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• The gut microbiota in prediabetes and diabetes: a population-based cross-sectional study

  The link between the gut microbiota and type 2 diabetes (T2D) warrants further investigation because of known confounding effects from antidiabetic treatment. Here we profiled the gut microbiome in a discovery (n=1011) and validation (n=484) cohort comprising Swedish subjects naive for diabetes treatment and grouped by glycemic status.

  Study EGAS00001004480

• Clonal architectures predict clinical outcome in clear cell renal cell carcinoma

  We analyze the clonal architectures of ccRCC patients from three different populations, including TCGA, Japanese and Chinese patients. We characterize the mutational signatures across different populations and evolution stages. The TCGA and Japanese data sets were downloaded from published studies and we also generated the whole genome sequencing data for more than 40 Chinese patients.

  Study EGAS00001003447

• Finding structural variation and functional consequences from the primary leukemia cells (AML) at the single-cell level

  In this study, we aimed to identify somatic structural variation of acute myeloid leukemia (AML) at the single-cell level and investigate its direct consequence on the nucleosome occupancy using scNOVA approach. For this purpose, we performed strand-specific single-cell sequencing of primary leukemia samples from 32 year old male donor.

  Study EGAS00001004903

• Bone marrow single cell genomics from blood cancer samples

  The overall goal of this study was to characterize bone marrow cells based on their transcriptome, surface protein expression and BCR- and TCR VDJ-profile for accurate identification of clinically relevant cell states. This project has received funding from the European Union Horizon 2020 research and innovation programme under grant agreement No 824110 (EASI-Genomics)

  Study EGAS00001007332

• Blueprint: A human variation panel of genetic influences on epigenomes and transcriptomes in three immune cell types, (ChIP-Seq for CD14-positive, CD16-negative classical monocyte, on genome GRCh37)

  ChIP-Seq data for 172 CD14-positive, CD16-negative classical monocyte sample(s). 572 run(s), 345 experiment(s), 340 analysis(s) on human genome GRCh37. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/blueprint_Epivar/protocols/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002672

• MutWP5: CRUK Mutographs of Cancer: Breast: Cancer Mastectomy (Targeted) (2020-01-29)

  Sequencing of LCM-derived microbiopsies from 30 women who mastectomies due to Breast Cancer. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Targeted data will be used as a driver and clonality screen, highly clonal or driver-containing samples will subsequently be sent for whole-genome sequencing. Results from this portion of the study will be compared to women who had cosmetic breast reduction surgeries and those with germline BRCA 1/2 mutations. . This dataset contains all the data available for this study on 2020-01-29.

  Dataset EGAD00001005923

• Blueprint: A human variation panel of genetic influences on epigenomes and transcriptomes in three immune cell types, (ChIP-Seq for CD4-positive, alpha-beta T cell, on genome GRCh37)

  ChIP-Seq data for 154 CD4-positive, alpha-beta T cell sample(s). 355 run(s), 265 experiment(s), 250 analysis(s) on human genome GRCh37. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/blueprint_Epivar/protocols/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002673

• Genetic regulation of RNA splicing in human pancreatic islets

  Here we provide access to newly generated RNA-seq data for 101 human islet samples used to map genetic effects on gene expression and alternative splicing (eQTLs and sQTLs) in a total of 399 human islets. We also make publicly available genotyping array data for 128 human islets, including the fraction of 101 human islet samples with existing RNA-seq data.

  Dataset EGAD00001009102

• A98299B

  Whole genome sequencing for single cells for library A98299B 991 cells; filetype=bam

  Dataset EGAD00001007087

• Whole Transcriptome Analysis + AbSeq + Sample Tag Multiplexing

  Multiomics data for a cohort of 20 COVID-19 patients (10 patients mild, 3 patients moderate, 4 patients severe, 3 patients critical) obtained from peripheral blood mononuclear cells (PBMCs) from longitudinally sampled at hospital admission, discharge, and 1 month thereafter. The data has been obtained a multiwell-based single-cell technology (BD Rhapsody) that includes the analysis of PBMCs' whole transcriptome and a set of 52 surface proteins. The samples of the different patients at different collection times were labelled using a cell hashing strategy with the BD Single-Cell Multiplexing Kit (6 samples for each run).

  Dataset EGAD00001011318

• RNA and whole-exome sequencing of 22 patients with non-small cell lung cancer

  Whole exome sequencing from pre-treatment samples and matched blood normals from 22 patients. Of these individuals, on-treatment samples are available for a subset of 18 patients. RNA sequencing from pre-treatment samples from 21 patients. Of these individuals, on-treatment samples are available for a subset of 15 patients.

