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• 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

• Transcriptomic characterization of the histopathological growth patterns in breast cancer liver metastases

  20 fastq files of RNA-sequencing of the 2 main histopathological grow patterns observed in liver metastases.

  Dataset EGAD50000000331

• Angiosarcoma follow up study

  A bespoke targeted pulldown experiment will be performed on patients with Angiosarcoma. the resulting products will be sequenced to determine the prevalence of previously found mutations in these patients.

  Dataset EGAD00001000620

• 30X WGS sequencing of 100 individuals from the general Greek population

  This project entailed generation of high depth WGS (30x) of 100 individuals from the general Greek population.

  Dataset EGAD00001001440

• bam files Targeted BS

  Data from the paper Context-specific Effects of TGFβ/SMAD3 in Cancer Are Modulated by the Epigenome. Tufegdzic et al, Cell Reports 2015

  Dataset EGAD00001001667

• BAM Files MBD-SEQ

  Data from the paper Context-specific Effects of TGFβ/SMAD3 in Cancer Are Modulated by the Epigenome. Tufegdzic et al, Cell Reports 2015

  Dataset EGAD00001001668

• Characterising the evolutionary dynamics of cancer proliferation in single-cell clones with SPRINTER

  Characterising the evolutionary dynamics of cancer proliferation in single-cell clones with SPRINTER

  Dataset EGAD00001015411

• Spatial heterogeneity, stromal phenotypes, and therapeutic vulnerabilities in colorectal cancer peritoneal metastasis

  Peritoneal metastases (PM) in colorectal cancer (CRC) portend a poor prognosis. We sought to elucidate molecular features differentiating primary tumors (PTs) from PMs and actionable targets facilitating transcoelomic dissemination and progression. We performed multi-omic profiling of 217 samples from 136 patients, including 56 primary tumor (PT) and 120 PMs comprising 25 matched PT-PM pairs. Whole exome, and bulk RNA-seq analysis was conducted to identify underlying genomic aberrations and transcriptomic differences between primary and peritoneal lesions.

  Study EGAS50000000813

• Metastatic_Breast_Cancer_Validation

  Validation of point mutations and small insertions and deletions in primary and associated metastatic breast cancer samples with matched normal tissues.

  Study EGAS00001001968

• Molecular subsets in renal cancer determine outcome to checkpoint and angiogenesis blockade

  We conducted integrated multi-omics evaluation of 823 tumors from advanced renal cell carcinoma (RCC) patients and identified molecular subsets associated with differential clinical outcomes to angiogenesis blockade alone or with a checkpoint inhibitor. Unsupervised transcriptomic analysis revealed six molecular subsets with distinct angiogenesis, immune, cell cycle, metabolism, and stromal programs. While sunitinib was effective in subsets with high angiogenesis, atezolizumab+bevacizumab improved clinical benefit in tumors with high T-effector and/or cell cycle transcription. Somatic mutations in PBRM1 and KDM5C associated with high angiogenesis and AMPK/Fatty acid oxidation gene expression, while CDKN2A/B and TP53 alterations were more prevalent in tumors with increased cell cycle and anabolic metabolism. Sarcomatoid tumors exhibited low prevalence of PBRM1 mutations and angiogenesis markers, frequent CDKN2A/B, BAP1 and TP53 alterations, and increased PD-L1 expression. These findings can be applied to molecularly stratify advanced RCC patients, explain improved outcomes of sarcomatoid tumors to checkpoint blockade, and develop personalized therapies.

  Study EGAS00001004353

• Transcriptional profiling and clonality analysis of peripheral blood B cells and small intestinal plasma cells in celiac disease

  Single-cell RNA-seq and BCR sequencing and/or inference of sorted IgA+ peripheral blood B-lineage cells and small intestinal plasma cells of untreated celiac disease patients.

