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• GO30103 Source Tables

  Source data of clinical study data corresponding to figures reported in the paper titled: Anti-TIGIT antibody improves PD-L1 blockade through myeloid and Treg cells. PMID: 38418879 DOI: 10.1038/s41586-024-07121-9

  Dataset EGAD50000000367

• Cityscape Source Tables

  Source data of clinical study data corresponding to figures reported in the paper titled: Anti-TIGIT antibody improves PD-L1 blockade through myeloid and Treg cells. PMID: 38418879 DOI: 10.1038/s41586-024-07121-9

  Dataset EGAD50000000366

• RNAseq and ATACseq data, derived from HGSC cell lines pre- and post- treatment with an epigenetic compound

  These data consist of transcriptome and chromatin accessibility data (RNAseq and ATACseq respectively) derived from five High-Grade Serous Ovarian Carcinoma (HGSC) cell lines. HGSC lines included PEO1, PEO4, PEA2, OVCAR5 and OVCAR8. Samples were taken pre- and post-treatment with a novel epigenetic compound, HKMTi-1-005, which targets the activity of two histone methyltransferases, EZH2 and G9a.

  Dataset EGAD50000000064

• BASIS miRNA data

  399 tumors profiled using Agilent miRNA microarrays (Product Number G4872A, design ID 046064). The arrays are based on miRBase release 19.0 and 2006 human miRNAs are represented. 150 ng total RNA was used as input.

  Dataset EGAD00010000917

• Molecular characterization of T-PLL by Next-Generation Sequencing

  Patients with T-cell prolymphocytic leukemia (T-PLL) were profiled with multiple OMICS approaches based on Next-Generation Sequencing (NGS). In total, data from RNA-Seq, Whole-Exome Sequencing, Whole-Genome Sequencing and amplicon panel analyses in 134 samples are available. All samples were processed as paired-end libraries on Illumina sequencing machines. The data are available as paired FastQ files.

  Dataset EGAD00001003825

• Chromatin accessibility analysis of hepatocyte-like cell in vitro differentiation from iPSC in comparison to primary human hepatocytes

  Fastq files of ATAC-seq data of induced pluripotent stem cells (iPSC), definitive endoderm (DE), hepatocyte-like cells (HLC) and primary human hepatocytes (PHH). The dataset comprises data from two different in vitro differentiation protocols: Cellartis (Takara Bio, "CEL", n = 4) and as described by Wang et al. (PMID: 28287600, "HAY", n = 1), as well as from 3 PHH donors.

  Dataset EGAD00001005934

• Single cell transcriptomes of in vitro differentiated hepatocyte-like cells in comparison to primary human hepatocytes

  Fastq files of deeply sequenced single cell RNA-seq data (Smartseq2, approx. 2 million reads / sample) of hepatocyte-like cells (HLC) and primary human hepatocytes (PHH). The dataset comprises data from two different in vitro differentiation protocols: Cellartis (Takara Bio, "CEL", n = 3) and as described by Wang et al. (PMID: 28287600, "HAY", n = 1), as well as PHH from 3 donors. Each replicate comprises 96 single cells.

  Dataset EGAD00001005946

• cfDNA

  The mutational status of 112 recurrently mutated genes in B-cell lymphoma was examined by targeted next-generation sequencing (NGS). Libraries were performed with 15-30 ng of cfDNA obtained from plasma using molecular-barcoded library adapters (ThruPLEX Tag-seq kit; Takara) coupled with a custom hybridization capture based method (SureSelect XT Target Enrichment System Capture strategy, Agilent Technologies Inc.) and sequenced in a MiSeq instrument (Illumina, 2x150bp).

  Dataset EGAD00001006566

• Profiling of H3K27ac landscape in five immune cell types from rheumatoid arthritis patients and healthy controls

  We collected peripheral blood mononuclear cells (PBMC) from 6 RA patients and 4 healthy controls, as well as synovial fluid (SF) from the same RA patients. We then sorted B cells, CD4+ and CD8+ T cells, regulatory T cells and monocytes using flow cytometry and profiled regions marked with H3K27ac using CUT&Tag.

