14977 results for "cancer studies using rna-seq"

in 182.98 milliseconds.

• Genome and transcriptome sequence data from a cervical cancer patient

  Genome and transcriptome sequence data from a cervical cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010947

• Whole exome and targeted sequencing of non-muscle-invasive bladder cancer

  Tumor-blood paired whole-exome sequencing of 58 pairs of non-muscle-invasive bladder cancer samples (stageT1). Targeted sequencing of 112 non-muscle-invasive bladder cancer samples (34 stage T1; 78 stage Ta) Please note the following files have been removed: EGAR00003025153, EGAR00003025435, EGAR00003025294, EGAR00003025262, EGAR00003025224.

  Dataset EGAD00001008332

• Genome and transcriptome sequence data from a breast cancer patient

  Genome and transcriptome sequence data from a breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010315

• Genome and transcriptome sequence data from a pancreatic cancer patient

  Genome and transcriptome sequence data from a pancreatic cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010948

• Genome and transcriptome sequence data from a colorectal cancer patient

  Genome and transcriptome sequence data from a colorectal cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010991

• Genome and transcriptome sequence data from a metastatic ovarian cancer patient

  Genome and transcriptome sequence data from a metastatic ovarian cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001011005

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004689

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004707

• Genome and transcriptome sequence data from an appendix cancer patient

  Genome and transcriptome sequence data from an appendix cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001001309

• Genome and transcriptome sequence data from a breast cancer patient

  Genome and transcriptome sequence data from a breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002030

• Genome and transcriptome sequence data from a breast cancer patient

  Genome and transcriptome sequence data from a breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002048

• Genome and transcriptome sequence data from a breast cancer patient

  Genome and transcriptome sequence data from a breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002531

• Genome and transcriptome sequence data from a breast cancer patient

  Genome and transcriptome sequence data from a breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002549

• Genome and transcriptome sequence data from a metastatic endometrial cancer patient

  Genome and transcriptome sequence data from a metastatic endometrial cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002568

• Genome and transcriptome sequence data from a breast cancer patient

  Genome and transcriptome sequence data from a breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002605

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002643

• Genome and transcriptome sequence data from an ovarian cancer patient

  Genome and transcriptome sequence data from an ovarian cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005829

• Genome and transcriptome sequence data from a pancreatic cancer patient

  Genome and transcriptome sequence data from a pancreatic cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005864

• Whole Exome Sequencing of DNA from Pre-and Post-Chemotherapy Needle Biopsies of Triple Negative and Inflammatory Breast Cancers Enrolled in the S0800 Trial

  Purpose: The purpose of this study was to assess the somatic mutation landscape of breast tumors before and after neoadjuvant chemotherapy. The data includes whole exome sequencing of pre- and post- tissues that were collected in the context of an already published clinical trial SWOG S0800 (ZA Nahleh et al. Breast Cancer Research and Treatment. 158:485-495, 2016). The trial compared the efficacy of sequential nab-paclitaxel followed or preceded by doxorubicin/cyclophosphamide anthracycline chemotherapy with or without bevacizumab as preoperative therapy for stage II-III breast cancer. Experimental Design: 29 pre-treatment biopsies and 9 matching post-treatment surgically resected cancer tissues were available for analysis and were subjected to whole exome sequencing to identify mutational patterns associated with response to neoadjuvant chemotherapy. The 9 paired samples with residual invasive cancer after therapy were also analyzed to assess changes in mutational patterns in response to therapy. No matching normal tissues were available for germline sequencing and therefore we used n=7 post-treatment breast tissues without residual cancer (i.e. complete eradication of cancer by therapy) as a normal cohort to facilitate somatic variant calling.Conclusion: These results suggest that genomic disturbances in BRCA-related DNA repair mechanisms, reflected by a dominant mutational signature 3, confer increased chemotherapy sensitivity. Cancers that survive neoadjuvant chemotherapy, frequently have alterations in cell cycle regulating genes but different genes are affected in different patients.

