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• Whole-genome sequencing of high-grade serous ovarian cancer (HGSC) tumours and matched normals from long-term survivors.

  Whole-genome sequencing of high-grade serous ovarian cancer (HGSC) tumours and matched normals from long-term survivors performed as part of the Multidisciplinary Ovarian Cancer Outcomes Group (MOCOG) study. The dataset includes fastq files from 58 HGSC tumours (53 primary tumours and 5 recurrent tumours) and 53 matched normals from 53 long-term survivor patients. Sequence libraries were generated from tumour and matched normal genomic DNA using the KAPA HyperPrep PCR-free library preparation kit (Roche) according to manufacturer’s instructions. Sequencing was carried out by the Kinghorn Centre for Clinical Genomics Sequencing Laboratory (Sydney, Australia) on the HiSeq X Ten System (Illumina) to a minimum base coverage of 30-fold for normal DNA and 60-fold for tumour DNA samples.

  Dataset EGAD00001009398

• Using genetics to identify cell types and mechanisms underlying susceptibility to primary sclerosing cholangitis

  Primary sclerosing cholangitis (PSC) is a T-cell mediated, chronic inflammatory condition of the biliary tree that is strongly associated with inflammatory bowel disease. Genome-wide association studies have identified 22 non-HLA genetic risk variants associated PSC. Identifying the genes impacted by these variants has proven difficult as the majority lie in non-coding regions of the genome. Knowledge of the genes and biological pathways these non-coding variants are perturbing is vital to understanding the disease biology. One means of assessing the impact of non-coding variants within disease associated loci upon genes is via colocalisation with eQTL. Many eQTL are cell-type specific, requiring the analysis of disease relevant cell types to detect colocalisation. We have collected PSC-relevant T-cell-subtypes from the peripheral blood of PSC patients via fluorescence activated cell sorting in preparation for RNA sequencing and mapping of eQTL. Samples were collected at the Norfolk and Norwich University Hopital, for which local ethical approval has been granted. Lysed cell samples will be transferred to WTSI and DNA/RNA will be extracted from lysed cell samples by T143 before genotyping (DNA) and custom library preparation and sequencing (RNA). This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001011815

• Insights into non-crossover recombination from long-read sperm sequencing

  Meiotic recombination is a fundamental process that generates genetic diversity by creating new combinations of existing alleles. While crossovers in humans are well characterized, the more frequent non-crossovers that lead to gene conversion remain challenging to study. Here we show that single high-fidelity long sequencing reads from sperm can capture both crossovers and non-crossovers, allowing effectively arbitrary sample sizes for analysis from one male. Using fifteen sperm samples from thirteen donors we demonstrate variation between donors for the different types of recombination, even when they share the same PRDM9 genotype. Non-crossovers are less consistent with the genetic map and exhibit reduced association with meiotic double-strand break (DSB) sites identified by DMC1 binding. Where non-crossover gene conversions are close to PRDM9 sites they tend to occur upstream. We further provide evidence for two distinct non-crossover processes. One gives rise to the vast majority of non-crossovers with mean conversion tract length under 50bp, while ~1% of non-crossovers have much longer mean tract length. Applying the same analysis pipeline to public data from twelve blood samples, we also see non-crossover gene conversions, but very few crossover events. These non-meiotic events, not correlated with the genetic map, increase with age, consistent with double-strand break repair throughout life. We suggest that many of the non-crossover events seen in sperm also derive from non-meiotic repair prior to spermatogenesis.

  Dataset EGAD00001015736

• 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

• NKI-AvL CRC-OVC scTCR RNA-seq

  The dataset “NKI-AvL CRC-OVC scTCR RNA-seq" includes 368 BAM files from paired-end RNA sequencing on Illumina MiSeq for 2 colorectal cancer and 2 ovarian cancer patients.

  Dataset EGAD00001004342

• Exome sequencing of tumor samples

  We utilized exome sequencing for DNA obtained from saliva (germline DNA) and the four spatially separated tumor foci and 3 corresponding lymph node metastases

  Dataset EGAD00001000762

• High grade serous ovarian carcinoma sample

  Multi-region whole genome sequencing of an high grade serous ovarian carcinoma sample for characterization of genomic intra-tumoural heterogeneity.

  Dataset EGAD00001000978

• NeurOmics_HD_Biomarker-1_V1

  This data set includes RNAseq data from 136 samples from the TRACK-HD cohort including premanifest, manifest and control subjects. Data can only be used for Huntington's disease related research.

  Dataset EGAD00001002699

• Rare coding variants in lupus risk genes

  Set of 133 bam files from patients affected with Lupus. BAM alignments for exonic variants present in 76 Lupus-related genes. VCF file describing the variants.

  Dataset EGAD00001004859

• Low

  Non-deduplicated bam files comprising Illumina HiSeq2500 SE100 low coverage whole genome data for 30 pre-treatment (BL) cfDNA samples and 20 matched post-treatment (PD) cfDNA samples.

