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• 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

• Single cell transcriptomes of of primary tumors and normal endometrial derived organoids treated with DBZ

  Endometrial carcinoma, the most common gynecologic cancer, develops from endometrial epithelium which is composed of secretory and ciliated cells. Pathologic classification is unreliable and there is a need for prognostic tools. We used single cell sequencing to study organoid model systems derived from normal endometrial endometrium to discover novel markers specific for endometrial ciliated or secretory cells. We performed single cell sequencing on endometrial and ovarian tumours, and on organoids both treated with DBZ and normal and found both secretory-like and ciliated-like tumour cells.

  Dataset EGAD00001006280

• A108759B

  Whole genome sequencing for single cells for library A108759B 1134 cells; filetype=bam

  Dataset EGAD00001007088

• A108768B

  Whole genome sequencing for single cells for library A108768B 1126 cells; filetype=bam

  Dataset EGAD00001007089

• Follicular lymphoma shallow whole genome sequencing and targeted sequencing of lymphoma panel

  Stage I and stage III/IV Follicular lymphoma samples, shallow whole genome sequencing for copy number analysis and targeted capture sequencing for mutation and translocation analysis.

  Dataset EGAD00001008385

• Shallow whole genome sequencing and targeted capture sequencing data of PCNSL and PTL primary and relapse pairs

  Shallow whole genome sequencing for copy number analysis and targeted capture sequencing data for translocation and mutation anslysis of paired primary and relapse PCNSL and PTL samples

  Dataset EGAD00001008387

• WGS files for Klco RPAML

  WGS files for Klco RPAML study titled "Genomics of pediatric myeloid neoplasms"

  Dataset EGAD00001008413

• Single Cell Genome Sequence for DLP+ library A108765A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1181A passage 1 on DLP library A108765A

  Dataset EGAD00001009428

• Single Cell Genome Sequence for DLP+ library A96194A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1053B passage 1 on DLP+ library A96194A

  Dataset EGAD00001009468

• Single Cell Genome Sequence for DLP+ library A96194B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1053E passage 1 on DLP+ library A96194B

  Dataset EGAD00001009469

• Single Cell Genome Sequence for DLP+ library A96200B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1052D passage 1 on DLP+ library A96200B

  Dataset EGAD00001009470

• Single Cell Genome Sequence for DLP+ library A96205B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1049A passage 1 on DLP+ library A96205B

  Dataset EGAD00001009471

• Single Cell Genome Sequence for DLP+ library A96206B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1050F passage 1 on DLP+ library A96206B

  Dataset EGAD00001009472

• Single Cell Genome Sequence for DLP+ library A96207A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1051A passage 1 on DLP+ library A96207A

  Dataset EGAD00001009473

• Single Cell Genome Sequence for DLP+ library A96207B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1052B passage 1 on DLP+ library A96207B

  Dataset EGAD00001009474

• Single Cell Genome Sequence for DLP+ library A96213A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA501 passage 6, cell line SA1090 on DLP+ library A96213A

  Dataset EGAD00001009477

• Single Cell Genome Sequence for DLP+ library A96222A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient SA1105, patient SA1103, patient SA1106, patient SA1104 on DLP+ library A96222A

  Dataset EGAD00001009478

• Single Cell Genome Sequence for DLP+ library A98240A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA530 passage 3 on DLP+ library A98240A

  Dataset EGAD00001009480

• Single Cell Genome Sequence for DLP+ library A98243B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient SA1096A, patient-derived xenograft SA1052D passage 1 on DLP+ library A98243B

  Dataset EGAD00001009481

• Single Cell Genome Sequence for DLP+ library A98279A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1050A passage 1, patient SA1234 on DLP+ library A98279A

  Dataset EGAD00001009486

• Single Cell Genome Sequence for DLP+ library A95621B

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA501 passage 2 on DLP+ library A95621B

  Dataset EGAD00001009487

• Single Cell Genome Sequence for DLP+ library A95621A

  Single Cell Genome Sequence for Immortalized breast epithelium - BRCA2-/-; Tp53-/- cell line 184-hTERT-22 L9 112.109 cell line SA1055 on DLP+ library A95621A

  Dataset EGAD00001009488

• Single Cell Genome Sequence for DLP+ library A95717B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1050D passage 1 on DLP+ library A95717B

  Dataset EGAD00001009489

• Single Cell Genome Sequence for DLP+ library A96141A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA604 passage 8 on DLP+ library A96141A

  Dataset EGAD00001009513

• Tumour sample for patient SA673

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA673

  Dataset EGAD00001009340

• Tumour sample for patient SA674

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA674

  Dataset EGAD00001009341

• Tumour sample for patient SA675

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA675

  Dataset EGAD00001009342

• Tumour sample for patient SA676

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA676

  Dataset EGAD00001009343

• Tumour sample for patient SA677

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA677

  Dataset EGAD00001009344

• Tumour sample for patient SA678

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA678

  Dataset EGAD00001009345

• Tumour sample for patient SA679

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA679

  Dataset EGAD00001009346

• Tumour sample for patient SA680

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA680

  Dataset EGAD00001009347

• Tumour sample for patient SA681

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA681

  Dataset EGAD00001009348

• Tumour sample for patient SA682

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA682

  Dataset EGAD00001009349

• Tumour sample for patient SA683

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA683

  Dataset EGAD00001009350

• Tumour sample for patient SA221

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA221

  Dataset EGAD00001009351

• Tumour sample for patient SA238

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA238

  Dataset EGAD00001009352

• 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