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• Tumour sample for patient SA239

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA239

  Dataset EGAD00001009353

• Tumour sample for patient SA300

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA300

  Dataset EGAD00001009354

• Tumour sample for patient SA425

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA425

  Dataset EGAD00001009356

• Tumour sample for patient SA423

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA423

  Dataset EGAD00001009355

• Tumour sample for patient SA495

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA495

  Dataset EGAD00001009357

• Mucosal 16S metadata

  Metadata for 16S-V4 rRNA gene sequence data for intestinal biopsies from NCT02749630 trial participants.

  Dataset EGAD00001008823

• Sequencing data for oesophageal and related samples - Abbas et al (WGS)

  Data supporting: "Mutational signature dynamics shaping the evolution of oesophageal adenocarcinoma" Abbas et al (WGS for 1397 samples)

  Dataset EGAD00001011196

• Colorectal cancer organoid-stroma biobank cohort

  In colorectal cancers (CRC) the tumor microenvironment plays a key role for prognosis and therapy efficacy. Patient-derived tumor organoids (PDTOs) show enormous potential for preclinical testing, however, purely epithelial cultures features including the ‘consensus molecular subtypes’ (CMS) are largely eradicated. To better reflect the cell type heterogeneity, we established the CRC organoid-stroma biobank of matched PDTOs and cancer-associated fibroblasts (CAFs) from 30 patients. Whole exome sequencing and transcriptome analysis in various in vitro and in vivo contexts was performed to study the influence of the TME on the CRC phenotype.

  Dataset EGAD00001011173

• COVID-19 Multiomics Atlas

  We provide a single-nuclei RNA-sequencing (snRNA-seq) dataset derived from four COVID-19 patients, generated using the 10x Chromium Next GEM Single Cell v3.1 kit. For our study, these were integrated with snRNA-seq data with 12 publicly available sc/snRNA-seq datasets, comprising organ donor lung samples (n=89) and COVID-19 lung tissue samples (n=51). Additionally, we provide a spatial transcriptomic dataset characterizing different histopathological stages of diffuse alveolar damage, across a cohort of 33 COVID-19 patients. This was generated using the Nanostring Whole Transcriptome Assay (WTA) with regions of interest (ROIs) sized 400 µm² each. This integrated multi-omics analysis of snRNA-seq, histology, and spatial transcriptomics data, is available for exploration and download via our web portal: https://covid19-multiomicatlas.cellgeni.sanger.ac.uk/.

  Dataset EGAD00001015404

• Acral Melanoma PDXs from the admixed Brazilian Population - Tumour and unfiltered PDX sample CRAM files - Whole exome sequencing data

  CRAM files containing the whole exome data for Tumours, and unfiltered Patient Derived Xenograft samples mapped to build GRCh38. Acral melanoma (AM) is an aggressive melanoma subtype with limited therapeutic options and poor outcomes. In non-European descent and admixed populations, like in Latin America, it can account for a significant proportion of cutaneous melanoma cases. Here, we performed comprehensive genomic and functional profiling of AM from a uniquely diverse Brazilian cohort. Whole-exome and transcriptome sequencing was performed on both tumours and patient-derived xenograft (PDX) samples. The PDX were obtained from a comprehensive collection of patient-derived xenograft (AM-PDX) models that we established which faithfully retained the histopathological and genomic features of the original tumours.

  Dataset EGAD00001015740

• Acral Melanoma PDXs from the admixed Brazilian Population - Tumour VCF files with somatic SNV and INDELs - Whole exome sequencing data

  Raw, flagged and annotated VCF files with somatic calls made with CavEMan and Pindel for Acral Tumours. Variant effect prediction was run with Ensembl VEP v103.Acral melanoma (AM) is an aggressive melanoma subtype with limited therapeutic options and poor outcomes. In non-European descent and admixed populations, like in Latin America, it can account for a significant proportion of cutaneous melanoma cases. Here, we performed comprehensive genomic and functional profiling of AM from a uniquely diverse Brazilian cohort. Whole-exome and transcriptome sequencing was performed on both tumours and patient-derived xenograft (PDX) samples. The PDX were obtained from a comprehensive collection of patient-derived xenograft (AM-PDX) models that we established which faithfully retained the histopathological and genomic features of the original tumours.