  Dataset EGAD00001008733

• MutWP5: CRUK Mutographs of Cancer: Breast: BRCA Carriers (Targeted) (2020-01-29)

  Sequencing of LCM-derived microbiopsies from 20 women who underwent risk-reducing reduction mastectomies due to germline BRCA1/2. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Targeted data will be used as a driver and clonality screen, highly clonal or driver-containing samples will subsequently be sent for whole-genome sequencing. Results from this portion of the study will be compared to women who had cosmetic breast reduction surgeries and those with cancer. . This dataset contains all the data available for this study on 2020-01-29.

  Dataset EGAD00001005920

• Blueprint: A human variation panel of genetic influences on epigenomes and transcriptomes in three immune cell types, (RNA-Seq for CD14-positive, CD16-negative classical monocyte, on genome GRCh37)

  RNA-Seq data for 197 CD14-positive, CD16-negative classical monocyte sample(s). 197 run(s), 197 experiment(s), 197 analysis(s) on human genome GRCh37. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/blueprint_Epivar/protocols/README_rnaseq_analysis_sanger_20160816

  Dataset EGAD00001002674

• Genotype data for The admixture histories of Cabo Verde - genotype data

  Datasets used in the article "The genetic and linguistic admixture histories of the islands of Cabo Verde" by Laurent R et al. eLife 2023 (DOI: https://doi.org/10.7554/eLife.79827 - URL: https://elifesciences.org/articles/79827) As per Materials and Methods herein, the genotype data corresponds to 2,118,722 autosomal SNPs genotyped from the IlluminaOmni 2.5 Million BeadChip for 233 Cabo Verdean volunteer participants, family unrelated at the 2nd degree based on population genetics analyses (see Material and Methods). SNP rsID, Chromosome position and genetic position in (bp) are in Build GRCh38. Cabo Verdean individuals are designated with an alphanumeric unique code

  Dataset EGAD00001008979

• Systematic comparative analysis of single-nucleotide variant detection methods from single-cell RNA sequencing data

  In this study, we performed systematic comparative analysis of seven widely-used SNV-calling methods, including SAMtools, the GATK Best Practices pipeline, CTAT, FreeBayes, MuTect2, Strelka2 and VarScan2, on both simulated and real single-cell RNA-seq datasets. We generated SMART-seq2 data for 70 CD45- single cells, which were derived from two colorectal cancer patients (P0411 and P0413). The average sequencing depths of these cells were 1.4 million reads per cell. We also generated tumor and adjacent normal bulk WES data, as well as tumor bulk RNA-seq data for these patients.

  Dataset EGAD00001005373

• Genomic profiling of BRCA- mutant breast cancer tumors

  This data set contains whole exome sequencing (WXS) and RNA-Seq on germline BRCA- mutant tumors from 18 patients. BAM files are provided for WXS on tumor and germline samples. FASTQ files are provided for the RNA-Seq samples. Sequencing was done on an Illumina Hi-Seq 2500.

  Dataset EGAD00001008276

• MutWP5: CRUK Mutographs of Cancer: Breast: BRCA Carriers (Exome) (2020-01-29)

  Sequencing of LCM-derived microbiopsies from 20 women who underwent risk-reducing reduction mastectomies due to germline BRCA1/2. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Exome data will be used as a driver and clonality screen, highly clonal or driver-containing samples will subsequently be sent for whole-genome sequencing. Results from this portion of the study will be compared to women who had cosmetic breast reduction surgeries and those with cancer. . This dataset contains all the data available for this study on 2020-01-29.

  Dataset EGAD00001005921

• MutWP5: CRUK Mutographs of Cancer: Breast: Cancer Mastectomy (Exome) (2020-01-29)

  Sequencing of LCM-derived microbiopsies from 30 women who underwent mastectomies due to a breast cancer diagnosis. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Exome data will be used as a driver and clonality screen, highly clonal or driver-containing samples will subsequently be sent for whole-genome sequencing. Results from this portion of the study will be compared to women who had cosmetic breast reduction surgeries and those with germline BRCA 1/2 mutations. . This dataset contains all the data available for this study on 2020-01-29.