  Dataset EGAD00001007003

• WES_SCLC_MDACC

  To identify genomic drivers present in limited-stage small cell lung cancer (LS-SCLC); To determine the overall tumor mutational burden in LS-SCLC; To determine genomic intratumor heterogeneity (ITH) in LS-SCLC.

  Dataset EGAD00001007004

• Whole transcriptome profiling of liquid biopsies from tumour xenografted mouse models enables specific monitoring of tumour-derived extracellular RNA

  Total RNA sequencing (SMARTer Stranded Total RNA-Seq Kit v2) data of extracellular RNA (exRNA) from liquid biopsies of a BRC0004PR PDX and SK-N-BE(2C) CDX mouse model, and total RNA sequencing profiles of the matching PDX tumors.

  Dataset EGAD00001008318

• Genome and transcriptome sequence data from a poorly differentiated chordoma of C1-C2 spine patient

  Genome and transcriptome sequence data from a poorly differentiated chordoma of C1-C2 spine patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001008012

• A living biobank of patient-derived ductal carcinoma in situ Mouse-INtraDuctal xenografts identifies factors associated with risk of invasive progression

  Create a living biobank of patient-derived ductal carcinoma in situ (DCIS) Mouse-INtraDuctal (MIND) xenografts to find factors explaining invasive growth. Samples exist of both primary and pdx samples. Invasive growth was scored in the pdx.

  Dataset EGAD00001009336

• Single-cell transcriptome landscape of developing fetal gonads defines somatic cell lineage specification in humans

  Single-cell RNA-seq dataset recovering the gene expression programs of around 128,000 single cells derived from 17 fetal testes and 16 fetal ovaries from 5 to 12 postconceptional weeks.

  Dataset EGAD00001009811

• DS-ALL RNA-Seq

  RNA-Seq was performed on 249 DS-ALL samples. Library preparation was carried out using TruSeq Stranded Total RNA Library Prep Kit. The libraries were sequenced on a NovaSeq platform with read length of 2×101.

  Dataset EGAD00001009403

• Genome and transcriptome sequence data from a metastatic pancreatic adenocarcinoma patient

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

  Dataset EGAD00001010316

• Genome and transcriptome sequence data from a pancreatic ductal adenocarcinoma patient

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

  Dataset EGAD00001010317

• Low-coverage whole genome methylation sequencing of cell-free DNA from healthy volunteers and allograft transplant recipients

  Low-coverage whole genome methylation sequencing of cell-free DNA (cfDNA) from healthy volunteers (n=2) and allograft transplant recipients (n=11). The cfDNA was extracted from urine and plasma and sequenced using both a single- and double-strand library preparation method (n=15 and n=18).

  Dataset EGAD00001010937

• Comprehensive single-cell genome analysis at nucleotide resolution using the PTA Analysis Toolbox

  Whole genome sequencing data of 57 single (PTA), clonally expanded and bulk human cells. Cells were obtained from bone marrow samples of patients with Fanconi Anemia (PMCFANCNN) or pediatric AML (PBNNNNN), from a clonal intestinal organoid line (STE0072/D-ORGWTNISL), from human cord blood (PMCCB15) and from a human lymphoblastoid cell line (PMCAHH1). WGS libraries were sequenced to ~15-30x genomic coverage (paired-end) on an Illumina Novaseq.

  Dataset EGAD00001011126

• Single cell sequencing on whole bone marrow of NBM and AML

  To generate a cellular taxonomy of the human NBM and AML, representing both rare hematopoietic stem/progenitor cells (HSPCs) and stromal niche populations, allowing assessment of their cellular diversity and predicted intercellular signaling, we performed single cell RNA sequencing (scRNAseq) on viably frozen bone marrow (BM) aspirates from four healthy donors and 6 NPM1+ AML patients at diagnosis

  Dataset EGAD00001011057

• Neoantigen Immunogenicity Landscapes and Evolution of Tumor Ecosystems During Immunotherapy with Nivolumab

  We performed Whole Exome (WXS) and RNASeq sequencing on samples obtained from the same site before and during therapy from our prospective clinical trial (CA209-153, NCT02066636) of nivolumab in advanced Non-small cell lung cancer (NSCLC) patients that progressed on chemotherapy. There are 58 pre and 42 on therapy WXS samples and 24 pre and 12 on therapy RNASeq samples. All WXS tumor samples have matching normal samples.