  Study phs001883

• TOTHER3 dataset

  This dataset contains the FASTQ and BAM files for TOTHER3 study. Targeted DNA-Seq experiment were realized with 49 samples. Since this data was obtained with a panel of genes protected by Intellectual Property (IP), these files only contain information to validate the results published and, in consequence, sensible data had to be specifically removed.

  Dataset EGAD50000000562

• Bulk 3' mRNA-Sequencing of human ASC-derived kidney tubuloids

  Bulk 3' mRNA-Seq raw files (FASTQ) from human kidney tubuloids derived from 4 separate donors in collagen-based dome culture and suspension culture. Samples were collected for sequencing on day 7 of passage 3, 4, and 5. Total = 24 samples.

  Dataset EGAD50000002335

• McGill EMC Community projects Release 7 for cell line "SaOS-2"

  Complete reference epigenome (as defined by IHEC) of a SaOS-2 cell line with osteosarcoma.

  Dataset EGAD00001007678

• Tam-seq of tumor samples for HGSOC copy-number signatures study

  This dataset contains targeted amplicon sequencing of DNA extracted from 300 samples of 142 patients (158 methanol-fixed relapse biopsies and 142 FFPE archival diagnostic tissues). Samples were sequenced on Illumina HiSeq 2500 and were aligned to human genome assembly GRCh37 (hg19)to produce 600 bam files (2 technical replicates per sample).

  Dataset EGAD00001004173

• CBD-RAW-SC-ADT: 10X Single-Cell Features Barcode (CITE-seq)

  Raw Illumina sequencing data and CellRanger BAM output files. For further information regarding this dataset, please contact Stephen Sansom at contact@combat.ox.ac.uk.

  Dataset EGAD00001007962

• Mixture of 2 (closer mtDNA)

  Mixture of 2 unrelated individuals (of close mtDNA haplogroup) sequenced by 10x as a scRNA-seq. The dataset was then processed by Cell Ranger and deconvoluted to yield each individuals genetic profile. The clustering of SNPs is submitted as the processed file. The Sequencing fastqs are submitted as unprocessed files.

  Dataset EGAD00001008727

• Multiple Myeloma ChipSeq data on six histone modifications

  The data contained in this dataset is ChipSeq BAM files aligned to reference genome hg38. The ChipSeq was based on a combination of six histone modifications as follows: H3K4me1, H3K4me3, H3K9me3, H3K27me3, H3K27Ac and H3K36me3. The samples are patient-derived xenografts generated by passaging primary patient CD138+ selected cells through the SCID-rab myeloma mouse model.

  Dataset EGAD00001008353

• Early Detection of Malignant and Pre-Malignant Peripheral Nerve Tumors Using Cell-Free DNA Fragmentomics

  Early detection of neurofibromatosis type 1 (NF1) associated peripheral nerve sheath tumors (PNST) informs clinical decision-making, potentially averting deadly outcomes. Here, we describe a cell-free DNA (cfDNA) fragmentomic approach which distinguishes non-malignant, pre-malignant and malignant forms of NF1 PNST. Using plasma samples from a novel cohort of 101 NF1 patients and 21 healthy controls, we validated that our previous cfDNA copy number alteration (CNA)-based approach identifies malignant peripheral nerve sheath tumor (MPNST) but cannot distinguish among benign and premalignant states. We therefore investigated the ability of fragment-based cfDNA features to differentiate NF1-associated tumors including binned genome-wide fragment length ratios, end motif analysis, and non-negative matrix factorization deconvolution of fragment lengths. Fragmentomic methods were able to differentiate pre-malignant states including atypical neurofibromas (AN). Fragmentomics also adjudicated AN cases suspicious for MPNST, correctly diagnosing samples noninvasively, which could have informed clinical management. Overall, this study pioneers the early detection of malignant and premalignant peripheral nerve sheath tumors in NF1 patients using plasma cfDNA fragmentomics. In addition to screening applications, this novel approach distinguishes atypical neurofibromas from benign plexiform neurofibromas and malignant peripheral nerve sheath tumors, enabling more precise clinical diagnosis and management.

