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• Hi-C in endometrial healthy and tumor tissues

  Hi-C libraries have been prepared by enzymatic digestion with MboI restriction enzyme and sonication. Illumina single-indexig primers have been use to amplify ligated fragments. Hi-C experiments have been performed on 10 slices (30um thick) of fresh-frozen tissues derived from 3 healthy and 3 tumor endometrial tissues of post-menopausal patients. Raw paired-end fastq.gz files are provided.

  Dataset EGAD00001010898

• V(D)J and 5' Gene Expression data on patients with aplastic anemia

  Chromium V(D)J and 5' Gene Expression platform (10X Genomics) was used to study patients with aplastic anemia. CD45+ cells from two patients (patient AA-3: 3 longitudinal samples from bone marrow and patient AA-4: 3 longitudinal samples from peripheral blood) were analysed. The raw data was processed using Cell Ranger 3.0.1 pipelines.

  Dataset EGAD00001006937

• Paired-end Whole Exome-seq analysis of the Hypermutation and Malignant Progression in Low-grade Glioma Patients

  113 DNA samples were derived from the tumors of the low grade glioma patients and sequenced using Illumina WES (exome seq) paired-end technology. Dataset contains 113 BAM files aligned to hg19 using BWA v.0.5.9. After mapping duplicated reads were removed, reads were re-aligned around InDels and read base quality score was re-calibrated.

  Dataset EGAD00001005386

• RNASeq of TNBC

  RNAseq data relative to 41 triple negative breast cancer patients.

  Dataset EGAD00001008542

• Whole-exome sequencing of P2RY8-CRLF2-positive ALL on Illumina HiSeq 2000, 100 bp paired-end

  Genomic DNA from leukemic and remission bone marrow mononuclear cells was isolated with the QIAamp DNA Blood Extraction Kit (Qiagen, Venlo, The Netherlands). Libraries were prepared using Nextera Rapid Capture Exome Kit (Illumina, San Diego, USA). Paired-end sequencing of 100 bp reads was performed on a HiSeq 2000 (Illumina) to obtain at least a 50 x coverage.

  Dataset EGAD00001002666

• Combined DNA Methylation and Genotyping via scTAMARA-seq (DNA)

  This dataset features single-cell DNA methylation and nuclear genotyping data obtained using the scTAMARA-seq protocol, a combination of SDR-seq and scTAM-seq. The targeted panel, 200 DNA methylation (a subset of the orginal 448 CpG targets) and 167 genotyping targets, were applied to a CD34+ enriched bone marrow sample from patient X.1. The data was generated on the Mission Bio Tapestri platform.

  Dataset EGAD00001015496

• single-cell transcriptomics data from immune cells

  Smart-seq2 protocol was used to perform single cell RNA-sequencing on 465 immune cells. The immune cells analysed include 215 HLA-DQ2: gluten-(DQ2.5-glia-α1, -α2, -ω1, and -ω2) tetramer-sorted T cells, 247 transglutaminase 2 (TG2)-positive plasma cells from intestinal biopsy or peripheral blood from celiac disease patients, and 3 unassigned cells in 3 batches.

  Dataset EGAD00001004081

• Failure of Differentiation of the Rhombic Lip Constitutes Medulloblastoma

  We used single-cell transcriptomics to study cells from the developing human cerebellum, and show that different molecular subgroups of medulloblastoma resemble distinct glutamatergic progenitors.

  Dataset EGAD00001008381

• Transcriptome Changes in ASD (NRXN1α+/-) iPSC-derived neurons

  This dataset contains 10 fastq files from 10 cell lines (4 cell lines from 3 patients and 6 cell lines from 4 controls) that have undergone 50bp single end sequencing with PolyA enrichment strategy (BGI project number HUMpcsN). *please note one of the samples (Patient_4) was named in error and should be corrected to Patient_3 during analysis

  Dataset EGAD00001007993

• Childhood cerebellar tumors mirror conserved fetal transcriptional programs

  We used single-cell transcriptomics to study >60,000 cells from the developing murine cerebellum, and show that different molecular subgroups of childhood cerebellar tumors mirror the transcription of cells from distinct, temporally restricted cerebellar lineages.