  Dataset EGAD00001015741

• Acral Melanoma PDXs from the admixed Brazilian Population - filtered PDX sample BAM files - RNAseq

  BAM files containing the whole exome data for the Patient Derived Xenograft samples mapped to build GRCh38. All files have been processed with XenofilteR to remove mouse reads. Acral melanoma (AM) is an aggressive melanoma subtype with limited therapeutic options and poor outcomes. In non-European descent and admixed populations, like in Latin America, it can account for a significant proportion of cutaneous melanoma cases. Here, we performed comprehensive genomic and functional profiling of AM from a uniquely diverse Brazilian cohort. Whole-exome and transcriptome sequencing was performed on both tumours and patient-derived xenograft (PDX) samples. The PDX were obtained from a comprehensive collection of patient-derived xenograft (AM-PDX) models that we established which faithfully retained the histopathological and genomic features of the original tumours.

  Dataset EGAD00001015746

• Acral Melanoma PDXs from the admixed Brazilian Population - filtered PDX sample BAM files - Whole exome sequencing data

  BAM files containing the whole exome data for the Patient Derived Xenograft samples mapped to build GRCh38. All files have been processed with XenofilteR to remove mouse reads. Acral melanoma (AM) is an aggressive melanoma subtype with limited therapeutic options and poor outcomes. In non-European descent and admixed populations, like in Latin America, it can account for a significant proportion of cutaneous melanoma cases. Here, we performed comprehensive genomic and functional profiling of AM from a uniquely diverse Brazilian cohort. Whole-exome and transcriptome sequencing was performed on both tumours and patient-derived xenograft (PDX) samples. The PDX were obtained from a comprehensive collection of patient-derived xenograft (AM-PDX) models that we established which faithfully retained the histopathological and genomic features of the original tumours.

  Dataset EGAD00001015748

• Whole Exome Sequencing for the paper titled "Orthotopic Patient-Derived Xenografts of Pediatric Solid Tumors"

  Whole Exome Sequencing for the paper titled "Orthotopic Patient-Derived Xenografts of Pediatric Solid Tumors"

  Dataset EGAD00001003434

• ExomeSeq-EGAS00001001306

  Exome Sequencing. 3 μg of genomic DNA from each sample were sheared and used for the construction of a paired-end sequencing library as described in the paired-end sequencing sample preparation protocol provided by Illumina41. Enrichment of exonic sequences was then performed for each library using either the Sure Select Human All Exon 50 Mb or All Exon+UTRs v4 kits following the manufacturer’s instructions (Agilent Technologies). Exon-enriched DNA was pulled down by magnetic beads coated with streptavidin (Invitrogen), followed by washing, elution and 18 additional cycles of amplification of the captured library. Enriched libraries were sequenced (2 × 76 bp) in one lane of an Illumina GAIIx sequencer or in two lanes of a HiSeq2000 when using pools of eight samples.

  Dataset EGAD00001001464

• Pilot experiment on functional genomics in osteoarthritis_RNA

  The aim of this work is to apply an integrated systems approach to understand the biological underpinnings of large joint (hip and knee) osteoarthritis which culminates in the need for total joint replacement (TJR). In this pilot we will assess the feasibility of the approach in the relevant tissue. We will obtain diseased and non-diseased tissue (cartilage and endochondral bone) following TJR, coupled with a blood sample, from 12 patients. We will characterise the 12 pairs of diseased and non-diseased tissue samples in terms of transcription (RNASeq) The pilot will help assess the feasibility of isolating sufficient levels of starting material for the different approaches, and will instigate the development of analytical approaches to synthesising the resulting data.