  Dataset EGAD00001011302

• 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 peritoneal mesothelioma patient

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

  Dataset EGAD00001001310

• Genome and transcriptome sequence data from a peritoneal mesothelioma patient

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

  Dataset EGAD00001001311

• Genome and transcriptome sequence data from an atypical teratoid rhabdoid tumor patient

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

  Dataset EGAD00001001655

• Genome and transcriptome sequence data from an atypical chronic lymphocytic leukemia patient

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

  Dataset EGAD00001001656

• Genome and transcriptome sequence data from a parotid gland cancer patient

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

  Dataset EGAD00001001657

• Genome and transcriptome sequence data from an odontogenic ghost cell carcinoma patient

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

  Dataset EGAD00001001658

• Trimmed bam-files from whole genome sequencing data from plasma DNA

  Single-end sequencing data (trimmed to 60bp) of 104 plasma samples from donors without tumors (male=50; female=54) were merged and used to establish coverage profiles around the TSS and to establish a gene expression prediction algorithm. Dataset includes merged alignements of low coverage whole genome sequencing from plasma DNA from 50 male, 54 female non-cancer donors. Furthermore, 2 patients with metastasized breast cancer were sequenced on a NextSeq with higher depth.

  Dataset EGAD00001002254

• Genome and transcriptome sequence data from a locally advanced breast cancer patient

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

  Dataset EGAD00001004897

• Genome and transcriptome sequence data from a metastatic rectal carcinoma patient

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

  Dataset EGAD00001004898

• Genome and transcriptome sequence data from a invasive ductal carcinoma of right breast patient

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

  Dataset EGAD00001004899

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

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

  Dataset EGAD00001004900

• Single cell RNA sequencing of colorectal cancer with diverse tissue dissociation protocols or fresh vs. frozen cell preparations.

  To evaluate 3 different tissue dissociation protocols or fresh vs. frozen cell preparations, we performed single-cell RNA sequencing on cancer or distant normal tissue dissociates from 2 colorectal cancer patients. Total 18,409 cells from 10 sample preparations were analyzed (5 primary colorectal cancer and 5 matched normal mucosa). The results suggest highly consistent cellular proportions were recovered with different sample preparation methods.

  Dataset EGAD00001005191

• Next Generation Sequencing Characterization of Tregs in Human Peripheral Blood during Autoimmunity

  Tregs were sorted as CD4+CD25+CD127- cells from peripheral blood of 14 healthy individuals, 8 patients with mild/severe rheumatoid arthritis, 1 patient with systemic lupus erythematosus/rheumatoid arthritis, 2 patients with ulcerative colitis and 2 patients with Chrohn's disease. RNA was extracted and polyA libraries were prepared using the Illumina Truseq sample preparation kit v.2. Single-end 75bp sequencing was performed on NextSeq500.

  Dataset EGAD00001005446

• A Protein Neddylation Inhibitor MLN4924 Suppresses Patient-Derived Glioblastoma Cells via Inhibition of ERK and AKT Signaling

  To identify what factors cause a different reactivity to MLN4924, 15 cells were categorized into high, intermediate, and low MLN4924 resistance groups based on the half-maximal inhibitory concentration (IC50) of MLN4924. PDC1, PCD2, PDC3, PDC4, and PDC5 showed high MLN4924 sensitivity, whereas PDC12, PDC13, PDC14, and PDC15 showed low MLN4924 sensitivity. Whole-transcriptome sequencing of these 9 patient-derived glioblastoma stem cells was performed.