  Dataset EGAD00001005070

• Whole genome sequencing in myasthenia gravis

  This dataset contains whole genome sequencing data on 25 individuals with myasthenia gravis. The data was generated using Illumina sequencing technology and is presented as BAM files for each sample.

  Dataset EGAD00001005262

• ChIP-Seq of human stimulated and cultured CD4+ Treg cells

  This dataset includes whole genome sequence data for ChIPmentation assays (18 H3K4me3, 20 H3K27ac and 3 input samples) of human stimulated and cultured CD4+ Treg cells.

  Dataset EGAD00001005816

• RNA-Seq data of de novo assembly individual EGYPT

  This is the blood RNA-Seq read data used for expression analysis such as haplotypic expression (mapped against GRCh38).

  Dataset EGAD00001006036

• 10X Genomics WGS data of de novo assembly individual EGYPT

  10x Genomics linked read data used in variant phasing and de novo assembly scaffolding for the EGYPT individual (mapped against GRCh38).

  Dataset EGAD00001006035

• NICHE - RNA-seq of MMR proficient and MMR deficient early stage colon cancers

  The dataset includes 77 FASTQ files from single-end total RNA sequencing on Illumina HiSeq2500 for 39 patients.

  Dataset EGAD00001006042

• 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

• Genome-wide data and mtDNA Resande and Swedes

  This dataset includes genome-wide autosomal array data and whole mtDNA sequences for 12 Resande and 17 Swedish individuals.

  Dataset EGAD00001008697

• Mixtures of 5-9 individuals

  Deconvoluted files of the 5-9 individuals of in silico datasets (combination of biological mixture sequencing and publicly available data). The dataset includes the phenotypes used for clustering.

  Dataset EGAD00001008725

• Beta values of methylation data of the CUP/reference/validation cohort (H021)

  Beta values of methylation data of the CUP/reference/validation cohort (H021) used for the validation cohort described in the publication

  Dataset EGAD00001008669

• 2_cortical-neurons_HD_vs_Ctrl_DMSO_Branaplam

  n=3 Ctrl and n=3 HD iPSC lines differentiated into cortical neurons were treated with DMSO or 10nM Branaplam for 72h and RNA-seq was performed.

  Dataset EGAD00001008808

• liCHi-C samples of different input cell numbers.

  Libraries of liCHi-C for different input cell numbers (50k, 100k, 250k, 500k and 1M cells) with 2 biological replicates each. Fastq file format

  Dataset EGAD00001008827

• Dataset for RNA PCNSL

  RNA sequencing of 19 samples from PCNSL tumors. Sequencing was performed on a HiSeq X Ten using Illumina TruSeq Stranded mRNA Kit. Sequencing was always paired.

  Dataset EGAD00001011119

• Effects of busulfan, fludarabine and clofarabine treatment on human small intestinal organoids.

  Instestinal organoids treated with either busulfan, fludarabine or clofarabine for 24h

  Dataset EGAD00001011336

• Genome-Wide Association Study of Hypertriglyceridemia in Mexicans

  Coronary artery disease (CAD) is the number one cause of death and mortality world-wide. High levels of serum triglycerides (TGs) and low levels of serum high-density lipoprotein cholesterol (HDL-C) are major risk factors for CAD. Previous epidemiological studies have shown that these two lipid disturbances are highly common dyslipidemias in Mexicans. However, the genetic factors underlying high serum TGs and low HDL-C are underinvestigated and poorly identified in Mexicans. As the Mexican-American and the genetically related Latin-American populations represent the fastest growing minority in the United States, elucidation of the unknown genetic factors influencing the increased susceptibility of Mexicans to these common dyslipidemias is of great relevance to these U.S. minorities and the American healthcare system. This study is a research collaboration between investigators at the University of California, Los Angeles (UCLA) and Instituto Nacional de Ciencias Médicas y Nutrición (INCMN), Mexico City, to perform a two-stage genome-wide association study (GWAS) for hypertriglyceridemia and low high-density lipoprotein cholesterol (HDL-C) in Mexicans (Weissglas-Volkov et al. 2013, PMID: 23505323). This study was funded by an RO1 grant from NIH/NHLBI (PI Paivi Pajukanta; PI of the subaward Teresa Tusie-Luna). In stage 1 of the GWAS, we tested all GWAS SNPs from the Illumina Infinium Human610-Quad platform that passed quality control for association in ~2,200 hypertriglyceridemia cases and controls. In stage 2, we genotyped the ~1,200 positive signals of stage 1 in additional ~2,200 hypertriglyceridemia cases and controls, and performed a combined analysis of the two stages to identify genome-wide significant variants. The subjects were recruited at the INCMN. The DNA isolation and clinical laboratory measurements of the case-control study samples were performed at INCMN using standardized procedures. Genotyping and statistical analyses of the data were performed at UCLA. A summary of this GWAS can be found in Weissglas-Volkov et al. 2013 Journal of Medical Genetics, PMID: 23505323. Briefly, using the two-stage GWAS design, we identified a novel Mexican-specific genome-wide significant locus for serum TG levels close to the Niemann-Pick type C1 protein (NPC1) gene (Weissglas-Volkov et al. 2013, PMID: 23505323). Of the European lipid GWAS loci, three TG loci (APOA5, GCKR, and LPL) and four HDL-C loci (ABCA1, CETP, LIPC and LOC55908) resulted in genome-wide significant signals in Mexicans. Furthermore, our cross-ethnic mapping narrowed three European TG GWAS loci, APOA5, MLXIPL, and CILP2 that exhibited long range LD and a large number of candidate SNPs in the European GWAS scan. In the apolipoprotein A1C3A4A5 gene cluster region, the cross-ethnic fine mapping and LD comparisons reduced the number of candidate variants to one SNP, rs964184. We also found that although 52% of the associations from European lipid GWAS meta-analysis could be generalized to Mexicans, in 82% of the European GWAS loci, a different variant other than the European lead SNP provided the statistically strongest evidence of association in the Mexican scan (Weissglas-Volkov et al. 2013, PMID: 23505323). Taken together, our Mexican GWAS for lipids identified a novel Mexican-specific locus for high serum TGs; restricted three European GWAS loci; and investigated which European lipid GWAS variants extend to the Mexican population (Weissglas-Volkov et al. 2013, PMID: 23505323). This NHLBI sponsored RO1 project aimed to identify genetic variants contributing to serum lipid levels in Mexicans. In addition to de-identified genome wide genotypic data, a selected list of de-identified phenotypic data related to hypertriglyceridemia and related metabolic traits are also available in dbGaP.