  Study phs003712

• using-ega-account

  Using your EGA account The purpose of this page is to help you access and download the data you have been granted permission to view through your EGA account. To obtain an EGA account please register here. Once your account is created, you can find details on how to manage your EGA account here. EGA access policy (New account holders please read) Access to EGA services are only provided to EGA account holders. EGA accounts are created, updated and closed upon direct instruction from the relevant DAC contact, using the EGA account management tools or through EGA Helpdesk. As part of the EGA account creation process, the EGA account holder must reset their password when instructed. Password resets are checked and verified usually within 24 business hours, during which time the EGA account is inaccessible. EGA accounts are assigned on an individual basis for the exclusive use of the registered EGA account holder; log-in details must remain private and only be used by the EGA account holder. Controlled access data files are only provided, in accordance to the permissions set by the DAC, to EGA account holders. EGA controlled access data files are encrypted prior to download and must be decrypted on the EGA account holders side. EGA account holders are provided access to the EGA download streamer to download access approved datasets and files therein. The EGA download streamer represents the primary means for the EGA account holder to download access approved datasets and files therein. EGA account holders may be provided with an EGA download account for accessing approved datasets and files therein, using FTP or Aspera in response to clearly defined technical reasons, which may restrict the use of the EGA download streamer. It is the sole responsibility of the EGA account holder to ensure full compliance to all terms and conditions of the Data Access Agreement are met once data is downloaded from the EGA. Should you move institute you must contact all Data Access Committee's contacts to update your details and, if necessary, re-apply for data access. The Data Access Agreement (DAA) is a contract made between the DAC and the EGA account holder; the EGA is not responsible for enforcing the DAA. EGA reserves the right to place EGA accounts 'onhold', pending DAC approval to re-activate, should EGA account 'misuse' be suspected. Further information Introduction to the EGA Frequently Asked Questions Subscribe to the EGA mailing list

  Documentation using-ega-account

• Novel genes for Intellectual Disability identified using whole genome sequence and pathway analysis

  Intellectual Disability (ID) is one of the most common global disorders. However for ~30% of patients with ID no cause is identified, despite a clinical diagnostic odyssey that includes genome wide clinical microarray (CMA). We carefully selected 8 trios, each composed of a child with ID and brain structural defect, and both normal parents for whole genome sequencing (WGS). We conducted WGS on the trio and filtered out de novo single nucleotide variants (SNVs) and then used a pathway-based refinement to select candidates. We confirmed a de novo pathogenic SNV in ARID1B, and likely pathogenic SNVs in CACNB3, SPRY4, PHF6, SQSTM1 and UPF1 in 5 of the 8 children. All genes except ARID1B and PHF6 are previously unreported for ID. We analysed our WGS data using 4 independent algorthims for copy number and structural variation including using de novo whole genome assembly. We confirmed one likely contributory 165kb de novo CNV (missed by CMA). We conducted a validation study of over 2000 exomes for our novel candidate genes and also present a strategy to analyze the non-coding sequence space. This study provides an extensive analysis of WGS in the context of ID and yielded causative variants in >60% of cases.

  Study EGAS00001001386

• Enrichment of PTPRT and JAK2 mutations in lung cancer from African Americans and evidence for increased GI and HRD in LUSC

  The goal of this study is to compare the somatic mutation landscape between European Americans and African Americans. It includes various histological forms of lung cancer. In LUAD, we find increased prevalence of PTPRT and JAK2 mutations among African Americans. These proteins function in the same pathway and as such, this may be a new actionable target for lung cancer. We have also examined the landscape of copy number profiles in African Americans and European Americans.