  Dataset EGAD00001005709

• Prostate Cancer and Normal Adjacent Prostate RNA-seq samples, NGS-ProToCol

  The dataset "Prostate Cancer and Normal Adjacent Prostate RNA-seq samples, NGS-ProToCol" includes 41 Normal Adjacent Prostate and 51 ribo-depleted Prostate Cancer RNA-seq samples. ---- Detection of fusion transcripts and their genomic breakpoints from RNA sequencing data Youri Hoogstrate, Malgorzata A. Komor, René Böttcher, Job van Riet, Harmen J. G. van de Werken, Stef van Lieshout, Ralf Hoffmann, Evert van den Broek, Anne S. Bolijn, Natasja Dits, Daoud Sie, David van der Meer, Floor Pepers, Chris H. Bangma, Geert J. L. H. van Leenders, Marcel Smid, Pim French, John W.M. Martens, Wilbert van Workum, Peter J. van der Spek, Bart Janssen, Eric Caldenhoven, Christian Rausch, Mark de Jong, Andrew P. Stubbs, Gerrit A. Meijer, Remond J.A. Fijneman, Guido Jenster

  Study EGAS00001002816

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A73044A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1340 samples; filetype=bam

  Dataset EGAD00001004719

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A73044B

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 2057 samples; filetype=bam

  Dataset EGAD00001004720

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A73046B

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1970 samples; filetype=bam

  Dataset EGAD00001004721

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A73047D

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 2091 samples; filetype=bam

  Dataset EGAD00001004722

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A73056B

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1267 samples; filetype=bam

  Dataset EGAD00001004723

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A75616A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 230 samples; filetype=bam

  Dataset EGAD00001004724

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A75616B

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 232 samples; filetype=bam

  Dataset EGAD00001004725

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A75616C

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 239 samples; filetype=bam

  Dataset EGAD00001004726

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A75617A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 692 samples; filetype=bam

  Dataset EGAD00001004727

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A90553A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 612 samples; filetype=bam

  Dataset EGAD00001004728

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A90553C

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1700 samples; filetype=bam

  Dataset EGAD00001004729

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95664B

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 606 samples; filetype=bam

  Dataset EGAD00001004752

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95670A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 615 samples; filetype=bam

  Dataset EGAD00001004753

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95670B

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 636 samples; filetype=bam

  Dataset EGAD00001004754

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95722A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 968 samples; filetype=bam

  Dataset EGAD00001004755

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95724A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 480 samples; filetype=bam

  Dataset EGAD00001004756

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95724B

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 561 samples; filetype=bam

  Dataset EGAD00001004757

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95732A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 928 samples; filetype=bam

  Dataset EGAD00001004759

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95732B

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 635 samples

  Dataset EGAD00001004760

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95736A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1072 samples

  Dataset EGAD00001004761

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96139A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1436 samples; filetype=bam

  Dataset EGAD00001004762

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96145A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 589 samples; filetype=bam

  Dataset EGAD00001004763

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96150A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 656 samples; filetype=bam

  Dataset EGAD00001004764

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96156A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 648 samples; filetype=bam

  Dataset EGAD00001004765

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96156B

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 375 samples; filetype=bam

  Dataset EGAD00001004766

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96165A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 755 samples; filetype=bam

  Dataset EGAD00001004767

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96171A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 492 samples; filetype=bam

  Dataset EGAD00001004768

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96187A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1222 samples; filetype=bam

  Dataset EGAD00001004770

• National Heart, Lung, and Blood Institute (NHLBI) Bench to Bassinet Program: The Pediatric Cardiac Genetics Consortium (PCGC)

  Multi-center, prospective observational cohort study of individuals with congenital heart defects (CHD). Phenotypic data and source DNA derived from 10,000 probands, parents, and families of interest are being collected to investigate relationships between genetic factors and phenotypic and clinical outcomes in patients with CHD.

  Study phs000571

• RNA sequencing of BCP-LBL and EM B-ALL patients samples

  In order to perform comprehensive transcriptomics and gene fusion analyses of a cohort of BCP-LBL and extramedullary (EM) manifestations of B-ALL patients, we performed RNA sequencing of 16 tissue samples from BCP-LBL and EM B-ALL 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 EGAD50000002047

• WGS data of paediatric B-other B cell acute lymphoblastic leukemia (set3)

  The dataset includes FASTQ and BAM/CRAM files from diagnostic and matched remission (control) samples of 10 B-other ALL patients (ALLT-369,ALLT-378, ALLK-109, ALLK-110, ALLK-115, ALLT-391, ALLK-101, ALLK-113, ALLK-123, ALLT-393). Sequencing library was made using PCR free-based WGS library preparation (PCR-), using NEBNext® Ultra™ II DNA Library Prep Kit. Both diagnostic (90x) and remission (30x) samples were sequenced using Illumina NovaSeq 6000.