  Dataset EGAD00001001331

• Preeclampsia InterPregGen Consortium: Whole Genome Sequencing of 100 unrelated Uzbeks (DNA samples from the Institute of Immunology, Uzbek Academy of Sciences, Tashkent, Uzbekistan; Republic Specialized Scientific Practical Medical Centre of Obstetrics and Gynecology, Tashkent, Uzbekistan)

  Whole genome sequencing of 100 unrelated Uzbeks in order to impute genotypes into PE cases and controls from Uzbekistan and to provide genetic data and infrastructure for future genetic studies in Uzbekistan and Central Asia more generally and to fill a gap in worldwide information as Central Asia is not adequately represented in available genomic data. This dataset is one component of the InterPregGen FP7 project. DNA samples for this component were collected by InterPregGen Consortium collaborators in Tashkent, Uzbekistan at the Institute of Immunology, Uzbek Academy of Sciences and at the Republic Specialized Scientific Practical Medical Centre of Obstetrics and Gynecology.

  Dataset EGAD00001005466

• Cell line data (RNAseq, ATACseq, ChIPseq)

  Content: 2 GB RTK I cell lines (LN229, ZH487) in two conditions (NT control and shSOX10). RNAseq: single replicates per condition, polyA+ RNA sequencing, SE. ATACseq: biological replicates per condition, SE. ChIPseq (histone H3 modifications, LN229 only): all marks for each condition were pooled and sequenced on two lanes for each pool. ChIPseq (BRD4 and SOX10): SOX10 libraries were sequenced on single lanes. BRD4 samples were multiplexed and sequenced in two lanes. ChIPseq input samples are also included. Data type and technology: RNAseq: SE 50bp sequenced on HiSeq2000/4000. ATACseq: SE 50bp sequenced on HiSeq2000/4000. ChIPseq: SE 50bp sequenced on HiSeq2000/4000.

  Dataset EGAD00001005493

• Center for Common Disease Genomics [CCDG] - Cardiovascular: Genetics of Coronary Heart Disease - Characterizaton of Coronary Prone Pedigrees

  The primary cohort includes samples from 499 men and 154 women who survived a myocardial infarction, percutaneous transluminal angioplasty, or coronary artery bypass grafting (CABG) by age 55 years for men or age 65 years for women. Patients were seen at least six months after their acute event. Samples from another 488 men and 541 women that showed a nearly identical age, gender, and measured blood pressure distribution were collected as population-based controls. These controls tended to live in urban Salt Lake City, where the vast majority of the population is Caucasian. Blood samples were collected in the morning after 12h to 16h of fasting and prepared according to guidelines of the Lipid Research Clinic's program Manual of Laboratory Operations. All samples have serum, DNA and/or white blood cells, and a host of measurements (e.g. standard clinical chemistries, LDL and HDL cholesterol, triglycerides, glucose, HbA1C, insulin, blood pressures, anthropometric data, information on medical conditions and drug use, etc.). Additional details about the cohort or sample preparation were published previously. Here we present in total 1,475 patients that were successfully sequenced. This number includes 228 women, 419 men, and 7 of unreported gender survivors as well as 339 women and 482 men that served as population-based controls.

  Study phs001901

• Machine Learning Signal Enrichment for Ultrasensitive Plasma Tumor Burden Monitoring

