project

  The dataset regards the sequencing of coding and putative regulatory sequences of 38 genes associated to either sporadic or Mendelian form of Parkinson's disease

  Dataset EGAD00001001029

• circulating cell-free RNAs, CF-miRNAs, Sequencing with Qiaseq and NextSeq 550

  This dataset includes small RNA sequencing data from circulating cell-free RNAs (CF-miRNAs). miRNA libraries were prepared using the Qiaseq miRNA Library Kit with adaptations for low RNA input and sequenced on the Illumina NextSeq 550 platform

  Dataset EGAD50000001503

• Prognostic whole-genome and transcriptome signatures in colorectal cancers

  This dataset consists of RNA-seq CRAM raw-data files of 1063 primary colorectal cancer and 120 adjacent normal tissue samples. The expression profiles for these samples can be found at the ArrayExpress with accession number E-MTAB-12862.

  Dataset EGAD50000000169

• MicroRNA profiling by next-generation sequencing for colorectal cancer screening

  The dataset contains raw miRNA sequencing data of plasma samples from 20 newly diagnosed colorectal cancer cases and 20 controls free of colorectal neoplasms matched by age and sex. It includes files in the FASTQ compressed (.gz) format.

  Dataset EGAD00001006966

• Spermidine/spermine N1-acetyltransferase controls tissue-specific regulatory T cell function in chronic inflammation

  In this project we wanted to understand the role of tissue resident regulatory T cells with the aim of finding commonalities between multiple inflammatory diseases namely psoriasis, sarcoidosis and inflammatory bowel disease. Using single cell sequencing data we found that specifically in the skin, Spermidine/spermin N1-acetyltransferase seems to mediate a „fragile“ Treg phenotype. To test the influence of the tissue on this phenotype we also sought to charactierize a similar population in patient PBMCs for which we generated this data.

  Study EGAS50000000745

• Non-Coding Autoimmune Risk Variant Defines Role for ICOS in T Peripheral Helper Cell Development

  Our fine-mapping of 76 non-MHC loci associated with risk for rheumatoid arthritis (RA, 11,475 cases, 15,870 controls) has recently identified rs117701653, a non-coding single nucleotide polymorphism (SNP) in the CTLA4/CD28/ICOS locus, as the variant most likely to modulate RA risk within this region, with the minor allele C showing disease protection compared to the major allele A. We found that this SNP exhibits allele-specific protein binding and transcriptional modulation, further supporting its regulatory nature. Here, we aimed to determine whether the functional non-coding variant rs117701653 modulates the expression of genes within the CD28/CTLA4/ICOS locus. To address this question, we employed low-input RNA sequencing using the Illumina SmartSeq2 platform on resting total CD4+ T cells from the blood of 24 healthy subjects (8 AA, 8 AC, 8 CC) recruited based on genotype from the Mass General Brigham biobank. We performed a targeted cis-eQTL mapping analysis for protein coding genes with transcription start sites (TSS) within a 1MB window of SNP rs117701653. These genes included WDR12, NBEAL1, CYP20A1, ABI2, RAPH1, CD28, CTLA4, ICOS, and PARD3B. Surprisingly, allelic variation at rs117701653 correlated strongly with expression of ICOS. This suggests that individuals carrying the protective allele C at rs117701653 express lower levels of ICOS, implicating ICOS as a plausible target gene influenced by this protective allele. The raw sequence data from the 24 healthy individuals are available through dbGAP. Gene expression matrices have been deposited to GEO accession GSE235868.

  Study phs003448

• AmsterdamUMC Data Access Committee for the study "Multi-omic analysis of thyroid dysfunction in Down Syndrome"

  The current data access committee reviews and assesses data requests of researchers that seek to gain access to data acquired as part of the "Multi-omic analysis of thyroid dysfunction in Down Syndrome" study as performed at the AmsterdamUMC, Amsterdam, Netherlands.

  Dac EGAC50000000186

• Impact of germline pathogenic variants in 27 cancer-predisposing genes on the risk of lymphoma

  The application of advanced molecular technology has significantly expanded lymphoma classification, allowing risk stratification and treatment optimization. Limited evidence suggests the presence of a genetic predisposition in lymphoma, indicating the potential for better individualized clinical management based on a novel lymphoma classification. Herein, we examined the impact of germline pathogenic variants in 27 cancer-predisposing genes with lymphoma risk and explored the clinical characteristics of pathogenic variant carriers. This study included 2,066 lymphoma patients and 38,153 cancer-free controls from the Japanese population. Following quality control of sequencing data, samples from 1,982 lymphoma patients and 37,592 controls were further analyzed. Sequencing data of controls were obtained from JGAD000721. Germline pathogenic variants in some cancer-predisposing genes were associated with a high risk of lymphoma. Furthermore, germline pathogenic variants in these genes were especially associated with the higher risk of a certain subtype. These results would provide novel insights concerning monogenic form into lymphoma classification. Some lymphoma patients may benefit from surveillance and targeted treatment like other neoplasms.