  Dataset EGAD50000002158

• Transcriptome analysis of human iPSC-derived microglia in a novel human 3D cortical tissue model

  scRNA-seq analysis of human iPSC-derived microglia in a novel, human in vitro 3D cortical tissue model. Samples include three distinct conditions (each as biological duplicates): wild-type microglia extracted from cultures after 1 month (WT_1mo) and 3 months (WT_3mo) of culturing, as well as knock-in microglia extracted from cultures carrying three familial AD mutations in the APP gene (Swedish, Iberian, Arctic; introduced by CRISPR/Cas9-mediated knock-in) after 3 months of culturing (KI_3mo).

  Dataset EGAD50000000677

• Nurminen et al ("GP2Men") Study Primary and Metastatic Prostate Cancer Whole Genome Sequence Data

  We used novel processing techniques to obtain whole genome data together with 3D anatomic and histomorphologic analysis in two men (GP5 and GP12) with high risk PrCa undergoing radical prostatectomy. A total of 22 whole genome-sequenced sites (16 primary cancer foci and 6 lymph node metastatic) were analyzed using evolutionary reconstruction tools and spatio-evolutionary models. Probability models were used to trace spatial and chronological origins of the primary tumor and metastases, chart their genetic drivers, and distinguish metastatic and non-metastatic subclones.

  Dataset EGAD50000000005

• Quantitative Exploratory Proteomics Analysis of Glioblastoma in Initial and Recurrent Tumors

  Shotgun Proteomics; Glioblastoma samples from 11 patients were obtained at initial and recurrent tumor stages. Proteins were extracted, identified and quantified via tandem mass spectrometry based on a TMT isobaric labelling approach. Quatitative proteomics reveals 146 differentially abundant proteins using a patient-matched statistical modelling. Analysis of proteolytic processing reveals differential proteolytic patterns in recurrent tumors. Proteogenomics reveals the presense of 30 single-amino acid variants present in glioblastoma tumor and 1 of those as increased in recurrent tumor.

  Dataset EGAD00010002350

• FFPE

  The mutational status of 112 recurrently mutated genes in B-cell lymphoma was examined by targeted next-generation sequencing (NGS). Libraries were performed with 150 ng of genomic DNA (gDNA) obtained from formalin-fixed paraffin-embedded (FFPE) biopsy using molecular-barcoded library adapters (ThruPLEX Tag-seq kit; Takara) coupled with a custom hybridization capture based method (SureSelect XT Target Enrichment System Capture strategy, Agilent Technologies Inc.) and sequenced in a MiSeq instrument (Illumina, 2x150bp).

  Dataset EGAD00001006565

• Whole genome sequencing of HSPC clones, bulk MSC cultures, and bulk sorted tumor samples

  Whole genome sequencing data (Illumina NovaSeq 6000) of clonal cultures derived from pediatric human bone marrow-derived hematopoietic stem and progenitor cells (in total 35 samples from 7 donors), bulk pediatric acute myeloid/lymphoid leukemia blasts (in total 2 samples from 1 patient) and bulk control mesenchymal stem cell cultures (4 samples from 4 patients) to study the mutation accumulation.

  Dataset EGAD00001006824

• DNA-seq FASTQ files from 16 patients affected by acute intermittent porphyria

  Paired-end DNA-seq FASTQ files from 16 patients affected by acute intermittent porphyria. Whole genome sequencing of these samples was performed in an Illumina HiSeq 4000 instrument. Libraries were prepared using the Fisher PE Kit (Kapa Biosystems). Each sample was multiplexed across flowcells and lanes, leading to a total number of 83 pairs of FASTQ files.

  Dataset EGAD00001006950

• Genomic and Transcriptomic Profile of Paired Primary-Metastasis Colorectal Tumors

  Samples encompass primary colorectal tumors, adjacent normal colonic mucosa and metastasis of 12 patients, collected by Medical Pathologists from surgically removed specimens. Normal mucosa samples were taken more than 2 cm away from the tumor. Tissues were embedded in optimal cutting temperature (OCT) medium, snapshot frozen in liquid nitrogen within 40 minutes of collection and preserved at -80ºC. Samples were collected between June 2010 and October 2017 as part of a prospective biobanking project.