  Dataset EGAD00001004318

• RNA sequencing of tumor samples from patients with BPLL

  RNA-Seq was performed on 12 samples of sorted CD19+ tumor cells. RNA-Seq libraries were prepared using the SureSelect Automated Strand Specific RNA Library Preparation Kit as per manufacturer’s instructions (Agilent technologies) and subjected to paired-end (2 x 100 bp) sequencing on HiSeq2000 (Illumina). The files are in FASTQ format.

  Dataset EGAD00001004412

• RNA Sequencing of Colorectal Liver Metastases

  Reverse-stranded paired-end 75 base-pair RNA sequencing libraries of 93 metastatic FFPE samples were constructed using Illumina Total RNA Stranded Kits. Ribosomal RNAs (rRNAs) were depleted by using the Ribo-Zero rRNA Removal Kit (Illumina). Libraries were sequenced on a HiSEQ2500 machine. Five samples were re-sequenced using paired-end 50 base-pair libraries due to the smaller insert sizes.

  Dataset EGAD00001004111

• Understanding population genetics and patterns of genome-wide heterozygosity in a sample of the Croatian isolated populations (ESGIDalmatians)

  Using high-throughput sequencing technologies and analytical tools, we conduct an exome sequencing study that will help understand the population genetics of a Croatian island isolate, in a sample of 200 subjects from the Adriatic island of Vis who were selected to reflect islanders with at least four known ancestors in grandparental line who are original islanders.

  Dataset EGAD00001001387

• Somatic mutations reveal embryonic genetic bottlenecks generating placental mosaicism

  The human placenta harbours chromosomal aberrations that are absent from the fetus in one to two percent of pregnancies. This confined mosaicism suggests that embryonic genetic bottlenecks exist, which phylogenetically segregate placental tissue. Here, we studied the somatic genetic landscape of human placentas by whole genome sequencing of 86 placental biopsies and of 106 microdissections.

  Dataset EGAD00001006337

• Characterization of Neoantigen-reactive T cells by Single-Cell Analysis

  Through CITE-seq and TCR-seq analysis of non-small cell lung cancer (NSCLC) tumor-infiltrating lymphocytes (TIL), we developed a neoantigen-reactive T-cell signature based on clonotype frequency and CD39 protein and CXCL13 mRNA expression. There are four datasets from four NSCLC cases. Each dataset includes (1) Transcriptome of tumor infiltrating lymphocytes (TIL), (2) Cell surface protein expression on TIL by Feature barcoding, (3) T-cell receptor analysis of TIL, and (4) Reference file for feature-barcoding antibodies.

  Study phs002792

• Decade-Long Leukemia Remissions with Persistence of CD4+ CAR T-Cells

  Two patients with chronic lymphocytic leukemia (CLL) were treated with CD19 targeted CAR T therapy and followed over several years. Peripheral blood from both patients at multiple time points was collected, and 5' CITE-Seq with TCR profiling was performed on sorted CD3+CAR+ T cells at multiple time points. Here, we deposit the raw sequencing data for these single-cell experiments. Processed and de-identified data (e.g. cellranger output, Seurat objects) have been made available on a separate public data repository.

  Study phs002931

• 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

• Single-Cell Genome Sequencing of Gastrointestinal Carcinomas

  We experimentally derived copy number profiles and transcriptome profiles of gastrointestinal cancers using single cell sequencing. Using a microfluidic droplet partitioning system, we isolated individual cells of a suspension from a primary solid tumor into droplets. These droplets tag the resultant genomic or transcriptomic material with an identifying barcode that enables bioinformatic single cell tracking. From this joint analysis, we determined the overall level of genomic instability for gastrointestinal cancers as well as transcriptomic consequences from these events.

  Study phs001711

• Single-Sperm Genome Sequencing of Sperm Donors

  This study performed single-cell DNA sequencing of sperm from 20 presumably fertile sperm donors from a sperm bank. In aggregate, these single-cell sequences yield the genomes of the sperm donors. Original analyses consisted of inferring recombination and aneuploidy from the single-cell sequences. The raw data may be useful for re-processing, investigation of other meiotic phenotypes, and other investigations that would benefit from DNA sequence data deriving from sperm cells. Data can be aggregated by molecular identifier, cellular identifier, or sperm donor.