  Study EGAS50000000229

• Genetic and epigenetic analysis of individuals with porokeratosis

  We performed genome sequencing���including whole-exome sequencing (WES), whole-genome sequencing (WGS), long-read WGS, and amplicon-seq���along with SNP array, methylation array, and RNA-seq on samples of epidermis (both lesion and non-lesion), peripheral blood, and/or cultured keratinocytes from individuals with porokeratosis.

  Study JGAS000684

• Neuron-specifc methylome analysis of Alzheimer's disease brain

  Neuron-specific methylome analysis of Alzheimer's disease brain to detect epigenetic changes related to the pathomechanism.

  Study JGAS000125

• 30X_WGS_sequencing_of_100_individuals_from_the_general_Greek_population

  This project entailed generation of high depth WGS (30x) of 100 individuals from the general Greek population.

  Study EGAS00001000988

• WES bam files associated with HNSCC patients in the LIONESS study

  This dataset contains 85 WES bam/bai files of HNSCC cancer patients as part of with the LIONESS study

  Dataset EGAD50000001487

• Angiosarcoma follow-up 2 validation study

  A bespoke targeted pulldown experiment will be performed on patients with Angiosarcoma. the resulting products will be sequenced to determine the prevalence of previously found mutations in these patients.

  Dataset EGAD00001000679

• WGBS data set used in the study, 96 samples

  WGBS data set used in the study, 96 samples

  Dataset EGAD00001007968

• Live slow-frozen human tumor tissues scRNA

  Bam files of 17 samples from 11 different patients. The scRNAseq data were obtained using the 10X 3' Gene Expression kit.

  Dataset EGAD00001009284

• WXS and RNA-seq raw sequence data for TG project

  WXS sequence data from 112 samples, RNA-seq sequence data from 117 samples, all sequence data are raw sequence data in fastq format, sequenced by Illumina platform.

  Dataset EGAD00001007989

• single cell data from HPV-positive head and neck cancer patients receiving induction CTLA-4 and PD-1 immune checkpoint blockade

  Baseline and on-treatment tumor samples from human papillomavirus-positive oropharynx cancer patients receiving anti-CTLA-4 and anti-PD-1 immune checkpoint blockade were analyzed by single-cell RNA and TCR sequencing.

  Study EGAS50000000335

• Extraembryonic tissue and cytotrophoblast epigenome mapping

  Maps of H3K27ac from normal 2nd- and 3rd-trimester cytotrophoblasts, preterm severe preeclampsia cytotrophoblasts, and 2nd-trimester amnion. Maps of H3K27me3, H3K27me3, H3K36me3, and H3K4me1 from 2nd- and 3rd-trimester cytotrophoblast. Maps of H3K9me3 from 2nd- and 3rd-trimester cytotrophoblast, smooth chorion, and basal plate. RNA-seq from 2nd- and 3rd-trimester cytotrophoblasts.

  Dataset EGAD00001006066

• Dataset for colorectal_cancer-RNA

  Rare cancer sequencing data of 97 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008855

• Solve-RD_EuroNMD_cohort-1_DF1+2_V1

  Solve-RD data submitted to the ERN-EuroNMD cohort for re-analysis (Data freeze 1+2) v1

  Dataset EGAD00001009768

• FOCUS Trial

  We studied patients with advanced colorectal cancer, starting treatment with non-curative intent. 2135 unpretreated patients were randomly assigned to three treatment strategies in the ratio 1:1:1. Strategy A (control group) was single-agent fl uorouracil (given with levofolinate over 48 h every 2 weeks) until failure, then single-agent irinotecan. Strategy B was fl uorouracil until failure, then combination chemotherapy. Strategy C was combination chemotherapy from the outset.

  Study EGAS50000000725

• glioblastoma and glioblastoma stem cells (GSCs), RNA-seq and WGS

  Characterization of glioblastoma tumors and glioblastoma stem cells (GSCs) lines via RNA-seq and/or WGS profiling.