  Study phs001895

• Genome-Wide Analysis of Aberrant Position and Sequence of Plasma DNA Fragment Ends in Patients With Cancer

  This study investigated fragmentation characteristics in plasma cell-free DNA and evaluated the relevance of such analysis for cancer diagnostics. Specifically, we performed whole genome sequencing (WGS) of healthy individuals and cancer patients, and evaluated genome-wide coverage and sequences surrounding fragment ends. This was a retrospective study of archived plasma samples. The WGS data are available through this submission. Detailed study design and findings were published in Budhraja et al. Science Translational Medicine 2023.

  Study phs003170

• Human Skin Cancer Atlas, Medical University of Vienna Data Access Policy

  Cancer-associated fibroblasts (CAFs) play a key role in cancer progression and treatment outcome. Here, we elucidate the yet unresolved intra-tumoral CAF variety in three skin cancer types at molecular and spatial single-cell resolution in a large cohort. We show that two out of three CAF subtypes contribute to tumor immune surveillance with distinct mechanisms. Matrix CAFs (mCAFs) ensheath tumor nests and synthesize extracellular-matrix to prevent T cell invasion. Immunomodulatory CAFs (iCAFs), which express proinflammatory and immunomodulatory factors, are only detected in high abundance in aggressive tumors. Strikingly, iCAFs but not tumor cells are (apart from immune cells) the exclusive cell type producing chemokines and, thus, play a key role in immune cell recruitment and activation. Mechanistically, we show that cancer cells transform adjacent healthy fibroblasts into cytokine-expressing iCAFs, which subsequently recruit immune cells and modulate the immune response. In conclusion, targeting CAF variants holds promise for improved efficacy of immunotherapy.

  Dac EGAC50000000154

• WES of breast cancer patients and controls

  This study assessed the variant profiles of 408 samples from 126 breast cancer patients with various survival outcomes, including paired uninvolved mammary gland samples collected at proximal distances from primary lesions. As a reference, control samples from 15 mammoplasty individuals without cancer history were studied. Whole exome sequencing was performed to identify post-zygotic and germline variants present in the studied samples. Variant annotation in known databases, interpretation, and statistical analyses followed to discern the clinical relevance of called variants.

  Study EGAS50000000539

• Uncovering Principles of Adaptive Regulation in Cancer Resistance Through Deep Evolutionary Profiling

  A comprehensive understanding of the emergence of therapy resistance in cancer requires new approaches capable of generating and characterizing drug resistant cell lines at scale. Here, we present the EVolution Of Lineages in Vitro (EVOLV) platform, a high-throughput approach for generating diverse libraries of viable, drug-resistant cell lines from a common progenitor. EVOLV enables deeper insights into the genomics of drug resistance as well as into the complex interplay among genomic, transcriptomic, and functional layers during cancer evolution.

  Study phs003851

• Evaluation of whole genome sequencing utility in identifying driver alterations in cancer genome

  This study aimed to assess the effectiveness of whole genome sequencing (WGS) compared to whole exome sequencing (WES) in identifying driver alterations in cancer genomes. Out of 177 cases with no driver alterations detected by WES, WGS identified driver alterations in 68.4% and likely driver alterations in 22.6% of cases. The most common alterations found were oncogene amplifications, tumor suppressor gene deletions, and small variants outside coding regions. WGS proved valuable in uncovering genomic changes associated with cancer development.

  Study JGAS000715

• Metabolomic and transcriptomic analyses identify metabolic alterations and immune suppression in ovarian cancer

  The objective of this study is to identify metabolic alterations and related phenotypes specific to ovarian cancer by performing metabolomic analysis of plasma and tissue samples. In addition, transcriptomic analysis is conducted to investigate the relationship between metabolic status and immune-related gene expression. By integrating metabolomic and transcriptomic data, this study aims to clarify how metabolic reprogramming contributes to tumor progression and immune suppression, particularly the reduction of natural killer (NK) cell activity, in ovarian cancer.