  In solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate assessment of minimal residual disease (MRD) and therapeutic response monitoring. To overcome the sparsity of ctDNA fragments in low tumor fraction (TF) settings and increase MRD sensitivity, we previously leveraged genome-wide mutational integration through plasma whole genome sequencing (WGS). We now introduce MRD-EDGE, a composite machine learning-guided WGS ctDNA single nucleotide variant (SNV) and copy number variant (CNV) detection platform designed to increase signal enrichment. MRD-EDGESNV uses deep learning and a ctDNA-specific feature space to increase SNV signal-to-noise enrichment in WGS by 300X compared to previous WGS error suppression. MRD-EDGECNV also reduces the degree of aneuploidy needed for ultrasensitive CNV detection through WGS from 1 Gb to 200 Mb, thereby expanding its applicability to a wider range of solid tumors. We harness the improved performance to identify MRD following surgery in multiple cancer types, track changes in tumor burden in response to neoadjuvant immunotherapy in non-small cell lung cancer (NSCLC) and demonstrate ctDNA shedding in precancerous colorectal adenomas. Finally, the radical signal-to-noise enrichment in MRD-EDGESNV enables de novo mutation calling in melanoma and small cell lung cancer (SCLC) without matched tumor, yielding clinically informative TF monitoring for patients on immune checkpoint inhibition (ICI).

  Study EGAS00001007451

• Transcriptome sequencing of gingivo-buccal oral squamous cell carcinoma for integrative analysis: alterations in expression of genes attributable to methylation changes

  Gingivo-buccal oral squamous cell carcinoma (OSCC-GB) is the most common cancer among men in India and is associated with high mortality. Although OSCC-GB is known to be quite different from tongue cancer in its genomic presentation and its clinical behavior, it is treated identically as tongue cancer. Predictive markers of prognosis and therapy that are specific to OSCC-GB are, therefore, required. To achieve this, we have carried out transcriptome (n=72) profiling of paired tumor-normal tissues collected from OSCC-GB patients from India. RNA sequencing was performed on tumor and paired adjacent normal samples from 72 OSCC-GB patients. From each patient, total RNA was extracted from tumor and normal tissue samples using AllPrep DNA/RNA Mini Kit (QIAGEN). The quality and concentration of isolated total RNA were checked using Agilent 2100 Bioanalyzer and NanoDrop 2000 (Thermo Fisher Scientific). The OD260/OD280 ratio was ≥ 2 and RNA Integrity Number (RIN) was ≥ 7.0 for all sequenced samples. Ribosomal RNA (rRNA) was removed from the RNA samples, using Ribo-Zero Magnetic Kit (Epicentre). Sequencing libraries were prepared from rRNA depleted samples using TrueSeq RNA Sample Preparation Kit (Illumina). Each triplex cDNA library pool was sequenced as 100bp paired-end on HiSeq-2000 or HiSeq-2500 (Illumina). Protocols suggested by the manufacturers were used for all assays.

  Study EGAS00001003893

• Patient-derived tumor organoids for personalized medicine in a rare case of hepatocellular carcinoma with neuroendocrine differentiation.

  We report the case of a 74-year-old man with a very rare subtype of hepatocellular carcinoma with neuroendocrine differentiation (HCC-NED). The patient presented with two independent tumors, a gastrointestinal stromal tumor in the stomach and a hepatocellular carcinoma in the liver. Both tumors were surgically removed in curative intent. Histopathological work-up of the liver tumor revealed poorly differentiated hepatocellular carcinoma (Edmondson-Steiner grade IV) with diffuse expression of neuroendocrine markers synaptophysin (SYP) and chromogranin (CHGA). Three months after resection, multifocal recurrence of the HCC with neuroendocrine differentiation (HCC-NED) was observed. In the meantime, tumor organoids have been generated from the resected HCC-NED and extensively characterized. Sensitivity to a number of drugs approved for the treatment of HCC or neuroendocrine carcinomas was tested in vitro. Based on their in vitro efficacy, etoposide and carboplatin were used as first line palliative combination treatment. Because genomic analysis revealed a NTRK1-mutation (kinase domain) and tumor organoids were sensitive to entrectinib, a pan-TRK inhibitor, the patient received entrectinib as second line therapy. After only two weeks, treatment had to be discontinued due to deterioration of the patient’s general condition. In conclusion, we demonstrate for the first time that preclinical drug testing using organoids is feasible in selected HCC cases.