  Dataset EGAD00001005924

• Blueprint: A human variation panel of genetic influences on epigenomes and transcriptomes in three immune cell types, (RNA-Seq for CD4-positive, alpha-beta T cell, on genome GRCh37)

  RNA-Seq data for 212 CD4-positive, alpha-beta T cell sample(s). 212 run(s), 212 experiment(s), 212 analysis(s) on human genome GRCh37. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/blueprint_Epivar/protocols/README_rnaseq_analysis_sanger_20160816

  Dataset EGAD00001002671

• BLUEPRINT release August 2016, RNA-Seq for CD34-negative, CD41-positive, CD42-positive megakaryocyte cell, on genome GRCh38

  RNA-Seq data for 6 CD34-negative, CD41-positive, CD42-positive megakaryocyte cell sample(s). 24 run(s), 6 experiment(s), 6 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002339

• BLUEPRINT release August 2014, RNA-Seq for CD34-negative, CD41-positive, CD42-positive megakaryocyte cell

  RNA-Seq data for 4 CD34-negative, CD41-positive, CD42-positive megakaryocyte cell sample(s). 22 run(s), 4 experiment(s), 4 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001000903

• BLUEPRINT release January 2015, RNA-Seq for CD34-negative, CD41-positive, CD42-positive megakaryocyte cell

  RNA-Seq data for 5 CD34-negative, CD41-positive, CD42-positive megakaryocyte cell sample(s). 23 run(s), 5 experiment(s), 5 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001001165

• Sequencing data for Maturity-Onset Diabetes of the Young (MODY) patients in south India

  We performed whole genome, whole or targeted exome sequencing for 289 individuals from India. This included 152 clinically diagnosed MODY and 137 control samples. Whole genome libraries were constructed using TruSeqNano DNA Library Preparation Kit (Illumina, CA) and sequenced on Illumina HiSeq2500 (Illumina, CA). The whole exome analysis was performed using Agilent SureSelect (Santa Clara, CA) Human All Exome kit v5 (50 Mb). Exome capture libraries were sequenced on HiSeq 2500 (Illumina, CA). Targeted exome sequencing was performed using custom probes corresponding to 1965 genes implicated in pancreatic cell biology and/or diabetes.

  Dataset EGAD00001003919

• Clonal expansion of mutated cell population in bladder urothelium (2018-08-03)

  1cm biospies of from patients undergoing bladder cystectomy will be collected. The underlying muscle and stroma will be removed and the remaining epithelia dissected into small sequential areas which will be sent for ultra-deep exome sequencing using a panel of known cancer and viral genes. Sequence analysis using similar methods to Martincorena I et al (Science 2015, 348:880) will provide an idea of the somatic mutational landscape in these patient samples. Individual patient muscle samples will also be sequenced as a reference. . This dataset contains all the data available for this study on 2018-08-03.

  Dataset EGAD00001004274

• BLUEPRINT release August 2015, RNA-Seq for CD34-negative, CD41-positive, CD42-positive megakaryocyte cell, on genome GRCh38

  RNA-Seq data for 5 CD34-negative, CD41-positive, CD42-positive megakaryocyte cell sample(s). 23 run(s), 5 experiment(s), 5 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001534

• Elucidating the heterogeneity of immunotherapy response and immune-related toxicities by longitudinal ctDNA and immune cell compartment tracking in lung cancer

  The dataset for the study Elucidating the heterogeneity of immunotherapy response and immune-related toxicities by longitudinal ctDNA and immune cell compartment tracking in lung cancer includes 207 bam files from hybrid capture targeted error-correction next-generation sequencing (TEC-Seq) from plasma cell-free DNA and matched white blood cell DNA from 30 individuals with non-small cell lung cancer, alongside 46 bam files from whole exome sequencing of tumor and matched normal DNA for 21 individuals with non-small cell lung cancer who received immunotherapy-containing regimens.

  Dataset EGAD00001011991

• CCA RNA-seq data (60 CCA, 6 normal, 16 cell-line)

  Fastq files for RNA-seq for 60 CCAs, 6 normal bile duct tissues, 14 CCA cell-lines (including replicates), and 2 normal cholangiocyte cell-lines (including replicates). RNA was extracted using the Qiagen RNeasy Mini kit. Illumina Tru-Seq Stranded Total RNA kit (Illumina, San Diego, California, USA) was used to prepare RNA libraries from 1 µg of total RNA. Paired-end 150 bp sequencing was performed using Illumina HiSeq4000 sequencer with the paired-end 150 bp read option.