  Study EGAS00001004395

• Defective homologous recombination in HCC

  Backgrounds and Aims: We performed an in-depth examination of pathogenic germline (PGVs) and somatic variants in DNA damage response (DDR) genes in hepatocellular carcinoma (HCC) to explore their clinical and genomic impacts. Approach and Results: We used a merged whole exome or RNA sequencing dataset derived from in-house (n=230) and TCGA (n=362) databases of multiethnic HCC samples.

  Study EGAS00001006599

• Single-Cell RNA-Sequencing of Tumor and Immune Cells from Patients with Asymptomatic Waldenstrom's Macroglobulinemia

  We performed single-cell RNA-seq on tumor and immune cells from 30 patients with IgM Monoclonal Gammopathy of Undetermined Significance (IgM MGUS), Smoldering Waldenstrom's Macroglobulinemia (SWM), and overt Waldenstrom's Macroglobulinemia (WM) to identify tumor-intrinsic and immune biomarkers of disease progression in patients with asymptomatic WM. We identified subtypes within MYD88-mutant WM that are associated with clinical presentation and/or patient outcomes. We also characterized immune dysregulation in patients with asymptomatic WM, and demonstrated disordered interferon stimulation in T and NK cells of patients.

  Study phs003787

• RNASeq of PDX and CDX tumours treated with ADC

  Enapotamab vedotin (EnaV), an antibody-drug conjugate (ADC) targeting AXL, effectively targets tumors that display insensitivity to immunotherapy and/or tumor-specific T cells in several melanoma and lung cancer models. Mechanistically, EnaV treatment induced an inflammatory response and immunogenic cell death in tumor cells, and promoted induction of a memory-like phenotype in cytotoxic T cells. Combining EnaV with tumor-specific T cells proved superior to any treatment alone in models of melanoma and lung cancer, and increased ICB benefit in models otherwise insensitive to anti-PD-1 treatment.

  Study EGAS00001004562

• Next-generation sequencing data derived from patient single cells or clonal colonies

  The following samples were generated from the patient samples used in the study: - Bulk DNA sequencing specifically targeting mutated sites of interest derived from clonal cell populations (288 monoclonal colonies - 2 replicates). - Targeted Muta-seq method (Patient P342: 2208 cells, Patient HRK: 1066 cells, Patient LAK: 618 cells, Patient P101: 1080 cells) - Smart-seq2 method (Patient P342 - 768 individual cells).

  Dataset EGAD00001006228

• Paired RNA-Seq data from 17 samples of different tumors

  Paired RNA sequencing data (21 runs/ 17 samples) of different tumors. The samples were prepared using the Illumina TruSeq stranded mRNA Kit. The sequencing was done on Illumina HiSeq 4000.

  Dataset EGAD00001009706

• Targeted sequencing data and shallow whole genome sequencing data of Follicular lymphoma.

  Contain data of 2 studies 1: 82 nodal stage 1 FL cases and 139 stage III/IV cases 2: 44 watch and wait stage III/IV and 46 Immediate treatment stage III/IV targeted sequencing data of 369 genes and 12 translocation regions whole genome shallow sequencing data

  Study EGAS00001005755

• Facioscapulohumeral dystrophy transcriptome signatures correlate with different stages of disease and are marked by different MRI biomarkers

  This project includes RNA-sequencing data from human FSHD and control skeletal muscle biopsies. This project includes data from 28 FSHD patients (total 37 samples, including vastus lateralis and tibialis anterior muscles) and 12 control individuals (total 24 samples, including vastus lateralis and tibialis anterior muscles).

  Study EGAS00001005782

• WES-based association study of cefaclor-induced anaphylaxis

  This study investigates the genetic factors associated with cefaclor-induced anaphylaxis using whole-exome sequencing (WES).

  Study EGAS50000001163

• LUMC Department Biomedical Data Sciences, Osteoarthritis group

  Committee to control single nucleus multiomics data generated within the project Single Cell Microgel embedded iPS-cells to map molecular variability of cell differentiation using a systems biology approach (SCI-MAP) at the LUMC.

