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• 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

• 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

• 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

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

  pacBio whole-genome sequencing data for "HPV integration induces gene fusions" We performed long read whole-genome sequencing on four HPV+ head and neck cancer samples using pacBio HiFi. The sequence reads were submitted in fastq format.

  Dataset EGAD50000001304

• Thymic epithelial transplantation for complete DiGeorge syndrome Spatial (2026-01-19)

  Spatial transcriptome analysis of thymic cells from children with syndromic diseases such as Trisomy 21 and inflammatory/autoimmune diseases such as myasthenia gravis. . This dataset contains all the data available for this study on 2026-01-19.

  Dataset EGAD00001015798

• Exome sequencing of patients with acute promyelocytic leukemia

  The dataset consists in 64 fastq files from 23 patients with acute promyelocytic leukemia. Exome sequencing was conducted on several stages (Diagnosis, Remission, Relapse) for each patient. For 5 patients, only Diagnosis and Relapse samples are available.

  Dataset EGAD00001004043

• 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

• Tissue Sampling and Biorepository to improve Cancer Cell Therapy

  This study focuses on the elucidation of determinants of response and resistance to anti-CD19 CAR T-cells in large B-cell lymphoma. Plasma samples were collected prior to treatment and serially post CAR T-cell infusion. Pre-treatment and relapse tumor samples were also obtained as available. Germ-line DNA isolated from Peripheral Blood Mononuclear Cells (PBMCs) was collected for all patients when available. Circulating tumor DNA (ctDNA) and tumor DNA were sequenced using a target hybrid capture oligonucleotide pool. RNA-Seq was also performed on tumor isolated RNA. The authors identified several recurrent genomic alterations associated with relapse, and identified molecular thresholds that were predictive of response.

  Study phs003145

• Single-cell expression of Hodgkin and Reed-Sternberg (HRS) cell

  Hybrid capture sequencing was performed to 3 purified Hodgkin and Reed-Sternberg (HRS) cell samples. In brief, Probes for 177 genes were designed and synthesized by Twist Bioscience. Hybridization capture of DNA libraries was performed using Twist Hybridization and Wash Kit (Twist Bioscience). The captured library was measured using Agilent Bioanalyzer High Sensitivity chip and Qubit dsDNA HS Assay Kit and run on Illumina Nextseq550. The BAM files were generated from the raw sequencing data using Cell Ranger (v6.0.2) mkfastq and count commands

  Dataset EGAD00001010892

• Single-cell ATAC-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell ATAC sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015715

• Single-cell RNA-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell RNA sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015710

• Single-cell ATAC-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell ATAC sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015711

• Single-cell RNA-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell RNA sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015717

• Single-cell ATAC-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell ATAC sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015719

• 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

• Type I Interferon Exacerbates Mycobacterium Tuberculosis Induced Human Macrophage Death

  In this study, we tested whether type I interferons (IFN-I), namely IFN-alpha and IFN-beta, may promote Mycobacterium tuberculosis (Mtb) pathogenesis by exacerbating cell death of human monocyte-derived macrophages (MDM) infected with Mtb. We differentiated the MDM under two different published methods (see Document Method.pdf for Table 1 of Methods). To determine if MDM infected with Mtb upregulates IFN-I transcripts, signaling factors, or IFN-I stimulated genes (ISGs), the MDM were infected with Mtb or treated with an activator of stimulator of IFN genes (STING), diamidobenzimidazole (di-ABZI). STING activation acted as a positive control for IFN-I induction and ISG upregulation. Indeed, di-ABZI treated MDM differentiated under both methods upregulated ISGs 24 hpi. At 24 hour post treatment, MDM differentiated under one method, but not under another method, upregulated ISGs, such as ISG15, IFITM3, and CXCL10, upon Mtb infection. MDM differentiated under both methods upregulated ISGs upon di-ABZI treatment.

  Study phs003607

• Cell-free MeDIP-seq of plasma samples from lymphoma patients and healthy controls

  This dataset contains cell-free methylated DNA immunoprecipitation sequencing (cfMeDIP-seq) data generated from plasma samples of lymphoma patients and healthy controls. The study aims to characterize genome-wide methylation patterns of circulating cell-free DNA and identify hypermethylated regions associated with lymphoma. Sequencing libraries were prepared using cfMeDIP with anti-5-methylcytidine antibody enrichment and sequenced on an Illumina platform. The dataset supports differential methylation analyses and the development of classification models for lymphoma detection.