  Study EGAS00001005887

• Machine learning guided signal enrichment for ultrasensitive plasma tumor burden monitoring

  In solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate assessment of minimal residual disease (MRD) and therapeutic response monitoring. To overcome the sparsity of ctDNA fragments in low tumor fraction (TF) settings and increase MRD sensitivity, we previously leveraged genome-wide mutational integration through plasma whole genome sequencing (WGS). We now introduce MRD-EDGE, a composite machine learning-guided WGS ctDNA single nucleotide variant (SNV) and copy number variant (CNV) detection platform designed to increase signal enrichment. MRD-EDGESNV uses deep learning and a ctDNA-specific feature space to increase SNV signal-to-noise enrichment in WGS by 300X compared to previous WGS error suppression. MRD-EDGECNV also reduces the degree of aneuploidy needed for ultrasensitive CNV detection through WGS from 1 Gb to 200 Mb, thereby expanding its applicability to a wider range of solid tumors. We harness the improved performance to identify MRD following surgery in multiple cancer types, track changes in tumor burden in response to neoadjuvant immunotherapy in non-small cell lung cancer (NSCLC) and demonstrate ctDNA shedding in precancerous colorectal adenomas. Finally, the radical signal-to-noise enrichment in MRD-EDGESNV enables de novo mutation calling in melanoma and small cell lung cancer (SCLC) without matched tumor, yielding clinically informative TF monitoring for patients on immune checkpoint inhibition (ICI).

  Study EGAS00001007545

• DAC Longitudinal Multi-Omics Study Reveals Molecular Drivers and Tumor Microenvironment in Extramedullary Multiple Myeloma

  Data access requests for the raw data used in publication "Longitudinal Multi-Omics Study Reveals Molecular Drivers and Tumor Microenvironment in Extramedullary Multiple Myeloma"

  Dac EGAC50000000016

• DAC Whole Exome Sequences from Eivissan and Menorcan Individuals

  30 and 21 whole exome sequences for Eivissan and Menorcan healthy unrelated volunteers, respectively. The exomes were captured with the Agilent SureSelect Human All Exon V6 capture kit and sequences in Illumina platforms.

  Dac EGAC50000000249

• DAC for lymphoma IFZ Essen

  This DAC is set in place to handle acess to data on lymphomas and immune cells submitted by scientists from the Institute of Cell Biology (Cancer Research) at the University of Duisburg-Essen in Essen, Germany.

  Dac EGAC50000000521

• Dataset for whole exome sequencing of PTCLs

  The dataset consists of whole exome sequencing FASTQ files and analyzed data, including single nucleotide variants (SNVs) and short insertions and deletions (Indels) of candidate driver genes.

  Dataset EGAD50000001798

• β-catenin ChIP sequencing in HCC models.

  This dataset contains ChIP sequencing data for β-catenin, H3K27ac and H3K27me3 from three HCC cell lines and five tumour organoids under normal conditions and oleic acid treatment.

  Dataset EGAD50000001816

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0187_002

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0167_003 for Diffuse large B-cell lymphoma patient sample TFRIPAIR10

  Dataset EGAD50000001372

• ATAC-seq samples from 9 cHL cell lines

  The dataset contains 21 ATAC-seq samples from 9 cHL cell lines. Files within the dataset are raw fastq files for each cell line.

  Dataset EGAD50000001273

• Adaptive nanopore sequencing of chrX from peripheral samples

  Analysis of skewed X inactivation for X-linked disorders

  Dataset EGAD50000000638

• Dataset for RNA sequencing of Glioblastoma samples

  This dataset contains 10x scRNA sequencing of glioblastoma samples. Sequencing was performed on a Illumina HiSeq 4000. The sequencing was always paired.

  Dataset EGAD50000000081

• uganda_autosomes

  Genotype data (in binary PLINK format) and imputed data (with merged 1000Gp3 and AGVP reference panel in GEMMA BIMBAM dosage format) for 1391 individuals from EMaBS in Entebbe, Uganda.

