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• COVID_19_Challenge_Project_Single_Cell_Profiling

  Single-cell profiling of sero-negative and sero-positive humans that were inoculated with SARS-CoV-2. The cellular response during SARS-CoV-2 is profiled using single-cell transcriptomics, CITE-seq and single cell immune profiling, by sampling PBMCs and nasal swabs before and at multiple time points during SARS-CoV-2 infection. This one-of-a-kind cellular map will give unique temporal resolution of how nasal and immune cells respond to SARS-CoV-2 exposure and infection

  Study EGAS00001005696

• Mutational_burden_in_human_hair_follicles

  We would like to dissect human hair follicles and assess the mutations found in diffferent parts of the follicle eg bulge, root etc. We can also compare this with mutations found in the surrounding epidermis of the same patients (this is done under a different study). This may provide insights into the origin of PTCH1 mutants frequently seen in basal cell carcinoma but so far not located in our whole epidermis work as well as defining the clonality of the hair follicle

  Study EGAS00001004462

• Cell-free DNA and bone marrow samples from myelodysplastic syndromes

  We have assessed the molecular profile of a cohort of 70 patients with MDS by next-generation sequencing (NGS) using cfDNA and compared the results to paired bone marrow (BM) DNA. Sequencing of BM DNA and cfDNA showed a comparable mutational profile and variant allele frequencies (VAF) strongly correlated between both sample types. Our results support the analysis of cfDNA as a promising strategy for performing molecular characterization, detection of chromosomal aberrations and monitoring of MDS patients.

  Study EGAS00001005992

• Characterization of MCSP+ melanoma DCC and MelDCC lines

  To dissect the sequence of genotypic and phenotypic progression during early metastatic colonization, we searched for the earliest detectable disseminated cancer cells (DCC) and identified MCSP+ melanoma cells as strong candidates for metastasis founder cells (MFC) in lymph nodes. We isolated MCSP+ DCC from various stages of metastatic colony-formation, performed scRNA-seq and unravelled their phenotypic progression. Further we performed bulk sequencing on patient-derived DCC models (MelDCC) and showed that they exhibit an immunosuppressive activity on CD8 T cells.

  Study EGAS00001006702

• Human pan-cancer plasma cfRNA study - raw data

  This study contains mRNA capture sequencing data from plasma of 266 different human donors. The first, pan-cancer, cohort covers 25 high-grade to metastatic cancer types (8 cancer patients per type) and a control group (8 healthy donors). The validation cohort comprises additional plasma samples from ovarian, prostate and uterine cancer patients (12 per type) as well as additional samples from controls (22 new and 8 repeated). Samples were sequenced on a NovaSeq 6000 and are provided in FASTQ format.

  Study EGAS00001006755

• Identification of genomic aberrations in low-grade serous ovarian cancer

  Low-grade serous ovarian cancer (LGSOC) is a rare disease that occurs more frequently in younger women compared with high-grade disease. The current treatment is suboptimal, and better understanding of molecular pathogenesis of this disease is needed. In this study, we compared the whole genome sequences of LGSOCs from short-term and long-term survivors (defined as <40 and >60 months, respectively). Our goal was to identify novel genomic aberrations in LGSOC, especially in short-term survivors.

  Study EGAS00001006679

• Molecular analysis of cancer genomes in children with Lynch syndrome: exploring causal associations

  Lynch syndrome (LS) predisposes to cancer in adulthood and is caused by heterozygous germline variants in a mismatch repair (MMR) gene. Recent studies show an increased prevalence of LS among children with cancer, suggesting a causal relationship. For LS-spectrum (LSS) cancers, including high-grade gliomas and colorectal cancer, causality has been supported by typical MMR-related tumor characteristics, but for non-LSS cancers, causality is unclear. This dataset contains 5 patients with Lynch Syndrome from the INFORM registry.

  Study EGAS00001007146

• Idiosyncratic and generic single nuclei and spatial transcriptional patterns in papillary and anaplastic thyroid cancers

  Thyroid cancer is the most common endocrine malignancy. This dataset encompasses two types of thyroid cancer : anaplastic which is the most de-differentiated and aggressive one, and papillary which is the most common one. We profiled 14 patients, including 10 papillary and 4 anaplastic thyroid carcinomas, using both single nuclei RNA sequencing and spatial transcriptomics to link single cell resolution RNA sequencing with tissue morphology and better understand inter and intratumoral thyroid cancer heterogeneity.