  Dac EGAC50000000644

• MSI_Cancer_Models___WGS

  The study will use whole genome sequencing to aid in define determinants of WRN dependency in MSI Cancer models.

  Study EGAS00001004178

• Myeloproliferative_Neoplasms__MPN__Exome_Validation_Study

  Experiments using targeted pulldown methods will be sequenced to validate findings in the exomes of patients with Myeloproliferative Neoplasms (MPN).

  Study EGAS00001000404

• Impact of BRCA mutation type in non-tumorous breast tissue transcriptome

  To investigate the transcriptomic difference between BRCA1 vs. BRCA2 carriers, RNA sequencing was carried out.

  Study EGAS00001004890

• Functional dissection of inherited non-coding variation influencing multiple myeloma risk

  The project aimed at identification of genotype dependent chromatin accessibility in MM patients.

  Study EGAS00001005394

• CNV profile in HSP90 inhibitor resistant K562 cells

  Analysis of the acquired copy number profile in K562 cell which got resistant against HSP90 inhibitors.

  Study EGAS00001006385

• Longitudinal ctDNA in Uveal Melanoma

  Assess the efficacy of using multi-modal ctDNA analysis to detect relapse in patients with uveal melanoma

  Study EGAS00001006373

• Delineating pediatric brain tumor progression using single-nuclei sequencing

  raw fastq files from the single-nuclei RNA-seq experiments generated from 42 paediatric CNS tumour samples by the 10X Genomics technology.

  Dataset EGAD50000001831

• Saliva microbiota in Finnish children

  The saliva microbiota of 972 Finnish children, aged 9-14 years was characterized using the 16S rRNA (V3-V4) gene sequencing with Illumina Hiseq platform.

  Dataset EGAD00001004145

• RNAseq data set used in the study, 10 samples

  RNAseq data set used in the study, 10 samples

  Dataset EGAD00001007967

• Initial WGS of plasma cell neoplasms in fire fighters exposed to the WTC attack

  Initial WGS of plasma cell neoplasms in fire fighters exposed to the WTC attack

  Dataset EGAD00001006896

• Total RNA sequencing in M1911

  The dataset comprises total RNA sequencing data obtained from two samples of testicular tissue from the individual M1911, who was diagnosed with meiotic arrest.

  Dataset EGAD00001008639

• Assessing mitochondrial bioenergetics in coronary artery disease: A translational left ventricular tissue study in humans (The AMBITION study).

  Single nuclei transcriptomic data from the AMBITION study.

  Dataset EGAD00001011078

• Variant calling for UPST-SCCHN3 cohort

  Tumor versus Germline variant calling on UPST-SCCHN3 cohort

  Dataset EGAD50000002178

• NANOPORE_TALL_t_14_16_translocation

  Nanopore sequencing for patients with t(14;16) translocated T-ALL

  Dataset EGAD50000001785

• WXS_TALL_t_14_16_translocation

  Whole exome-sequencing for patients with t(14;16) translocated T-ALL.

  Dataset EGAD50000001783

• WGS_TALL_t_14_16_translocation

  WGS data for patients with t(14;16) translocated T-ALL.

  Dataset EGAD50000001782

• WGS data for medulloblastoma samples (MDT-AP)

  WGS data of medulloblastoma tumor/control pairs.

  Dataset EGAD00001003125

• GM18507 direct library preparation (DLP) single-cell genomes

  Microfluidic direct library preparation (DLP) single-cell whole-genome BAM files for near-diploid immortalized lymphoblastoid cell line GM18507.

  Dataset EGAD00001003148

• Sequencing data for ICGC Oesophageal Adenocarcinoma tissue samples - barretts_1

  Samples from Ross Innes et. al 2015 - doi:10.1038/ng.3357

  Dataset EGAD00001001394

• Low-depth whole genome sequencing across multiple isolated populations

  Isolated populations have unique population genetics characteristics that can help boost power in genetic association studies for complex traits. Leveraging these advantageous characteristics requires an in-depth understanding of parameters that have shaped sequence variation in isolates. This study performs a comprehensive investigation of these parameters using low-depth whole genome sequencing (WGS) across multiple isolates.