  Study phs000618

• PAK4 inhibition improves PD-1 blockade immunotherapy

  Introduction with rationale and aims for study Immune checkpoint blockade therapies have significantly altered the current landscape of cancer treatment. However, this immunotherapy still fails more often than it succeeds. There are now evidences that the lack of tumour infiltration by immune cells is the main mechanism of primary resistance to PD‐1 blockade therapies for cancer. It has been postulated that cancer cell‐intrinsic mechanisms may actively exclude T cells from tumours, suggesting that the finding of actionable molecules that could be inhibited to increase T cell infiltration may synergize with checkpoint inhibitor immunotherapy. With the idea of finding potential drivers of immune exclusion, we performed RNA sequencing analysis of biopsies from melanoma patients and compared the transcriptomic differences of samples that where infiltrated with those that did not have immune infiltration. Methods RNAseq analysis of gene expressions on biopsies from melanoma patients treated with checkpoint blockade were analysed. We focused on the variable of "infiltration: yes or no,", e.g. tumors that were well infiltrated by immune cells with those that kept immune cells out. Sequencing revealed a list of genes whose expression differed between the infiltrated and noninfiltrated tumors. The kinase PAK4 stood out as a good candidate for inhibition treatment in the future as it was consistently enriched in the samples without immune infiltration. To test whether immunotherapy would work better if we deleted PAK4, we first knocked out PAK4, using CRISPR‐Cas9, in the ‐resistant melanoma cell line, B16. Then they injected the melanoma cells into mice and observed that PAK4 KO tumours now responded to PD‐1 blockade. In order to elucidate whether pharmacological inhibition of PAK4 could recapitulate the results observed in the B16 PAK4 KO tumours, we obtained the PAK4 inhibitor, KPT-9274, from Karyopharm Therapeutics. Indeed, inhibiting PAK4 in combination with anti‐PD‐1 immunotherapy significantly slowed the growth of the B16 melanomas more than either drug alone. Results and Conclusions Transcriptomic analysis of melanoma tumors that were well infiltrated by immune cells with those that kept immune cells out revealed a list of genes whose expression differed between the infiltrated and non-infiltrated tumours. The result suggests that p21 activated kinase 4 (PAK4) is enriched in non-responding tumour biopsies with low T cell and dendritic cell infiltration. In addition, PAK4 decreased WNT activity, a signalling pathway that has previously been involved in immune exclusion. In mouse models, genetic deletion of PAK4 increased T cell infiltration and reversed resistance to PD‐1 blockade in a CD8 T cell-dependent manner. Furthermore, combination of with the PAK4 inhibitor, KPT-9274, improved anti‐tumour responses compared to anti‐PD‐1 alone. Therefore, high PAK4 expression is correlated with low T cell and dendritic cell infiltration and lack of response to PD‐1 blockade, which could be reversed with PAK4 inhibition. The data establish a rationale for targeting this kinase with inhibitors in combination with immune checkpoint inhibitors for patients. Future work and data that we can anticipate for this study Oncogenic signalling pathways and specially the WNT signalling pathway, have been associated with lack of immune infiltration and resistance to PD‐1 blockade therapies. Here, we show that PAK4 overcome resistance to PD‐1 blockade while significantly decreases WNT signalling activity. Therefore, it constitutes the first potential druggable target that is able to reverse oncogenic driven immune cell exclusion. However, the fully mechanism whereby PAK4 sensitizes tumours to immunotherapy remains to be fully elucidated. It is necessary to address whether PAK4 inhibition overcomes resistance through WNT signalling inhibition or if other signalling pathways are involved in the observed phenotype.

  Study phs001919