  Study EGAS00001007574

• Transcriptomic predictors of survival for palbociclib + endocrine therapy vs. capecitabine in aromatase inhibitor-resistant breast cancer from GEICAM/2013-02 PEARL

  We examined transcriptomic tumor features associated with survival from GEICAM/2013-02 PEARL, a phase III trial of palbociclib + ET vs. capecitabine in aromatase inhibitor-resistant HR+/HER2- MBC. PAM50 intrinsic subtype predicted PFS differences between palbociclib + ET and capecitabine, and lower B-cell-associated gene expression predicted longer OS with palbociclib + ET vs. capecitabine. These features may help identify HR+/HER2- tumors resistant to further ET-based treatment with CDK4/6 inhibitors.

  Study EGAS00001008177

• Progressive supranuclear palsy - bulk RNA seq of prefrontal cortex

  Dataset corresponding to the bulk RNA-seq dataset from prefrontal cortex for a total of N=42 samples. Tissue samples correspond to donors with pathologically confirmed progressive supranuclear palsy. RNA-seq was carried out using ribosomal depletion. Dataset contains paired fastq files, sample metadata and downstream quantification files. Quantification was performed with salmon v1.3.0 with Gencode 35 (GRCh38.p13).

  Dataset EGAD50000002623

• Multiple system atrophy - bulk RNA seq of prefrontal cortex

  Dataset corresponding to the bulk RNA-seq dataset from prefrontal cortex for a total of N=35 samples. Tissue samples correspond to donors with pathologically confirmed multiple system atrophy. RNA-seq was carried out using ribosomal depletion. Dataset contains paired fastq files, sample metadata and downstream quantification files. Quantification was performed with salmon v1.3.0 with Gencode 35 (GRCh38.p13). N=6 samples are overlapping with EGAS50000000301.

  Dataset EGAD50000002624

• Alzheimer's disease - bulk RNA seq of prefrontal cortex

  Dataset corresponding to the bulk RNA-seq dataset from prefrontal cortex for a total of N=72 samples. Tissue samples correspond to donors with pathologically confirmed Alzheimer's disease. RNA-seq was carried out using ribosomal depletion. Dataset contains paired fastq files, sample metadata and downstream quantification files. Quantification was performed with salmon v1.3.0 with Gencode 35 (GRCh38.p13).

  Dataset EGAD50000002625

• Dementia with Lewy bodies - bulk RNA seq of prefrontal cortex

  Dataset corresponding to the bulk RNA-seq dataset from prefrontal cortex for a total of N=80 samples. Tissue samples correspond to donors with pathologically confirmed dementia with Lewy bodies. RNA-seq was carried out using ribosomal depletion. Dataset contains paired fastq files, sample metadata and downstream quantification files. Quantification was performed with salmon v1.3.0 with Gencode 35 (GRCh38.p13).

  Dataset EGAD50000002626

• Parkinson's disease - bulk RNA seq of prefrontal cortex

  Dataset corresponding to the bulk RNA-seq dataset from prefrontal cortex for a total of N=448 samples. Tissue samples correspond to donors with pathologically confirmed Parkinson's disease. RNA-seq was carried out using ribosomal depletion. Dataset contains paired fastq files, sample metadata and downstream quantification files. Quantification was performed with salmon v1.3.0 with Gencode 35 (GRCh38.p13). N=81 samples are overlapping with EGAS50000000301.

  Dataset EGAD50000002627

• Controls - bulk RNA seq of prefrontal cortex

  Dataset corresponding to the bulk RNA-seq dataset from prefrontal cortex for a total of N=283 samples. Tissue samples correspond to health control donors. RNA-seq was carried out using ribosomal depletion. Dataset contains paired fastq files, sample metadata and downstream quantification files. Quantification was performed with salmon v1.3.0 with Gencode 35 (GRCh38.p13). N=21 samples are overlapping with EGAS50000000301.

  Dataset EGAD50000002628

• Corticobasal degeneration - bulk RNA seq of prefrontal cortex

  Dataset corresponding to the bulk RNA-seq dataset from prefrontal cortex for a total of N=17 samples. Tissue samples correspond to donors with pathologically confirmed corticobasal degeneration. RNA-seq was carried out using ribosomal depletion. Dataset contains paired fastq files, sample metadata and downstream quantification files. Quantification was performed with salmon v1.3.0 with Gencode 35 (GRCh38.p13).