  Study phs001887

• 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

• Childhood Cancer Data Initiative (CCDI): Comprehensive Genomic Sequencing of Pediatric Cancer Cases (CMRI/KUCC)

  This study provides paired tumor normal genomic sequencing data from ~ 200 children with cancer, including both solid tumors and leukemias, done by the Children's Mercy Research Institute (CMRI) and University of Kansas Cancer Center (KUCC). These data include whole genome sequencing (generally, ~20x), whole exome sequencing (generally, ~300x), bulk RNA sequencing (generally, ~80 million reads), and single-cell RNA and ATAC sequencing (>50,000 reads/cell). Additional phenotypic, pathologic, and genetic data, gathered clinically for these samples, are also provided.

  Study phs002529

• Targeted plasma cell-free DNA sequencing for tissue-of-origin determination and donor-derived cell-free DNA quantification in organ transplant recipients and healthy controls

  The dataset comprises targeted deep methylation sequencing data used for both tissue-of-origin determination and donor-derived cfDNA quantification. It includes plasma cfDNA data from stable kidney transplant recipients (n = 31), stable liver transplant recipients (n = 20) and healthy controls (n = 23). In addition, plasma cfDNA samples collected early after transplantation were analyzed from kidney transplant recipients (n = 44) and liver transplant recipients (n = 40). The dataset also features genomic DNA data generated from whole blood (n = 10) and buffy coat (n = 3) from healthy controls, as well as from T cells (n = 1), B cells (n = 2), hepatocytes (n = 1) and kidney epithelium (n = 1). Lastly, genomic DNA data was generated from buffy coat of transplant recipients (n = 17). Here, “n” indicates the sample number.

  Dataset EGAD50000001446

• South African Blood Regulatory (SABR) Resource

  Functional genomics resources are critical for interpreting human genetic studies, however they are predominantly from European-ancestry individuals. Here we present the South African Blood Regulatory (SABR) resource, a map of blood regulatory variation that includes three South Eastern Bantu-speaking groups. Using paired whole genome and blood transcriptome data from over 600 individuals, we map the genetic architecture of 40 blood cell traits derived from deconvolution analysis, as well as expression, splice, and cell type interaction quantitative trait loci (QTL).

  Study EGAS50000001008

• Spatial multiomic analyses reveal carcinogenic pathways in end-stage renal disease

  Patients with end-stage renal disease (ESRD) are at increased risk for acquired cystic kidney disease (ACKD) and renal tumours, but the molecular basis of such disorders remains elusive. Here, we performed spatial immunogenomic analyses on specimens from 43 patients with ACKD and associated tumours. In this study, we characterized the genomic and transcriptomic features of renal tumours in ESRD. Second, we elucidated the genetic background and microenvironment of cysts in ACKD via comprehensive spatial transcriptomics.

  Study JGAS000855

• Genomic features of renal cell carcinoma developed in end-stage renal disease and dialysis

  Patients with end-stage renal disease (ESRD) or receiving dialysis have 3 ���24-fold higher risk for renal cell carcinoma (RCC). Long-term hemodialysis cause acquired cystic disease (ACD) and RCC.���But its carcinogenic mechanism and genomic features are not so clear. In this study, we analyzed whole genome and transcriptome of 38 RCCs, which were developed in ESRD patients receiving dialysis and characterized their genomic features and associations with their histology and dialysis or end-stage renal diseases.

  Study JGAS000533

• VariantMedium: Sensitive and generalizable somatic point mutation calling with 3D DenseNets trained and evaluated on experimental confirmation data

  This study contains whole-exome sequencing (WES) and results of targeted deep-sequencing data of three matched tumor and normal cell lines, with two technical WES replicates each. The calls by Mutect2, Strelka2, and VariantMedium were confirmed using targeted deep sequencing on Illumina Miseq The targeted deep sequencing was performed in three runs and the results are summarized under VCF files, with labels determined for 1663 point mutations and 201 insertion-deletions.