  Study JGAS000347

• ISCAPE V(D)J libraries from HA-specific single memory B cells of four Influenza A exposed individuals

  Peripheral blood mononuclear cells were used to produce paired, full-length IGM, IGK and IGL V(D)J libraries from HA-binding single memory B cells using the ISCAPE (Individualized Single Cell Analysis of Paired Expressed antigen receptors) technique. Locus-specific multiplexed nested PCR with primer sets targeting the 5’ UTR/leader and 3’ constant region was performed before well and plate indexing and paired chain sequencing with an Illumina MiSeq instrument. Expressed total IGM, IGK and IGL V(D)J libraries from each donor were acquired and analyzed to define personalized IG allele content. The fastq file names include the donor and a numerical plate index for the HA-specific ISCAPE BCR HC and LC V(D)J libraries.

  Dataset EGAD50000002019

• A Single-cell Atlas of Progressive TKI Resistance in Chronic Myeloid Leukemia

  High-dimensional scRNA seq and CyTOF were used to identify features predictive of treatment outcome at diagnosis. An optimal TKI response was characterised by erythroid lineage skewing of the CD34+ HSPC compartment. While TKI-resistant CP was reminiscent of a BC-like state, where HSPCs were enriched for inflammation, stemness and quiescence. We designed a machine-learning approach which assessed the prognostic potential of all 32 sub-populations of our scRNA seq dataset. LSCs and NK populations harboured the highest prognostic power at diagnosis. Within the LSCs, erythroid lineage priming and MYC activation were features of an optimal and poor TKI responses, respectively. With the NK cell compartment, apart from a higher abundance of NK cells in TKI optimal responders, a memory-like HLA-DR+ adaptive NK and KLRC1+ NK populations were hallmarks of an optimal and poor TKI responses, respectively. Mechanistically, both cell intrinsic and extrinsic mechanisms contributed towards the higher sensitivity of EPs to TKI therapy. In summary, our high-dimensional single-cell atlas of TKI resistance highlights pivotal transcriptional features associated with TKI-resistance disease, some of which have the potential to be exploited as biomarkers.

  Study EGAS00001005509

• Pilot study towards the development of a Companion/Complimentary Diagnosis platform using liquid biopsy with cfDNA for immune checkpoint inhibitor therapy in advanced urothelial cancer

  Preliminary analysis was conducted to develop a cfDNA-based platform capable of predicting gene mutation profiles, TMB, gene expression profiles (molecular subtype diagnosis), and immunohistochemical findings (PD-L1 expression) using the primary lesion tissue of bladder cancer and upper urinary tract epithelial cancer, verifying the feasibility of such development.

  Study JGAS000714

• The taxonomic composition of the human microbiome of healthy donors

  Single homogenized human stool samples from five healthy donors and mix were analyzed by shotgun sequencing to generate a baseline for the establishment of humanized microbiome to be transferred into mice.

  Dataset EGAD50000001119

• Center for Craniofacial and Dental Genetics: Exome Sequencing of Orofacial Cleft Families

  Orofacial Clefts (OFCs) are genetically complex structural birth defects caused by genetic factors, environmental exposures, and their interactions. OFCs are the most common craniofacial anomalies in humans. Affect about 1 in 800 newborns, OFCs are also one of the most common structural birth defects worldwide. OFCs can impose a substantial personal cost resulting from the associated emotional and financial burden. On average a child undergoes 6 surgeries, spends 30 days in hospital, receives 5 years of orthodontic treatment, and participates in ongoing speech therapy, leading to an estimated total lifetime treatment cost of about $200,000. Individuals born with an OFC have higher infant mortality (especially in developing countries with limited access to care), higher mortality rates at all other stages of life, increased incidence of mental health problems, and higher risk for other disorders (notably including breast, brain, and colon cancers). Prior genetic studies have focused on the contribution of common genetic variants through genome-wide linkage and association studies. These studies have revealed a significant etiologic heterogeneity. One promising approach to dissect the etiology of OFCs into focus on subclinical phenotypic features present in the non-cleft family members of affected individuals. These subclinical features are subtle phenotypic features that may represent mild manifestations of the same risk genes; thus, their inclusion in family-based studies may clarify the inheritance patterns in OFC families. In this project, we conducted whole exome sequencing in multiplex families with both overt OFCs and subclinical phenotypes to identify high-impact genes causing OFCs.

  Study phs001675