  Dataset EGAD50000002629

• Single cell RNA sequencing of mononuclear cells from synovial fluid of patients with rheumatoid arthritis

  Mononuclear cells were collected from synovial fluid of anti-citrullinated positive antibodies (ACPA)-positive rheumatoid arthritis patients (n=8) and ACPA-negative RA patients (n=8). Global cell types (i.e., no enrichment) were obtained from these cryopreserved synovial fluid mononuclear cells (SFMC) samples and immediately fixed and processed using the GEM-X Flex Gene Expression Reagent Kits (10x Genomics) according to protocol. Following Gel Bead-in Emulsion (GEM) generation, samples were processed using the standard manufacturer’s protocol. Once sequencing libraries passed standard quality control metrics, libraries were sequenced on an Illumina NextSeq2000 P4 100 cycle reagent kit with the following read structure: R1: 28, R2: 90, I1: 10, I2: 10. Libraries were sequenced to obtain a read depth greater than 10,000 reads/cell for gene-expression (GEX). FASTQ files are made available. More detailed information can be obtained in Argyriou A. et al, Annals of the Rheumatic Disease, 2025.

  Dataset EGAD50000001801

• Differential expression in clear cell renal cell carcinoma

  To investigate the levels of gene expression in clear cell renal cell carcinoma (ccRCC), we performed an RNA-seq analysis in 786-O, A-498, UM-RC-2 clear cell renal carcinoma cell lines, as well as HK-2 normal renal epithelium cell line, cultured under normoxic (20% O2) and hypoxic (0.05% O2) conditions. Data are provided in raw fastq files and csv files with the differential expression results. Differential expression was calculated by the RNAflow pipeline (DEseq2), and log fold changes are calculated with respect to the normal cell line (HK-2), with separate results between normoxic and hypoxic datasets.

  Dataset EGAD50000001883

• Multiregional single nuclei RNA-seq and WGS of prostate cancer

  This study investigates the clonal evolution and metastatic dissemination of prostate cancer using multiregional single-nuclei RNA sequencing (snRNA-seq) and low-pass whole-genome sequencing (WGS) data from 43 spatially distinct tumor areas in five patients with locally advanced prostate cancer, including both primary and regional lymph node samples. We employed the Chromium Next GEM Single Cell 3’ Kit (v3/3.1, 10x Genomics) for single-nuclei transcriptome profiling and constructed bulk WGS libraries using the NEBNext Ultra II FS DNA Library Prep Kit (New England Biolabs) from the same pool of nuclei extracted from each area. snRNA-seq data were aligned to the human genome (GRCh38-1.2.0_premrna) using 10x Genomics Cell Ranger v5.0.0, while WGS reads were aligned to the human reference genome (GRCh38) with BWA MEM, achieving an average sequencing depth of 0.3X for low-pass WGS and 16X after resequencing.

  Dataset EGAD50000001357

• MOSAIC Window Mesothelioma Data

  This dataset will include Spatial Transcriptomics from the 10x Genomics Visium SD technology, Single-Cell RNA-Seq from the 10x Genomics Chromium Flex protocol, Bulk RNA-Seq (sequenced on Illumina), WES (sequenced on Illumina), H&E, and Clinical data from 10 Mesothelioma patients. For Visium and Chromium data we are sharing the outputs of respectively Space Ranger and Cell Ranger. For Bulk RNA-Seq we are including processed files such as counts.tsv, FPKM.tsv, fusion_genes.tsv, TPM count matrix.tsv, DESeq2 count matrix.tsv, multiqc_report. For WES, we are sharing the presence or absence of single nucleotide variants (SNVs), small insertions and deletions (indels), and copy number variants (CNVs).* Researchers from private or public institutions outside the MOSAIC Consortium will be able to apply to access this data and, pending approval, use the data for their research.

  Dataset EGAD50000001706

• MOSAIC Window Ovarian Data

  This dataset will include Spatial Transcriptomics from the 10x Genomics Visium SD technology, Single-Cell RNA-Seq from the 10x Genomics Chromium Flex protocol, Bulk RNA-Seq (sequenced on Illumina), WES (sequenced on Illumina), H&E, and Clinical data from 15 Ovarian patients. For Visium and Chromium data we are sharing the outputs of respectively Space Ranger and Cell Ranger. For Bulk RNA-Seq we are including processed files such as counts.tsv, FPKM.tsv, fusion_genes.tsv, TPM count matrix.tsv, DESeq2 count matrix.tsv, multiqc_report. For WES, we are sharing the presence or absence of single nucleotide variants (SNVs), small insertions and deletions (indels), and copy number variants (CNVs).* Researchers from private or public institutions outside the MOSAIC Consortium will be able to apply to access this data and, pending approval, use the data for their research.