  Study JGAS000831

• A Comparative Analysis of Algorithms for Somatic SNV Detection in Cancer

  Four recently published algorithms for the detection of somatic SNV sites in matched cancer-normal sequencing datasets are VarScan, SomaticSniper, JointSNVMix and Strelka. In this analysis, we apply these four SNV calling algorithms to cancer- normal Illumina exome sequencing of a chronic myeloid leukaemia (CML) patient. The candidate SNV sites returned by each algorithm are filtered to remove likely false positives, then characterised and compared to investigate the strengths and weaknesses of each SNV calling algorithm.

  Study EGAS00001000927

• The T cell receptor repertoire of tumor infiltrating T cells is predictive and prognostic for cancer survival

  Tumor infiltration by T cells is paramount for effective anti-cancer immune responses. We hypothesized that the T cell receptor (TCR) repertoire of tumor infiltrating T lymphocytes (TIL/Tc) could determine disease course at different stages in cancer progression. We show that the diversity of the TIL/Tc TCR at baseline is prognostic in various cancers, whereas in metastatic melanoma TIL/Tc TCR clonality at baseline is predictive for activity and efficacy of PD1 blockade immunotherapy.

  Study EGAS00001005201

• Defining structural variation associated with breast cancer susceptibility by long-read genome sequencing

  Germline structural variants (SVs) are challenging to identify by conventional genetic testing assays. Long-read sequencing has improved the global characterization of SVs, but its sensitivity at genetic loci associated with high- and moderate-penetrance cancer susceptibility has not been reported. This study used long-read genome sequencing performed on the Oxford Nanopore Technologies' PromethION to resolve variants underlying breast cancer susceptibility in sixteen individuals with pathogenic germline SVs in BRCA1, BRCA2, CHEK2 or PALB2.

  Study EGAS00001005872

• Whole Genome Sequencing Data of High Grade Serous Ovarian Cancer

  Longitudinal whole genome sequencing data to study chemoresponse in ovarian cancer. These samples belong to an ongoing sample collection and the data already includes hundreds of samples from over 200 patients. Samples are from primary and metastatic tissues and ascites. All patients have been treated with platinum-taxane based chemotherapy and majority of them are diagnosed with high-grade serous ovarian cancer.

  Study EGAS00001006775

• 20 Matched Pair Breast Cancer Genomes

  20 Matched Pair Breast Cancer Genomes

  Dataset EGAD00001000082

• bulkRNAseq of ovarian cancer cell lines

  bulkRNAseq of four ovarian cancer cell lines (PA-1, A2780, A2780/CP20, TOV-21G)

  Dataset EGAD50000002059

• Cancer-associated genome-wide hypomethylation and copy number aberrations

  Noninvasive detection of cancer-associated genome-wide hypomethylation and copy number aberrations by plasma DNA bisulfite sequencing

  Dataset EGAD00001001093

• Amplicon sequencing data from organoids of colorectal cancer patients.

  The dataset includes 13 bam files. Each bam file is a different colorectal cancer patient organoid.

  Dataset EGAD00001004313

• KiCS cancer panel academic only data

  This data set contains KiCS cancer panel data for academic and for-profit use.