  Study EGAS00001007633

• Genetic_background_for_the_major_psychiatric_disorders_in_the_general_Finnish_population

  Low coverage (4-6x) sequencing on samples from population cohorts (Finrisk, Health2000) will be done at Wellcome Trust Sanger Institute (WTSI) using Illumina HiSeq sequencing technology. We will produce 100bp paired end reads. Variants will be called using the 1000 Genomes Project pipeline. The samples have been selected from a national representative set of 8028 samples from persons of 30 years or older, which were screened for psychotic and bipolar disorders using the Composite International Diagnostic Interview, self-reported diagnoses, medical examination, and national registers.

  Study EGAS00001000162

• Single cell multi-omic data of glioblastoma evolution under therapy

  We report a single-cell multi-omics atlas of GBM longitudinal specimens that represents decades of biobanking. We identify novel cell-intrinsic and cell-extrinsic targets for therapy development which we validate in situ and in low-passage patient-derived cell lines. We identify novel genetic correlates of the mesenchymal cellular phenotype. These studies integrate disparate findings in the literature around hypermutation status and immunogenicity as well as the source of the mesenchymal shift at recurrence.

  Study EGAS00001004909

• Patient tumour data (RNAseq, WGBS, ChIPseq, WGS)

  Content: 60 GB patient tumours and 4 normal brain samples combined in pairs by region (x2=8 total input samples). RNAseq: 1 lane per sample, total strand-specific rRNA-depleted (normal samples were combined = 2 lanes/samples per brain region). WGBS: 2 lanes per sample (normal samples were combined = 2 lanes/samples per brain region). ChIPseq (histone mark): a subset of 20 GB samples were profiled. For the same modification were multiplexed and sequenced on 4 lanes each (H3K27ac, H3K4me1) or a single lane (all others). WGS: used as matching input control for the 20 ChIPseq samples. Data type and technology: RNA-seq: PE 100bp sequenced on HiSeq2000. WGBS: PE 100bp sequenced on HiSeq2000/4000. ChIPseq: SE 50bp sequenced on HiSeq2000/4000. WGS: PE 150bp sequenced on HiSeq X.

  Dataset EGAD00001005492

• RNA-Seq dataset for Genomic rearrangements in Pediatric Cancer

  RNA-Seq data for systematic gene fusion detection in Pediatric Cancer

  Dataset EGAD00001008152

• COVID-19 Severity First Wave of Infection for Severe Patients in Madrid

  We recruited 98 hospitalised patients displaying severe COVID-19 symptoms from the first wave of infection. A stringent exclusion criteria based on non-genetic factors such as age, blood oxygen, radiologic findings and other typical COVID-19 signs was performed. Gingival or peripheral blood samples were taken for 98 individuals and whole exome sequencing performed using ExomeCapture-Seq capture KAPA HyperExome on Illumina machines.

  Dataset EGAD00001008464

• Nasal epithelial cells of PCD and non-PCD patients grown at air-liquid interface for RNAseq analysis

  Nasal epithelial cells of PCD and non-PCD patients grown at air-liquid interface for RNAseq analysis. A total of 10 non-PCD patients (ALI day 14), 9 non-PCD patients (ALI day 21), 8 non-PCD patients (ALI day 28), 4 PCD patients (ALI day 14, day 21 and day 28), and 23 PCD patients (ALI day 21). Non-PCD patients and the 4 PCD patients on the three ALI days were sequenced at a depth of 100M reads, the remaining 23 PCD patients were sequenced at a depth of 70M. Overall sequencing design was rRNA depletion and 150bp paired-end.

  Dataset EGAD00001009498

• A108757B

  Whole genome sequencing for single cells for library A108757B 1644 cells; filetype=bam

  Dataset EGAD00001007086

• RNA-sequencing of meningiomas for integrative molecular classification.

  RNA-sequencing of meningiomas for integrative molecular classification.

  Dataset EGAD00001007494

• BLUEPRINT ChIP-seq data for cells in the haematopoietic lineages, from adult and cord blood samples.

  ChIP-seq data for cells in the haematopoietic lineages, from adult and cord blood samples.