  Dataset EGAD50000001704

• MOSAIC Window DLBCL Data

  This dataset will include Spatial Transcriptomics from the 10x Genomics Visium SD technology, Single-Cell RNA-Seq from the 10x Genomics Chromium Flex protocol, Bulk RNA-Seq (sequenced on Illumina), WES (sequenced on Illumina), H&E, and Clinical data from 10 DLBCL patients. For Visium and Chromium data we are sharing the outputs of respectively Space Ranger and Cell Ranger. For Bulk RNA-Seq we are including processed files such as counts.tsv, FPKM.tsv, fusion_genes.tsv, TPM count matrix.tsv, DESeq2 count matrix.tsv, multiqc_report. For WES, we are sharing the presence or absence of single nucleotide variants (SNVs), small insertions and deletions (indels), and copy number variants (CNVs).* Researchers from private or public institutions outside the MOSAIC Consortium will be able to apply to access this data and, pending approval, use the data for their research.

  Dataset EGAD50000001702

• RNA sequencing from patient-derived intestinal organoids

  uman duodenal tissues for establishing organoid cultures used in this study were sourced from de-identified surgical specimens (n = 3) of the duodenum obtained from patients who had undergone biopsy procedures unrelated to CeD at Tampere University Hospital. The protocol was approved by the Ethics Committee of Tampere University Hospital, Tampere, Finland (ETL code R18082). RNA from the duodenal organoids was isolated using an RNeasy Kit (Qiagen, Hilden, Germany) following the manufacturer’s instructions. RNA purity and concentration were measured using a NanoDrop One spectrophotometer (NanoDrop Technologies, Wilmington, Delaware, USA). Preparation of the RNA library and transcriptome sequencing was conducted by Novogene Co., LTD (Cambridge, UK). Messenger RNA was purified from total RNA using polyA selection and subjected to library construction. Sequencing was performed on an Illumina platform, and 150 bp paired-end reads were generated.

  Dataset EGAD50000000492

• Longitudinal single-cell transcriptomic study in patient-derived xenografts of pediatric T-ALL

  In this study, we conducted single cell full length total RNA sequencing (VASA-seq) on 13 matched pediatric T-ALL PDX samples at initial diagnosis and relapse, along with 5 non-relapsing PDX samples collected at initial diagnosis. We identified a subpopulation of T-ALL cells with stem-like cell features that expands substantially at relapse indicating resistance to first-line therapy. Chemotherapy resistance was further validated through functional testing: Two samples were subjected to in-vitro drug testing, treated with Cytarabine for three days, followed by single-cell transcriptomic analysis using 10x Genomics. Additionally, in-vivo drug testing was conducted on one sample, involving re-engraftment into mice and treatment with a combination of Vincristine, Doxorubicin, and Dexamethasone. Single-cell transcriptomic analysis using 10x Genomics was performed after 0, 15 and 30 days of treatment.

  Dataset EGAD50000000831

• Transcriptomic analysis of the NA-PHER2 clinical trial

  We performed whole transcriptome RNA sequencing on serial tumour biopsies collected at baseline, Day 14, and after completion of all neoadjuvant therapy from the NA-PHER2 trial. Patients received neoadjuvant treatment with the combined regimen of trastuzumab, pertuzumab, palbociclib with or without addition of fulvestrant. Transcriptomic profiles were generated from 143 samples (Baseline n = 53, Day 14 n = 49, Surgery n = 41) corresponding to 53 of the 58 patients enrolled in NA-PHER2 trial (91.4%). RNA sequencing was performed on total RNA samples derived from formalin-fixed, paraffin-embedded (FFPE) tissue sections. RNA-Seq libraries were produced using NEBNext® Ultra™ II Directional RNA Library Prep Kit. The capture was then performed on cDNA libraries with the Twist Human Core Exome Enrichment System according to supplier recommendations (Twist Bioscience). The obtained eluted-enriched DNA samples was then sequenced on an Illumina NovaSeq as paired-end 100bp reads. FASTQ files are provided.

  Dataset EGAD50000000363

• Oesophageal adenocarcinoma scRNAseq from LUD2015-005 study (NCT02735239, EudraCT 2015-005298-19)

  This dataset contains single-cell RNA-seq generated from the LUD2015-005 study (NCT02735239, EudraCT 2015-005298-19) and additional donors with Barrett's oesophagus using the 5' Single Cell Gene Expression assay from 10x Genomics. Samples were generated from oesophageal tumours, Barrett's oesophagus, and normal oesophagus and gastric tissues, with the aim of generating a reference atlas for cell types found in normal and disease-associated tissue states in the upper GI tract. This reference atlas was used as the basis for a deconvolution workflow to estimate the cell composition of bulk transcriptomes from these tissues, and to assess cell type-specific expression patterns of potential predictive biomarkers for immunochemotherapy regimens in this setting.