  Dataset EGAD00001011998

• Tumor and normal exomes for 95 PMBCL cases

  Whole-exome sequencing for 95 PMBCL cases (including 21 with matching normal DNA) was performed using a targeted capture approach with the SureSelect Human All Exon V6+UTR bait (Agilent Technologies) followed by massively parallel sequencing of enriched fragments on the HiSeq2500 platform (Illumina). Five libraries were pooled per lane and a 125bp paired-end mode was used. Tumor and normal DNA samples were sequenced to an average of 115X (SD 24X). All reads were aligned to the human reference genome (hg19) using bwa-mem version 0.7.5a29 with optical and PCR duplicates removed using the Picard tool.

  Dataset EGAD00001005780

• A108837A

  Whole genome sequencing for single cells for library A108837A 1435 cells; filetype=bam

  Dataset EGAD00001007090

• A108846A

  Whole genome sequencing for single cells for library A108846A 1670 cells; filetype=bam

  Dataset EGAD00001007091

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

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

  Study EGAS50000001619

• Prospective Lynch Syndrome Database materials

  The Prospective Lynch Syndrome Database data. These data contain necessary clinical tables to reproduce the previous PLSD papers using the clinical tables for individual level cancer incidence by age, sex and MMR gene affected. The tables contain the demographics, individual cancers at given age, and therapeutic and prophylactic surgeries removing total or partial organs.

  Study EGAS50000001715

• Genome Sequencing of Circulating Tumor Cells for Minimally Invasive Molecular Characterization of Multiple Myeloma Pathology

  ​​Multiple Myeloma (MM) develops from well-defined precursor stages known as Monoclonal Gammopathy of Undetermined Significance (MGUS) and Smoldering MM (SMM); however, invasive bone marrow (BM) biopsy limits screening and monitoring strategies for patients. In this study, we enumerated circulating tumor cells (CTCs) from patients with precursor and overt diseases, and developed a novel approach, MinimuMM-seq, which enables detection of translocations and copy number abnormalities through whole-genome sequencing of highly pure CTCs. In a cohort of 51 patients, 24 with paired BM, we applied our method MinimuMM-seq and detected 100% of clinically reported BM biopsy events. The next-generation sequencing (NGS) assay could replace molecular cytogenetics by Fluorescence In Situ Hybridization (FISH) for diagnostic yield and risk classification. In 8 patients we could apply MinimuMM-seq on serially collected samples to track and monitor major clones in peripheral blood. We describe clonal evolution and shifting dynamics of subclones over time, as well as in between blood and marrow compartments. All whole-genome sequencing (WGS) data generated in this study will be made accessible through dbGaP.

  Study phs003084

• M116 Proteome Extracellular Vesicle Profiling

  For extracellular vesicles (ECV) extraction from plasma, 1M ammonium acetate was added to precipitate ECVs on ice for 45 min. Then, 100 mM ammonium acetate was added to the mixture, and ECVs were precipitated by centrifugation at 20,000g for 30 min. ECVs were washed with 50 mM ammonium bicarbonate (Sigma-Aldrich, Cat. 1066-33-7). Then, 600 µl of 1% ammonium deoxycholate (Sigma Aldrich, Cat. K2755-1MG) were added. The concentration of protein in each sample was measured using a bicinchoninic acid assay (BCA assay). Ammonium bicarbonate was used to dilute 500 µg of protein into a final volume of 500 µl. Next, dithiothreitol (Sigma-Aldrich, Cat. D9779) was added to obtain a final concentration of 20 mM, followed by iodoacetamide (Sigma-Aldrich, Cat. I6125) to a final concentration of 40 mM. Next, trypsin (Roche, Cat. RTRYP-RO) was added to the sample in a 1:25 protein ratio and incubated at 37°C overnight. Next day, formic acid (ThermoFisher Scientific, Cat. 28905) in a final concentration of 0.1% was added and extraction of proteins was done using Empore™ Solid Phase Extraction Cartridges (3M), following manufacturer’s instructions. The eluted samples were then centrifuged for 90 min. using a speed vacuum centrifuge (Thermo, RC1010), followed by snap freezing in liquid nitrogen. Then, the samples were kept in a freeze dryer (LyoDry Compact Benchtop, MechaTech) overnight. Next, the samples were reconstituted in 30 µl of 0.1% formic acid (FA) and an o-Phthaladehyde (Oparil) assay was performed to determine the concentration of each sample. After that, the sample was prepared in a concentration of 0.5 µg/µl using 0.1% FA and alcohol dehydrogenase (ADH). The samples were prepared in glass mass spectrometry vials for proteomic analysis using a Waters Synapt G2Si High-Definition Mass Spectrometry (Waters Corporation) operated by the MassLynx 4.1., 110 min. running time with 2 µl of an injection containing 1 µg of peptide. Quality controls were also run along with samples to guarantee consistency. Pooled quality controls were made from all samples, in which the samples were run at the beginning, middle and end of the mass spectrometry run. Samples were randomized before running the experiment. The proteomic data was then imported into Progenesis software 4.2 (Nonlinear Dynamic, UK) to identify and quantify peptides and proteins.