  Dataset EGAD00001002014

• Integrative Profiling of T790M Negative EGFR Mutated NSCLC Reveals Pervasive Lineage Transition and Therapeutic Opportunities

  We performed whole exome and transcriptome analysis of 59 first- and second-generation EGFR TKI resistant metastatic EGFR mutated patients to characterize and compare molecular alterations mediating resistance in T790M positive and negative disease. Transcriptomic analysis revealed ubiquitous loss of adenocarcinoma lineage gene expression in T790M negative tumors, orthogonally validated using multiplex immunohistochemistry. There was enrichment of genomic features such as TP53 alterations, 3q chromosomal amplifications, whole genome doubling and non-aging mutational signatures in T790M negative tumors. Almost half of resistant tumors were further classified as Immunehot, with clinical outcomes conditional on immune cell infiltration state and T790M status. Finally, using a Bayesian statistical approach, we explored how T790M negative and positive disease might be predicted using comprehensive genomic and transcriptomic profiles of treatment-naïve patients.

  Study EGAS00001005389

• Integrated Genomic and Transcriptomic Analysis of Small Cell Lung Cancer Reveals Inter- and Intratumoral Heterogeneity and a Novel Chemotherapy-Refractory Subtype

  We integrated histology, transcriptome, exome, and treatment outcomes of small cell neuroendocrine cancer (SCNC) from a range of metastatic sites, revealing complex intra- and intertumoral heterogeneity of neuroendocrine (NE) differentiation and transcriptomic subtypes (ASCL1, NEUROD1, POU2F3, YAP1 and ATOH1). High NE SCNCs were more likely to benefit from replication stress-targeted therapies, in contrast to non-NE tumors which were more likely to respond to immune response-targeted therapies.

  Study phs002541

• A110632A

  Whole genome sequencing for single cells for library A110632A 1151 cells; filetype=bam

  Dataset EGAD00001007094

• A110632B

  Whole genome sequencing for single cells for library A110632B 892 cells; filetype=bam

  Dataset EGAD00001007095

• A118833A

  Whole genome sequencing for single cells for library A118833A 919 cells; filetype=bam

  Dataset EGAD00001007096

• A118833B

  Whole genome sequencing for single cells for library A118833B 1147 cells; filetype=bam

  Dataset EGAD00001007097

• A118845B

  Whole genome sequencing for single cells for library A118845B 1209 cells; filetype=bam

  Dataset EGAD00001007098

• A118869A

  Whole genome sequencing for single cells for library A118869A 1165 cells; filetype=bam

  Dataset EGAD00001007099

• A118869B

  Whole genome sequencing for single cells for library A118869B 1124 cells; filetype=bam

  Dataset EGAD00001007100

• A95626A

  Whole genome sequencing for single cells for library A95626A 1040 cells; filetype=bam

  Dataset EGAD00001007103

• A95634B

  Whole genome sequencing for single cells for library A95634B 1335 cells; filetype=bam

  Dataset EGAD00001007105

• A95646A

  Whole genome sequencing for single cells for library A95646A 1071 cells; filetype=bam

  Dataset EGAD00001007106

• A95653B

  Whole genome sequencing for single cells for library A95653B 1342 cells; filetype=bam

  Dataset EGAD00001007107

• A95663B

  Whole genome sequencing for single cells for library A95663B 1364 cells; filetype=bam

  Dataset EGAD00001007108

• A95675A

  Whole genome sequencing for single cells for library A95675A 668 cells; filetype=bam

  Dataset EGAD00001007109

• A95731B

  Whole genome sequencing for single cells for library A95731B 1307 cells; filetype=bam

  Dataset EGAD00001007110

• A96115A

  Whole genome sequencing for single cells for library A96115A 1635 cells; filetype=bam