  Dataset EGAD00001009401

• Exome sequencing of patients with Ewings sarcoma

  Cancer is driven by mutations in the genome. We will uncover the mutations that give rise to Ewing's sarcoma, a bone tumour that largely affects children. We will use second generation Illumina massively parallel sequencing, and bespoke software, to characterise the genomes and transcriptomes of Ewing,s sarcoma tumours.

  Dataset EGAD00001000333

• There are 116 liver cancer cases in this study and belong to LICA-CN project.The NGS test was performed with whole exome sequencing with HiSeq 2000 platform.

  There are 116 liver cancer cases in this study and belong to LICA-CN project

  Dataset EGAD00001003174

• Whole exome and targeted DNA sequencing data for formalin-fixed paraffin embedded tissue from de novo small cell prostatic carcinoma cases

  This dataset consists of 44 compressed paired fastq files, 15 of which are generated from whole exome sequencing, and 29 of which are generated from DNA sequencing using a targeted gene panel capturing the exonic regions of 73 prostate cancer driver genes. Targeted DNA sequencing was performed on an Illumina MiSeq (v3 600 cycle kit), and exome sequencing was done using an Illumina HiSeq 2500 (v4 250 cycle kit) machine. The fastq files are named in accordance with the sample aliases provided, which reflect the pathology of interest to this study (small cell prostatic carcinoma--SCPC), whether it was sequenced using an exome or targeted gene panel, whether the FFPE sample was sourced from tumor or benign tissue (labeled T or B, respectively), and whether there exists multiple samples belonging to a single patient.

  Dataset EGAD00001004139

• Exome sequencing of 142 gastric cancer and matched normal from Japanese cohorts (UT)

  As a contribution to the International Cancer Genome Consortium, exome sequencing of 142 Japanese gastric cancer with various histological subtypes have been conducted. This study aims to identify unique and common driver genes and molecular subtypes in Japanese gastric cancer. Please refer ICGC website for detail: http://icgc.org/icgc/cgp/69/420/1012357

  Dataset EGAD00001004041

• Exome sequencing of 102 gastric cancer and matched normal from Japanese cohorts (YCU)

  As a contribution to the International Cancer Genome Consortium, exome sequencing of 102 Japanese gastric cancer with various histological subtypes have been conducted. This study aims to identify unique and common driver genes and molecular subtypes in Japanese gastric cancer. Please refer ICGC website for detail: http://icgc.org/icgc/cgp/69/420/1012357

  Dataset EGAD00001004042

• Massive parallel RNA sequencing of highly purified mesenchymal cells derived from bone marrow specimens of 45 low-risk myelodysplastic syndrome cases

  Highly purified mesenchymal cells (CD45-/7AAD-/CD235a-/CD31-/CD271+/CD105+) were prospectively FACS-isolated from bone marrow specimens of 45 low-risk myelodysplastic syndrome (LRMDS) cases. Gene expression profiles (GEPs) of the 45 LRMDS have been compared to GEPs derived from likewise highly purified mesenchymal cells obtained from bone marrow specimens of healthy donors for the identification of inflammatory signatures. Additionally, an overlap in inflammatory signatures has been determined by comparing the GEPs of these 45 LRMDS cases to the GEPs of 4 Shwachman-Diamond syndrome and 3 Diamond-Blackfan anemia cases, both representing different subclasses of congenital pre-leukemia syndromes with a tendency of leukemic progression and perturbed niche compartment. Finally, the GEPs and gene expression signatures have been utilized for prognostication and the prediction of leukemic progression.

  Dataset EGAD00001002658

• RNA-seq BAM files from newborn screening dried blood spot samples

  Paired-end RNA-seq BAM files from 21 newborn screening dried blood spot (DBS) samples. These DBS samples were obtained from extremely low gestional age newborns, where 10 of them were affected by a fetal inflammatory response (FIR) before birth, and 11 were unaffected. Total RNA was sequenced using an Illumina NextSeq-500 instrument. The sample preparation protocol included the depletion of rRNA and globin mRNA using the Globin Zero Gold rRNA Removal Kit from Illumina. Libraries were prepared using the NebNext Ultra TM II Directionl RNA LIbrary Prep Kit (New England Biolabs). There is one BAM file per sample and there is an additional BAM file, corresponding to sample BS13, which was downsampled to 1/4 of its original depth (see BS13_README file for details).