  Dataset EGAD00010002578

• Benchmark Dataset DIA Clinical Proteomics LymphNodes E.coli

  Real patient variability Benchmark Dataset for Optimization of DIA data analysis workflows

  Dataset EGAD00010002223

• RP1759 AYA sarcoma methylation array

  Raw methylation array data for tumor samples from patients with newly diagnosed, recurrent intermediate or high-grade sarcoma.

  Dataset EGAD00010002275

• SNPArray_TW

  The compressed file contains plink format file for the Affymetrix Human Origins SNP array data of 55 individuals generated and analyzed in Liu et al 2023 study of Taiwanese groups.

  Dataset EGAD00010002424

• GCAT| SNParray coreSpain V2

  4988 samples issued from GCAT cohort, genotyped with MEGAex-Infinium Array, with data for Cr1-22. Plink files with QC and imputed (SHAPEIT+IMPUTE).

  Dataset EGAD00010001664

• DCC_R26.PRAD-CNSM-Array

  Raw Array data from the PRAD-CA for ICGC DCC Release26

  Dataset EGAD00010001414

• DCC_R26.2.PRAD-CNSM-Array

  Raw Array data from the PRAD-CA for ICGC DCC Release27

  Dataset EGAD00010001519

• DATA FILES FOR NBL

  Neuroblastoma whole genome sequencing

  Dataset EGAD00001000135

• Pineoblastoma Single-Nuclei RNA-seq Data Access Committee (St. Jude)

  Committee responsible for reviewing and approving external access requests to controlled-access pediatric brain tumor transcriptomic datasets from St. Jude Children's Research Hospital, ensuring alignment with patient consent and institutional ethics policies.

  Dac EGAC50000000839

• Alveolar Rhabdomyosarcoma sequencing data

  This dataset comprises DNA sequencing for tumor and matched normal from an Alveolar Rhabdomyosarcoma patient. It also include RNA sequencing data from the tumor sample.

  Dataset EGAD00001006622

• WES of CTCL patients

  Paired end whole exome sequencing (WES) data of tumor/normal pairs (sorted malignant CD3+/Vb+ T-cells and CD19+ non-malignant B-cells) for the identification of somatic mutation.

  Dataset EGAD00001006895

• PIK3CA SiMSen-Seq

  Simple, Multiplexed, PCR-based barcoding of DNA for Sensitive mutation detection using Sequencing (SiMSen-Seq) of 11 PIK3CA hotspot mutations in plasma DNA of breast cancer patients.ng

  Dataset EGAD00001006897

• Richter Syndrome targeted NGS (13 genes)

  Targeted exome sequencing for a panel of 13 CLL driver genes

  Dataset EGAD00001009509

• BAM-file spanning the breakpoint region +/- 100kb of Ewing sarcoma

  Extracted regions from WGS of Ewing sarcoma spanning fusion breakpoints +/- 100kb for ctDNA tracking in plasma

  Dataset EGAD00001009110

• Clinical-Epidemiological (CE) dataset from an Erasmus MC COVID-19 cohort

  This dataset comprises of Clinical-Epidemiological (CE) data from an Erasmus MC cohort of 151 individuals who were tested positive for COVID-19.

  Dataset EGAD00001009748

• RNA-seq data for ATLAS paper (123 patients)

  RNA-seq data of multi-region samples from PLANET 123 Patient cohort

  Dataset EGAD00001009859

• Sequencing data for the manuscript "Multi-focal sampling of de novo metastatic prostate cancer reveals complex polyclonality and enables accurate clinical genotyping"

  This submission includes targeted and whole exome paired-end fastq files.

  Dataset EGAD00001009651

• Nanopore low-pass WGS of human brain tumors

  Nanopore low-pass WGS of human brain tumors for evaluation of DNA methylation-based classification of cancer

  Dataset EGAD00001009663