  Study EGAS00001000326

• Genomic profiling of subcutaneous patient derived xenograft models of solid childhood cancer

  The pediatric cancer cohort in this study included 70 PDX models from 65 different individuals. This cohort included a total of 16 different pediatric solid tumor subtypes, including fourteen Wilms tumors, thirteen hepatoblastomas, thirteen osteosarcomas, ten germ cell tumors, four neuroblastomas, three clear cell sarcomas, two adrenal cortical carcinomas, two leydig cell tumors, two medulloblastomas, one embryonal rhabdomyosarcoma (ERMS), one Ewing sarcoma, one pleomorphic sarcoma, one adenocarcinoma, one glioblastoma, one mesothelioma and one ovarian tumor. Notably, we have five samples with multiple PDX models from same patient, including two cases with duplicates (564 and 564-Dup, 1796 and 1796-Dup), one case with two different metastasis (560-SM, 560-LM), one case with two blocks from same tumor (1939 and 1939-Dup), and one case with different primary tumor from same patient (2264 and 1932). We have a total of 353 sequencing data, including 82 RNA sequencing data (RNA-seq), 138 whole-exome sequencing (WES) and 135 low-pass whole-genome sequencing (WGS). For RNA-seq data, we have 61 PDXs and 21 PTs; for WES, we have 67 PDXs, 30 PTs and 40 matched normal germlines; for WGS, we have 64 PDXs, 30 PTs and 40 matched normal germlines. Of which, 19 PT-PDX paired RNA-seq, 28 paired PT-PDX paired WES and WGS were included.

  Dataset EGAD00001009863

• ChIP-sequencing fragment coverage

  Raw sequencing reads from H3K27ac ChIP and input DNA from lymphoblastoid cells of three TET2 mutation carriers and two wild-type family members were quality and adapter trimmed with cutadapt version 1.16 in Trim Galore version 0.3.7 using default parameters. Trimmed reads were aligned to hs37d5 reference genome using Bowtie2 (version 2.1.0). Duplicate reads were removed with samtools rmdup (v1.7). Fragment coverage of paired-end reads was calculated from bam files with BEDtools genomecov (v2.26.0).

  Dataset EGAD00010001671

• Single-cell transcriptomic analyses of peripheral blood mononuclear cells from patients with colorectal cancer metastasized to the peritoneum

  The data published here contains single-cell RNA-sequencing (scRNAseq) data as obtained using the 3' scRNAseq using Chromium Single Cell 3’ Reagent from 10X Genomics on peripheral blood mononuclear cells (PBMC) from patients with colorectal cancer (CRC) and peritoneal metastases (PM). Sequencing was performed in a paired-ended fashion on the NovaSeq6000.

  Dataset EGAD50000000247

• Bulk RNAseq of cultured fibroblasts

  Fastq files from bulk RNAseq of fibroblasts after culture and facs sorting (N=9). Sorted FAP+ CAF cells RNAs were extracted using Qiagen miRNeasy Kit (Qiagen, #217004) according to the manufacturer's instructions. Verification of RNA integrity and quality was performed using the Agilent RNA 6000 nano Kit (Agilent Technologies, #5067-1511). cDNA libraries were prepared using the TruSeq Stranded mRNA Kit (Illumina, #20020594) followed by sequencing on NovaSeq (Illumina).

  Dataset EGAD50000000323

• Cityscape Serum peptide Mass Spec data

  Matrix of counts from the serum peptide mass spec data from patients enrolled in the CITYSCAPE trial, and the sample annotation. Specifically, serum samples at C1D1, C2D1, C3D1, SCRN were collected from a total of 132 patients and subject to Mass Spec at Biognosys. The current study focused on patients who have samples at both C1D1 and C2D1 (n = 64 pairs). Associated metadata also included.

  Dataset EGAD50000000369

• PBMC scRNA-seq data using 10X Genomics platform

  Matrices of counts from single-cell RNA-seq data and single-cell CITE-seq data collected from 16 patients enrolled in GO30103 trial, and the cell level annotation. Specifically, PBMCs at C1D1, C1D15 (2 weeks after treatment), C2D1 (3 weeks after treatment) and C4D1 (9 weeks after treatment) were collected and subject to 10x Genomics protocol. Associated metadata also included.

  Dataset EGAD50000000370

• RNA sequencing of BCP-LBL patients samples

  In order to perform comprehensive transcriptomics and gene fusion analyses of a cohort of BCP-LBL patients, we performed RNA sequencing of 49 tissue samples from BCP-LBL patients. Because the material was available as FFPE, and had a relative low quality, we used a capture-based approach, where NGS libraries obtained from total RNA were captured in 4-plex, using a whole exome capture panel.