  Dataset EGAD00001005009

• Pseudotime ordering of cell cycle state (2020-01-29)

  We will be using G&T method to sequence single cell genome and transcriptome derived from FS13B iPSCs cell line. The cell cycle state of each of the single cells is known. Hence, we will be analysing the genome and transcriptome of single cells from each of the cell cycle state to generate a copy number profile and transcriptome profile per given cell cycle stage: G1, S, G2, S. . This dataset contains all the data available for this study on 2020-01-29.

  Dataset EGAD00001005919

• Whole-genome sequences of single-cell derived clonal samples and bulk blood samples from human

  Human single cells were clonally expanded by culture and whole-genome sequenced. This dataset includes 334 clonal samples and 7 blood bulks from seven individuals (DB2, DB3, DB5, DB6, DB8, DB9, DB10). We extracted genomic DNA materials from clonally expanded cells and matched peripheral blood using DNeasy Blood and Tissue kits (Qiagen) according to the protocol. DNA libraries for WGS were generated by an Accel-NGS 2S Plus DNA Library Kit (Swift Biosciences) from 1 µg of genomic DNA materials. WGS was performed on either the Illumina HiSeq X platform or the NovaSeq 6000 platform to generate mean coverage of 25.2X for 374 clonally expanded cells and 94.8X for 7 matched blood tissues.

  Dataset EGAD00001007032

• MutWP5: CRUK Mutographs of Cancer: Lung: PD38233 (WG) (2021-02-02)

  Sequencing of LCM-derived microbiopsies from explanted lung from COPD patient. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Deep sampling throughout multiple regions of the lung will determine whether there are differences in smoking-related mutation burden in different portions of the lung. Whole-genome sequencing will be conducted on samples identified as promising from the initial targeted data. Results from this portion of the study will be compared to other individuals with smoking-related diseases (COPD, pulmonary fibrosis, lung cancer), and normal, non-smoking lungs. . This dataset contains all the data available for this study on 2021-02-02.

  Dataset EGAD00001006930

• MutWP5: CRUK Mutographs of Cancer: Lung: PD43291_Novaseq (Exome) (2021-02-02)

  Sequencing of LCM-derived microbiopsies from explanted lung from COPD patient. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Deep sampling throughout multiple regions of the lung will determine whether there are differences in smoking-related mutaiton burden in different portions of the lung. Whole-genome sequencing will be conducted on samples identified as promising from the initial targeted data. Results from this poriton of the study will be compared to other individuals with smoking-related diseases (COPD, pulmonary fibrosis, lung cancer), and normal, non-smoking lungs. . This dataset contains all the data available for this study on 2021-02-02.

  Dataset EGAD00001006932

• Drug screen in iPSC-Neurons identifies nucleoside analogs as inhibitors of (G4C2)n expression in C9orf72 ALS/FTD

  To investigate the mode of action and potential side-effects we analyzed differential gene expression in Postmitotic C9orf72 iPSC-Neurons by RNAseq. The cells were treated in a 2 dose regime at 10 µm in 0.1 % DMSO for 9 days. Compound treated iPSC-Neurons were washed with PBS, frozen on dry ice and stored at -80°C until RNA isolation. The RNA was isolated using miRNA Mini Kit (Qiagen) using 700 μl of Qiazol. A total of 250 ng of RNA per sample was processed for mRNA library preparation as per the manufacturer’s instructions for Illumina® Stranded mRNA Prep Ligation to be used with the IDT® for Illumina® RNA UD Indexes Set B and sequenced using NextSeq 500/550 High Output Kit v2.5 (Illumina) on NextSeq 550 (Illumina). The data was processed and analyzed using CLC genomics workbench (Version 21.0.3, Qiagen)

  Dataset EGAD00001008674

• Platelets contain a repertoire of DNA fragments that map over the human nuclear genome, including tumour-derived DNA in patients with active malignancy.

  This dataset consists of WGS from six patients with a recent diagnosis of gastrointestinal adenocarcinoma. DNA-Seq libraries were prepared from platelet DNA (pDNA) and plasma cfDNA obtained from the same peripheral blood sample. pDNA was size selected into 2 groups (small, s-pDNA: less than 600 bp and long, b-pDNA: greater than 600 bp). The short fragments were further cleaned to remove <100 bp fragments and large platelet fragments were fragmented via sonication. Libraries were then prepared using the NEBNext Ultra II DNA Sample Preparation Kit for Illumina according to the manufacturer’s protocol and sequenced on an Illumina NextSeq 500 (300 cycle PE) at low-pass (0.1X) for all samples, and 10X for the cfDNA and s-pDNA, using four lanes in each sample.