  Dataset EGAD50000001679

• Patient-tailored design for selective co-inhibition of leukemic cell subpopulations

  The extensive primary and secondary drug resistance in many cancer types requires rational approaches to design personalized and selective combinatorial therapies that do not only show synergistic effect in overall cancer cell killing but also result in minimal toxic side effects on non-malignant cells. To address the combinatorial explosion in the number of relevant combinations, we implemented a machine learning approach that prioritizes patient-customized drug combinations with a desired synergy-efficacy-toxicity balance by combining single-cell RNA-sequencing with ex vivo single-agent testing in scarce patient-derived primary cells. When applied to two diagnostic and two refractory AML patient cases, each with a different genetic background, our integrated approach accurately predicted patient-specific combinations that were shown to result not only in synergistic cancer cell co-inhibition but were also capable of targeting specific AML cell subpopulations that emerge in differing stages of disease pathogenesis or treatment regimens. Our data-driven approach provides an unbiased means for systematic identification of personalized combinatorial regimens that selectively co-inhibit leukemic cells while avoiding inhibition of non-malignant cells, and highlight the relevance of considering cell heterogeneity for personalized cancer therapy.

  Study EGAS00001004614

• Imputation analysis file

  This data set includes the following summary level data file used for the imputation data: imputation.sv.assoc.txt: results from single variant association analysis in imputed samples

  Dataset EGAD00010001184

• stilts-G-1

  Human Core Exome Genotyping for 1471 samples from the STudy Into Lean and Thin Subjects (STILTS) cohort

  Dataset EGAD00010001622

• Gencode_741K

  The individuals were genotyped for the Illumina Human Omni Express Bead Chip (OmniExpress), containing 741,000 SNPs. 22 samples were excluded with more than 10% missing genotypes

  Dataset EGAD00010001640

• SAFIR02_Oncoscan

  Genomics to select patients with metastatic breast cancer for targeted therapy (microarray_oncoscan)

  Dataset EGAD00010002241

• CITE-seq raw count matrix

  Raw count matrix for CITE-seq data of PBMC collected from 113 patients.

  Dataset EGAD50000000141

• Raw count matrix scRNA-seq

  Raw count matrix for scRNA-seq data of PBMC collected from 113 patients.

  Dataset EGAD50000000142

• Medulloblastoma dataset

  This dataset contains a tumor + normal DNA sequence data and tumor RNA seq data for a medulloblastoma patient.

  Dataset EGAD50000000384

• Cancer Genomics, ICR, cell line data

  DAC for cell line (non patient) data from the Cancer Genomics group, Division of Genetics and Epidemiology at the Institute of Cancer Research, Sutton, UK.

  Dac EGAC50000000023

• Michigan-Georgetown Cancer DAC

  Genomics data from cancers and/or dysplasias for the collaborations between Maureen Sartor and Nisha D'Silva at the University of Michigan and Laura Rozek at Georgetown University

  Dac EGAC50000000397

• RNAseq for 208 patients with medulloblastoma cancer (MB_COMICS cohort)

  This dataset contains 208 paired fastq files sequenced with Illumina HiSeq 2500.

  Dataset EGAD50000000600

• Short-read scRNA-seq

  10x Chromium Single Cell 3′ single-cell cDNA sequencing data for adrenal tissue sampleA and sampleB.

  Dataset EGAD50000002210

• Targeted PacBio long-read scRNA-seq

  Twist custom capture–based targeted PacBio long-read scRNA-seq datasets for human adrenal sampleA and sampleB

  Dataset EGAD50000002212

• Small RNA and MicroRNA sequencing data

  Small RNA and MicroRNA sequencing data was generated for the multiomics analysis of Eurotarget

  Dataset EGAD50000002294

• Brain mets discovery cohort, orthogonal validation raw sequencing files

  These are the raw sequencing files for the orthogonal validation brain tumour samples in the discovery cohort.

  Dataset EGAD00001005985

• Vitiligo exome sequencing

  Exome sequencing data for 14 Vitiligo samples

  Dataset EGAD00001006371