  Dataset EGAD00001007111

• A96115B

  Whole genome sequencing for single cells for library A96115B 1201 cells; filetype=bam

  Dataset EGAD00001007112

• A96118A

  Whole genome sequencing for single cells for library A96118A 1193 cells; filetype=bam

  Dataset EGAD00001007113

• A96130B

  Whole genome sequencing for single cells for library A96130B 1267 cells; filetype=bam

  Dataset EGAD00001007114

• A96178B

  Whole genome sequencing for single cells for library A96178B 846 cells; filetype=bam

  Dataset EGAD00001007116

• A96181C

  Whole genome sequencing for single cells for library A96181C 1216 cells; filetype=bam

  Dataset EGAD00001007117

• A96225B

  Whole genome sequencing for single cells for library A96225B 959 cells; filetype=bam

  Dataset EGAD00001007119

• A96225C

  Whole genome sequencing for single cells for library A96225C 1034 cells; filetype=bam

  Dataset EGAD00001007120

• A96240A

  Whole genome sequencing for single cells for library A96240A 1493 cells; filetype=bam

  Dataset EGAD00001007121

• A98172A

  Whole genome sequencing for single cells for library A98172A 898 cells; filetype=bam

  Dataset EGAD00001007123

• A98256A

  Whole genome sequencing for single cells for library A98256A 1372 cells; filetype=bam

  Dataset EGAD00001007124

• A98256B

  Whole genome sequencing for single cells for library A98256B 1437 cells; filetype=bam

  Dataset EGAD00001007125

• A98257B

  Whole genome sequencing for single cells for library A98257B 1286 cells; filetype=bam

  Dataset EGAD00001007126

• A98258B

  Whole genome sequencing for single cells for library A98258B 1357 cells; filetype=bam

  Dataset EGAD00001007127

• A98274B

  Whole genome sequencing for single cells for library A98274B 1295 cells; filetype=bam

  Dataset EGAD00001007128

• A98282A

  Whole genome sequencing for single cells for library A98282A 1198 cells; filetype=bam

  Dataset EGAD00001007129

• A98283A

  Whole genome sequencing for single cells for library A98283A 1137 cells; filetype=bam

  Dataset EGAD00001007130

• A98285A

  Whole genome sequencing for single cells for library A98285A 1422 cells; filetype=bam

  Dataset EGAD00001007131

• A98295B

  Whole genome sequencing for single cells for library A98295B 1381 cells; filetype=bam

  Dataset EGAD00001007132

• A110673B

  Whole genome sequencing for single cells for library A110673B 1153 cells; filetype=bam

  Dataset EGAD00001007603

• A118830A

  Whole genome sequencing for single cells for library A118830A 912 cells; filetype=bam

  Dataset EGAD00001007604

• A118862A

  Whole genome sequencing for single cells for library A118862A 1070 cells; filetype=bam

  Dataset EGAD00001007605

• A118862B

  Whole genome sequencing for single cells for library A118862B 1152 cells; filetype=bam

  Dataset EGAD00001007606

• A95623B

  Whole genome sequencing for single cells for library A95623B 1363 cells; filetype=bam

  Dataset EGAD00001007608

• A95697B

  Whole genome sequencing for single cells for library A95697B 1233 cells; filetype=bam

  Dataset EGAD00001007610

• A95700A

  Whole genome sequencing for single cells for library A95700A 1172 cells; filetype=bam

  Dataset EGAD00001007611

• A95703A

  Whole genome sequencing for single cells for library A95703A 740 cells; filetype=bam

  Dataset EGAD00001007612

• A96114A

  Whole genome sequencing for single cells for library A96114A 798 cells; filetype=bam

  Dataset EGAD00001007615

• A96124B

  Whole genome sequencing for single cells for library A96124B 1241 cells; filetype=bam

  Dataset EGAD00001007616

• A96155C

  Whole genome sequencing for single cells for library A96155C 1316 cells; filetype=bam

  Dataset EGAD00001007617