  Dataset EGAD00001009856

• CCA ChIP-seq data (63 CCA, 8 normal, 19 cell-line)

  Fastq files for H3K27ac ChIP-seq (with matched input-DNA control) for 63 CCAs, 8 normal bile duct tissues, 16 CCA cell-lines (including replicates), and 3 normal cholangiocyte cell-lines (including replicates). Library prep was performed with the NEBNext ChIP-seq library preparation kit. Each library (including matching input DNA) was sequenced to an average depth of 20 to 30 million raw reads on Illumina HiSeq4000 sequencer, with paired-end sequencing (except for 3 normal bile tissues done with single-end sequencing).

  Dataset EGAD00001012103

• Bulk RNAseq gene expression of baseline tumors from metastatic urothelial bladder cancer patients (IMvigor210) and metastatic renal cell carcinoma (IMmotion150)

  We examined tumors from a large cohort of patients with metastatic urothelial bladder cancer (mUC) and metastatic renal cell carcinoma (mRCC) treated with an anti-PD-L1 agent (atezolizumab) and found that high tumor IL8 gene expression was associated with worse overall survival (OS). We further identified the tumoral immune presence based on Teff signature. We found that high tumor IL8 expression continued to be associated with worse OS even in inflamed tumors in mUC and mRCC.

  Study EGAS00001004386

• Metabolomic and microbiome profiling reveals personalized risk factors for coronary artery disease

  A comprehensive clinical and multi-omic profiling for 199 patients with acute coronary syndrome (ACS), an acute subcategory of CAD, that we recruited in two major Israeli hospitals. We demonstrate that ACS has distinct serum metabolome and gut microbial signatures, as compared to a control cohort. Metabolic aberrations linked with microbiome and diet show a gradual trend with significant metabolite deviations in control participants with metabolic impairment suggesting their involvement in earlier dysmetabolic phases preceding clinically overt CAD.

  Study EGAS00001005342

• H3Africa - Consortium WGS

  To address gaps in sequence data for some of the African populations being studied in H3Africa projects, additional sequencing has been carried out through various projects and the data are being made available. The first dataset includes a high coverage whole genome sequence dataset generated at the Baylor College of Medicine with samples provided by H3Africa PIs and collaborators, funded by the National Institutes of Health. The sequence data files are accompanied by minimal metadata, including country, ethnic group (where available) and sex.

  Study EGAS00001005972

• Adipose transcriptome response after a 6-day very-low energy fast in obesity, in the single-arm feeding trial FASTOMICS-6

  Background: Fasting and ketogenic diets have gained popularity due to potential health benefits, in part via autophagy and other protective processes. However, although the basic physiology of fasting is well-established, we lack a deeper understanding of mechanisms on the tissue level and associated metabolome changes, particularly in humans. Method: 4 males and 9 females with severe obesity underwent a very-low-energy in-hospital feeding study (600 kcal/day). Plasma (n=13) and subcutaneous adipose tissue samples (n=12) were collected in the morning before and after 6 days and analyzed by GC-MS/MS and RNA-sequencing, respectively. Gene set enrichment analysis (GSEA) and weighted gene co-expression network analysis were used to identify biological pathways and modules of affected genes and their correlation with plasma ketones and metabolites.

  Dataset EGAD50000001484

• Comprehensive Genomic Profiling of a National Cohort of Pediatric Papillary Thyroid Carcinoma in Hungary

  Pediatric papillary thyroid carcinoma (PTC) is a rare childhood malignancy with increasing incidence and distinct clinicopathological features, including high rate of locoregional metastases and different molecular background compared to adult cases. Traditional treatments (surgery, radioactive iodine) are effective but pose long-term risks, prompting the exploration of targeted therapies. We performed comprehensive genomic profiling on 21 pediatric PTC patients utilising the Illumina TruSight Oncology 500 platform and detected mutations, gene fusions, copy number variations and revealed tumor mutational burden.

  Study EGAS50000001833

• Polygenic Risk Score for the Prediction of Breast Cancer Is Related to Lesser Terminal Duct Lobular Unit Involution of the Breast

  The Susan G. Komen Tissue Bank (KTB) at the Indiana University Simon Cancer Center is an annotated biobank, which has recruited healthy women who provided demographic, lifestyle, and cancer-related information via self-administered questionnaire, blood samples and normal breast tissues. H&E slides of the normal breast tissues were scanned for image analysis and a pathologist measured the number of terminal duct lobular units (TDLUs) ("TDLU count"). The acini count per TDLU was quantified using the TDLU analyzer software. In this analysis, we computed the recently developed polygenic risk score (PRS) based on 313 common variants for the prediction of breast cancer and related this PRS to TDLU count and acini count per TDLU. We did this for the overall PRS, the ER-positive PRS and the ER-negative PRS.