  Dataset EGAD00001009733

• EORTC RP1335 SPECTA Lung cancer data - Oncomine

  EORTC RP1335 SPECTA Lung cancer data - Oncomine dataset

  Dataset EGAD00001006594

• Neoantigen-Targeted CD8+ T-Cell Responses 1 With PD-1 Blockade Therapy

  Background: The primary target of T-cell responses induced against cancer cells are peptides derived from non-synonymous mutations presented by HLA (neoantigens). However, the large diversity of HLA alleles and restricted availability of clinical samples have limited the study of the specificity and the evolution over time of the neoantigen-specific T cell responses induced after treatment with immune checkpoint blockade (ICB) immunotherapy. Methods: We applied a newly developed neoepitope-specific T cell isolation technology to perform a longitudinal landscape analysis of the neoepitope-specific T cells in peripheral blood and tumor from 11 patients with metastatic melanoma; 7 with response and 4 with no response to ICB. Briefly, first using computational prediction, the putative neoantigens in each patient were ranked based on affinity for the patient's HLA and expression levels. Then hundreds of barcoded capture reagents consisting of the patient HLA class I subtypes loaded with the corresponding predicted neoantigen were made and used to isolate neoepitope-specific T cells. Once isolated, the TCRs and the barcodes were sequenced. Finally, the tumor reactivity of the isolated neoepitope-specific TCRs (neoTCRs) was assessed upon co-culture of autologous melanoma cell lines from each patient with primary human T cells expressing the neoTCRs generated using a CRISPR-based non-viral gene editing to replace the endogenous TCRs. Results: The tumor mutation burden ranged between 3507 and 177 for patients with response to therapy and 977 to 31 for patients without response to therapy. We screened a median of 172 predicted neoantigen-HLA per patient across their 6 HLA molecules and isolated neoTCRs in all 11 patients. The number of mutations targeted ranged between 13 and 1. We assessed the neoTCR-tumor reactivity in samples from 3 patients with response and 3 patients without response. 39 of the 62 neoTCRs demonstrated specific recognition and cytotoxicity to patient-matched melanoma cell lines. Multiple T cell clonotypes recognized a limited number of mutations in 7 patients with response (median of 41 different neoTCR clonotypes per patient), and the T cell specificities were recurrently detected in the blood and the tumor over time. Samples from 4 patients without response to therapy also demonstrated neoepitope-specific T cell responses in blood and tumor to a similarly restricted number of mutations, but lacked TCR polyclonality (median 6.5 neoTCR clonotypes per patient) and were not recurrently detected in sequential samples. Conclusion: Effective ICB therapy is associated with polyclonal neoepitope-specific T-cell responses in the tumor and blood that recognize a limited number of immunodominant mutations and are recurrently detected over time.

  Study phs003153

• Pan Prostate Cancer Group data

  The Pan Prostate Cancer Group intends to provide breakthrough advances from the analysis of a very large series of Whole Genome DNA data, contributed by many of the leading scientists and clinicians working in prostate cancer genomics generating Whole Genome DNA Sequence (WGS) data from prostate cancer patients. The accumulated data, collected and compared in a common format including common storage, re-analysis through a single pipeline, and investigation to achieve a variety of scientific goals, are presented in this series. This project will provide a global framework for the future analysis of even larger series of genomes as costs of DNA sequencing, storage, and sequence analysis decrease. In addition to these WGS data from different clinical categories, ethnicities, levels of aggressiveness, and disease managed by different treatments with information linked to long-term clinical follow up, we intend to add additional layers of data, including transcriptome and methylation data. The current data series focuses primarily on the analysis of WGS data. For further information, please refer to https://panprostate.org/, and The Pan Prostate Cancer Group Data Sharing Policy, EGAP50000000784.

  Study EGAS00001002876

• RNA stability controlled by m6A methylation contributes to X-to-autosome dosage compensation in mammals

  In mammals, X-chromosomal genes are expressed from a single copy since males (XY) possess a single X chromosome, while females (XX) undergo X inactivation. To compensate for this reduction in dosage compared to two active copies of autosomes, it has been proposed that genes from the active X chromosome exhibit dosage compensation. However, the existence and mechanism of X-to-autosome dosage compensation are still under debate. Here, we show that X-chromosomal transcripts are reduced in m6A modifications and more stable compared to their autosomal counterparts. Acute depletion of m6A selectively stabilises autosomal transcripts, resulting in perturbed dosage compensation in mouse embryonic stem cells. We propose that higher stability of X-chromosomal transcripts is directed by lower levels of m6A, indicating that mammalian dosage compensation is partly regulated by epitranscriptomic RNA modifications.