  Dataset EGAD50000000419

• Whole Exome Sequencing Bipolar cases matched controls performed at Broad Inst on cohort from Germany

  This research project was a collaboration between University Hospital Frankfurt and the Stanley Center at the Broad Institute. In this project we sequenced and analyzed the whole exomes of 823 Bipolar case/control samples from collaborators in Germany. Genomic DNA from each sample was sequenced to a mean depth of 20x. The exome used Twist capture and samples were sequenced on Illumina HiSeqX machines producing cram files.

  Dataset EGAD50000000563

• Whole Exome Sequencing of Bipolar cases, matched controls at Broad Inst on a cohort from Netherlands

  This research project was a collaboration between VU and the Stanley Center at the Broad Institute. In this project we sequenced and analyzed the whole exomes of 943 Bipolar case/control samples from collaborators in the Netherlands. Genomic DNA from each sample was sequenced to a mean depth of 20x. The exome used Twist capture and the samples were sequenced on Illumina HiSeqX machines producing cram files

  Dataset EGAD50000000619

• RNAseq profiles from the CheckMate-142 clinical trial

  The dataset contains RNAseq profiles of 57 patients from the CheckMate-142 clinical trial. The Allprep DNA/RNA FFPE kit was used to simultaneously purify genomic DNA and RNA from formalin-fixed, paraffin embedded (FFPE) tissue sections. Baseline tumor tissue samples were processed using the Illumina TruSeq RNA Access in-solution hybrid capture panel and underwent subsequent NGS on the Illumina NovaSeq platform. Fastq files are included.

  Dataset EGAD50000000609

• Whole Exome Sequencing of Bipolar cases, matched controls at Broad Inst on cohort from Cambridge, UK

  This research project was a collaboration between Cambridge University, UK and the Stanley Center at the Broad Institute. In this project we sequenced and analyzed the whole exomes of 2,873 Bipolar case/control samples from collaborators in UK. Genomic DNA from each sample was sequenced to a mean depth of 20x. The exome used Twist capture and samples were sequenced on Illumina HiSeqX machines producing cram files

  Dataset EGAD50000000627

• Indonesian Genome Diversity Project 3

  Low coverage whole genome sequences (1-3x) were collected to study human genetic history across Wallacea archipelago and West Papuan Region of Indonesia . We collected 254 newly sequenced genomes mostly from previously undocumented populations including 9 communities in Wallacea and 3 in West Papuan regions. Out of 254, there are 8 high coverage whole genome sequences were produce in the study (L4).

  Dataset EGAD50000000647

• scKaryoSeq of CRISPR-Cas9 edited primary human T cells

  To explore T cell-intrinsic driving forces of CRISPR-induced aneuploidy at the TRAC gene locus, we performed scKaryo-seq (Bolhaqueiro et al., Nature Genetics 2019). We compared the impact of the small molecule pifithrin-alpha in activated TRAC KO T cells. In a separate experiment, we determined the effect of pifithrin-alpha on non-activated T cells edited at the TRAC locus or treated with non-targeting Cas9 RNPs.

  Dataset EGAD50000000929

• Single-cell RNA seq-derived signatures define response patterns to atezolizumab + bevacizumab in advanced hepatocellular carcinoma

  FASTq files and normalised gene expression counts from bulk RNA-sequencing of pre-treatment tumour (n=39) and adjacent non-tumour tissue samples (n=13) from advanced hepatocellular carcinoma (HCC) patients treated with atezolizumab plus bevacizumab.

  Study EGAS50000000838

• Human Single-Oocyte Transcriptome - Control and Cannabis Treated

  RNAseq data of human single oocytes exposed to THC and its metabolites, (mean concentration measured in the follicular fluid, THC1, n=95, 25 ng/mL Δ9-THC, 5 ng/mL 11-OH-THC, 50 ng/mL 11-COOH-THC) or a supraphysiologic, THC2, n=93, 100 ng/mL Δ9-THC, 50 ng/mL 11-OH-THC, 200 ng/mL 11-COOH-THC).

  Dataset EGAD50000001534