  Study phs002062

• Host Response to Respiratory Infections

  In this study, we describe a strategy to identify undiagnosed respiratory viral infections through screening nasopharyngeal (NP) swabs for the chemokine CXCL10, which is highly induced in the nasopharynx as part of the host antiviral response. Using this strategy, we conducted two screens: first, we screened NP swabs collected at Yale New Haven Hospital (YNHH) in January 2017 from patients with undiagnosed respiratory viral infections and identified patients infected with seasonal coronaviruses and the relatively uncommon influenza C virus. Second, we screened samples from the beginning of March 2020 in the weeks before YNHH tested for SARS-CoV-2 and identified four patients that had undiagnosed SARS-CoV-2 infections. Sequences uploaded as part of this study include samples with rhinovirus, human coronavirus NL63, and 8 samples as part of the January 2017 screen for undiagnosed respiratory viral infections.

  Study phs002442

• Cholesterol homeostasis and lipid raft dynamics at the basis of tumor-induced immune dysfunction in chronic lymphocytic leukemia

  Autologous T-cell therapies show limited efficacy in chronic lymphocytic leukemia (CLL), where acquired immune dysfunction prevails. In CLL, disturbed mitochondrial metabolism has been linked to defective T-cell activation and proliferation. Recent research suggests that lipid metabolism regulates mitochondrial function and differentiation in T cells, yet its role in CLL remains unexplored. This comprehensive study compares T-cell lipid metabolism in CLL patients and healthy donors, revealing critical dependence on exogenous cholesterol for human T-cell expansion following TCR-mediated activation. Using multi-omics and functional assays, we found that T cells present in viably frozen samples of patients with CLL (CLL T cells) showed impaired adaptation to cholesterol deprivation and inadequate upregulation of key lipid metabolism transcription factors. CLL T cells exhibited altered lipid storage, with increased triacylglycerols and decreased cholesterol, and inefficient fatty acid oxidation (FAO). Functional consequences of reduced FAO in T cells were studied using samples from patients with inherent FAO disorders. Reduced FAO was associated with lower T-cell activation but did not affect proliferation. This implicates low cholesterol levels as a primary factor limiting T-cell proliferation in CLL. Consequently, CLL T cells displayed fewer and less clustered lipid rafts, potentially explaining the impaired immune synapse formation observed in these patients. Our findings highlight significant disruptions in lipid metabolism as drivers of functional deficiencies in CLL T cells, underscoring the pivotal role of cholesterol in T-cell proliferation. This study suggests that modulating cholesterol metabolism could enhance T-cell function in CLL, presenting novel immunotherapeutic approaches to improve outcome in this challenging disease.

  Dac EGAC50000000556

• From matrimonial practices to genetic diversity in Southeast Asian populations: the signature of the matrilineal puzzle

  This project aims at revisiting the "matrilineal puzzle" from a population genetics' point of view. The dataset consists of 719 individuals from 12 populations sampled in continental Southeast Asia and genotyped at 598764 loci. This dataset can only be accessed and used for non-commercial research purposes with a finality complying with the informed consent provided by donors. For accessing the data, please provide: 1. An explicit title for the project you wish to use the data for. 2. A detailed institutional affiliation of all recipients and users of the data. 3. A summary (500 words) of the research project, with emphasis on its scientific and societal finality, and predicted outputs. If access is granted by the DAC, data cannot be shared with a third party not initially involved in the project, without the third party officially applying for accessing the data.

  Study EGAS00001003727

• Single-cell analysis reveals fibroblast clusters linked to immunotherapy resistance in cancer

  A subset of Cancer-Associated Fibroblasts (CAF-S1) mediates immunosuppression in breast cancers (BC), but its heterogeneity and its impact on immunotherapy response remain unknown. Here, we identify 8 CAF-S1 clusters by analyzing more than 18000 single CAF-S1 fibroblasts from BC. We validate the 5 most abundant clusters by flow cytometry and in silico analyses in other cancer types, highlighting their relevance. Myofibroblasts from clusters 0 and 3, characterized by extra-cellular matrix proteins and TGF signaling respectively, are indicative of primary resistance to immunotherapies. Cluster 0 up-regulates PD-1 and CTLA-4 protein levels in regulatory T lymphocytes (Tregs), which in turn increases CAF-S1 cluster 3 cellular content. Thus, our study highlights a positive feedback loop between specific CAF-S1 clusters and Tregs and uncovers their role in immunotherapy resistance.

  Study EGAS00001004030