  Study EGAS00001007112

• ICGC prostate cancer whole genome mate-pair sequencing

  ICGC prostate cancer whole genome mate-pair sequencing

  Dataset EGAD00001000303

• SNParray copy number dataset

  4 oesophageal cancer derived organoid lines and 2 ovarian cancer derived organoid lines

  Dataset EGAD00010002002

• Amsterdam UMC Head and Neck Cancer Biology and Immunology

  This data access committee oversees data and assesses requests for the Head and Neck Cancer Biology and Immunology lab of Amsterdam UMC, location VUmc.

  Dac EGAC50000000350

• SPECTA Lung cancer DNA FASTQ files

  SPECTA Lung cancer DNA FASTQ files (Illumina TST170 targeted analysis)

  Dataset EGAD00001006223

• Genome-wide cell-free DNA mutational integration enables ultra-sensitive cancer monitoring

  Genome-wide cell-free DNA mutational integration enables ultra-sensitive cancer monitoring

  Dataset EGAD00001006237

• SNP data for Breast cancer PRS

  SNP data for 313 loci required for calculation of the Breast cancer PRS

  Dataset EGAD00001008144

• Ulcerative colitis study - WES data

  Whole Exome Sequencing data of Single crypts, bulk crypt samples, and colitis-associated cancer.

  Study EGAS00001003801

• Global Endometrial DNA Methylation Analysis Reveals Insights into mQTL Regulation and Associated Endometriosis Disease Risk and Endometrial Function

  Endometriosis is a common gynecological disorder affecting 11% of reproductive aged women and is a leading cause of pain and infertility. We investigated global DNA methylation (DNAm) profiles in endometrium associated with endometriosis, menstruation, and genetic variation. Endometrial samples were collected from 984 patients with confirmed endometriosis (n=637) and women without endometriosis (n=347). Patients were recruited through the University of California San Francisco, USA, University of Melbourne, Australia, Endometriosis CaRe Centre in Oxford, UK, and EXPPECT Centre, The University of Edinburgh, UK, using the World Endometriosis Research Foundation Endometriosis Phenome and Biobanking Harmonization Project (WERF EPHect) standardized protocols for tissue collection and processing, and participant characteristics and clinical annotation. DNA was extracted from samples and was use to generate DNAm data using the Illumina Infinium MethylationEPIC Beadchip and genotype data using the Axiom Precision Medicine Research array. Estimates from this study suggest that 15.4% of the variation in endometriosis is captured by DNAm. DNAm analysis identified significant differences in DNAm profiles and DNAm networks, associated with endometriosis, endometriosis sub-phenotypes, and menstrual cycle phases. Integration of DNAm and genetic data in a DNAm quantitative trait locus (mQTL) analysis identified 118,185 independent cis-mQTLs including 51 associated with risk of endometriosis highlighting target genes contributing to disease risk. This study identified novel factors affecting epigenetic regulation in endometrium associated with endometriosis risk and disease heterogeneity and provides an important data resource for reproductive medicine. Genotype data generated as part of this study are available on dbGaP and methylation data are available on GEO.

  Study phs003307

• EGAD00010000632

  WTCCC2 People of the British Isles (POBI) samples using Illumina 1.2M array

  Dataset EGAD00010000632

• Oncotrack_450K_metastatic

  Oncotrack metastatic samples using 450K. The shared AF analysis files oncotrackDNAmAnalysis.R and oncotrackDNAmBetaScores.txt which were applied for both Oncotrack_450K_tumor (EGAD00010001162) and Oncotrack_450K_metastatic (EGAD00010001161) datasets are included on Oncotrack_450K_tumor (EGAD00010001162) dataset.

  Dataset EGAD00010001161

• CCA methylation data (12 CCA, 7 normal)

  Raw idat files for DNA methylation profiling for 12 CCAs and 7 normal bile duct tissues. DNA methylation profiling was performed using Infinium MethylationEPIC v2.0 Kit.