  Dataset EGAD50000002108

• Whole genome characterisation of lung cancer organoids and tissue

  Organoids are self-organizing 3D structures grown from stem cells that recapitulate essential aspects of organ structure and function. Here we describe a method to establish long-term expanding human airway organoids from broncho-alveolar biopsies or lavage material. The pseudostratified airway organoid epithelium consists of basal cells, functional multi-ciliated cells, mucus-producing goblet cells, and CC10-secreting club cells. Airway organoids derived from cystic fibrosis (CF) patients allow assessment of CFTR function in an organoid swelling assay. Organoid culture conditions also allow gene editing as well as the derivation of various types of lung cancer organoids. Respiratory syncytial virus (RSV) infection recapitulated central disease features and dramatically increases organoid cell motility, found to be driven by the non-structural viral NS2 protein. We conclude that human airway organoids represent versatile models for the in vitro study of hereditary, malignant, and infectious pulmonary disease.

  Study EGAS00001002899

• Blood RNA-seq from Mexican DMD patients and healthy controls

  These data are part of a study that aimed to assess the potential of blood RNA-seq to track non-invasively disease progression for DMD. In particular, here we focus on a study designed to compare gene expression in blood from DMD patients to that of healthy controls. These data are analysed in the following manuscript: Signorelli, M., Ebrahimpoor, M. et al. (accepted). Peripheral blood transcriptome profiling enables monitoring disease progression in dystrophic mice and patients. To appear in EMBO Molecular Medicine.

  Study EGAS00001004907

• Functional Mapping of AKT Signaling and Biomarkers of Response From the FAIRLANE Trial of Neoadjuvant Ipatasertib Plus Paclitaxel for Triple-Negative Breast Cancer

  Purpose: Despite extensive genomic and transcriptomic profiling, it remains unknown how signaling pathways are differentially activated and how tumors are differentially sensitized to certain perturbations. Here, we aim to characterize AKT signaling activity and its association with other genomic or immunohistochemistry-based PI3K/AKT pathway biomarkers as well as the clinical activity of ipatasertib (AKT inhibitor) in the FAIRLANE trial. Experimental Design: In FAIRLANE, 151 patients with early triple-negative breast cancer were randomized 1:1 to receive paclitaxel with ipatasertib or placebo for 12 weeks prior to surgery. Adding ipatasertib did not increase pathologic complete response rate and numerically improved overall response rate by magnetic resonance imaging (MRI). We used reverse-phase protein microarrays (RPPA) to examine the total level and/or phosphorylation states of over 100 proteins in various signaling or cell processes including PI3K/AKT and mTOR signaling. 125 baseline and 127 on-treatment samples were evaluable by RPPA, with 110 paired samples at both time points. Results: Tumors with genomic/protein alterations in PIK3CA/AKT1/PTEN were associated with higher levels of AKT phosphorylation. In addition, phosphorylated(p)AKT levels exhibited a significant association with enriched clinical benefit of ipatasertib, and identified patients who received benefit in the absence of PIK3CA/AKT1/PTEN alterations. Ipatasertib treatment led to a down-regulation of AKT/mTORC1 signaling, which was more pronounced among the tumors with PIK3CA/AKT1/PTEN alterations or among the responders to the treatment. Conclusions: We showed that the high baseline pAKT levels are associated with the alterations of PI3K/AKT pathway components and enriched benefit of ipatasertib in TNBC.

  Study EGAS00001005892

• Single-Cell Atlas of Human Liver and Blood Immune Cells Across Fatty Liver Disease Stages

  The goal of the study was to investigate immunological correlates of human fatty liver disease progression. We generated a single-cell RNA-seq (scRNA-seq) atlas of immune cells from liver fine needle aspirates (FNAs) and paired peripheral blood mononuclear cells (PBMCs) from a full-spectrum Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD)/Metabolic Dysfunction-Associated Steatohepatitis (MASH) human cohort, using the 3' 10X Genomics platform. Using computational analyses to assess changes in cellular frequencies and function, we found heightened immunoregulatory programs with profibrotic potential alongside a shift from antigen-specific to natural killer cytotoxic functions in the liver with MASH progression. Available data include raw single-cell transcriptomic data (FASTQ files) for each sample type (PBMC, FNA) per patient alongside clinical and histological measurements of fatty liver disease.

  Study phs004044

• 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

• 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