  Dataset EGAD00010002613

• RISE-UP Cohort

  The RISE-UP study contains raw metagenomic sequencing data of Crohn's disease patients. Paired-end sequencing was performed using the Illumina HiSeq 2000 platform.

  Dataset EGAD50000001436

• PBAT sequencing of human embryonic stem cells

  To assess the DNA methylation landscape of naïve human embryonic stem cells derived from ERKi or control blastocysts using PXGL or UXGL media.

  Dataset EGAD50000001475

• HV31 - MGI standard short-read sequencing

  MGI standard short-read sequencing data for individual HV31 generated using DNA from peripheral blood mononuclear cells, to a sequencing depth of ~57×.

  Dataset EGAD00001007044

• HV31 - MGI CoolMPS short-read sequencing

  MGI CoolMPS short-read sequencing data for individual HV31 generated using DNA from peripheral blood mononuclear cells, to a sequencing depth of ~57×.

  Dataset EGAD00001007048

• Comparison of HCC cell lines and primary HCCs

  Whole genome sequencing (30X) using Hiseq X TEN on 4 HCC cell lines, primary HCCs and early-passage PDCs

  Dataset EGAD00001001995

• Amplicon–Based Metagenomic Analysis.

  Amplicon-based fungal metagenomic sequencing for the identification of fungal species in brain tissue from Alzheimer's disease. The study consists in 14 samples, sequenced using Illumina's paired-end technology.

  Dataset EGAD00001003196

• Exome sequencing of FFPE sample

  Bam file from exome sequencing of FFPE sample from Ly3 using SeqCap EZ Human Exome Library (Roche Nimblegen, Inc., WI, USA) and Illumina HiSeq2000 sequencer.

  Dataset EGAD00001004782

• Bulk transcriptomic analyses of monocyte-derived dendritic cells treated with CES1i

  The data published here contains bulk RNA-sequencing (RNAseq) data as obtainedfrom monocyte-derived dendritic cells in treated with/without LPS and with/without CESi (WWL113). Sequencing was performed in a paired-ended fashion on the NovaSeq6000.

  Dataset EGAD50000000344

• Small RNA sequencing of human oocytes and early embryos

  This dataset contains single-end fastq files for human oocytes (n=12), zygotes (n=5), and early embryos (n=10) sequenced with Illumina NextSeq500. The sequencing libraries were prepared from single oocytes, zygotes, and embryos in two batches.

  Dataset EGAD50000000227

• Single-nucleus RNA-sequencing of normal adrenal cortex and adrenocortical tumors

  This study reports a single-nucleus transcriptome atlas of steroid, stromal and immune cells in 38 human normal adrenals and adrenocortical tumors.

  Study EGAS50000000585

• Integrated Multiomics Uncovers Distinct Macrophage Alterations in Human Metabolic dysfunction-Associated Steatohepatitis Progression

  We report single-nuclei RNA sequencing data (n=18) from human livers in metabolic dysfunction-associated steatotic liver disease (MASLD) patients. there are 5 MASH, 4 MASL, 5 control obese and 4 control lean samples.

  Dataset EGAD50000001129

• Kidney tumour_DNA (2018-09-19)

  This is a bulk DNA and RNA sequencing study of human renal tumours . This dataset contains all the data available for this study on 2018-09-19.

  Dataset EGAD00001004346

• Data set for pan.met study

  The dataset referenced by EGA Study ID EGAS00001004208 includes 20 human exome sequencing data and 11 human RNA sequencing data from tumor or normal tissues. Each sequencing data includes two pair-end short read files in fastq format.

  Dataset EGAD00001005957

• Sequencing data for oesophageal / related samples - Foley, Shorthouse et al (RNA)

  Data supporting: "SMAD4 and KCNQ3 Alterations are Associated with Lymph Node Metastases in Oesophageal Adenocarcinoma" RNAseq (FASTQ files) 6 samples

  Dataset EGAD00001011065