  Dataset EGAD00001007686

• Single-cell RNA-seq data of bronchoalveolar lavage fluid and extramedullary relapse of a multiple myeloma patient with sarcoidosis-like reactions after anti-BCMA CAR T-cell therapy

  We performed single-cell RNA-sequencing (scRNA-seq) of cells in the bronchoalveolar lavage (BAL) fluid at 3-month follow-up of a multiple myeloma patient experiencing sarcoidosis-like pulmonary reactions after anti-BCMA CAR T-cell therapy (Sample alias: A8_3, A9_3; technical replicates). In addition we performed scRNA-seq of a extramedullary relapse lesion at 6-month follow-up (Sample alias: B10_3).

  Dataset EGAD00001008649

• Patient-derived gene and protein expression signatures of NGLY1 deficiency

  Single-end bulk RNA sequencing results of cell lines derived from patients described with NGLY1 deficiency as well as parent and CRISPR edited controls. The cell lines represent 4 different cell types: fibroblasts, lymphoblastoid cells, induced pluripotent stem cells (iPSCs) and neural progenitor cells (NPCs.).

  Dataset EGAD00001008094

• RNAseq from PDAC samples

  BAM files from RNA-seq of PDAC samples used in the COMPASS hENT1 study

  Dataset EGAD00001009409

• Candidate diagnostic variants reported into DECIPHER, Wright NEJM 2023

  Candidate diagnostic variants reported into DECIPHER by 4 April 2022, annotated with clinical and automated pathogenicity assertions (see DOI: 10.1056/NEJMoa2209046). Genomic Diagnosis of Rare Pediatric Disease in the United Kingdom and Ireland, Wright et al, NEJM 2023.

  Dataset EGAD00001010137

• Ither NB in Organoids WGS dataset - Exploring high-throughput drug sensitivity testing in neuroblastoma cell lines and patient-derived tumor organoids in the era of precision medicine

  Ither NB in Organoids WGS dataset - We aimed to launch an online repository integrating genomics and transcriptomics with high-throughput drug screening (HTS) of nineteen commonly used neuroblastoma cell lines and fourteen generated neuroblastoma patient-derived organoids (NBL-PDOs) to improve identification of molecularly matched therapies and support clinical uptake.

  Dataset EGAD00001010282

• Genome and transcriptome sequence data from a malignant rhabdoid tumor tumor patient

  Genome and transcriptome sequence data from a malignant rhabdoid tumor patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015323

• Genome and transcriptome sequence data from a embryonal rhabdomyosarcoma tumor patient

  Genome and transcriptome sequence data from a embryonal rhabdomyosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015324

• Genome and transcriptome sequence data from a NUT midline carcinoma tumor patient

  Genome and transcriptome sequence data from a NUT midline carcinoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015325

• Genome and transcriptome sequence data from a alveolar rhabdomyosarcoma tumor patient

  Genome and transcriptome sequence data from a alveolar rhabdomyosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015329

• Genome and transcriptome sequence data from a embryonal rhabdomyosarcoma tumor patient

  Genome and transcriptome sequence data from a embryonal rhabdomyosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015330

• Genome and transcriptome sequence data from a acute myeloid leukemia tumor patient

  Genome and transcriptome sequence data from a acute myeloid leukemia patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015331

• Genome and transcriptome sequence data from a osteosarcoma tumor patient

  Genome and transcriptome sequence data from a osteosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015332

• Genome and transcriptome sequence data from a pIlomyxoid astrocytoma tumor patient

  Genome and transcriptome sequence data from a pIlomyxoid astrocytoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015333

• Genome and transcriptome sequence data from a wilms tumor tumor patient

  Genome and transcriptome sequence data from a wilms tumor patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015334

• Genome and transcriptome sequence data from a rhabdomyosarcoma, alveolar tumor patient

  Genome and transcriptome sequence data from a rhabdomyosarcoma, alveolar patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015335

• Genome and transcriptome sequence data from a neuroblastoma tumor patient

  Genome and transcriptome sequence data from a neuroblastoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015337

• Genome and transcriptome sequence data from a osteosarcoma tumor patient

  Genome and transcriptome sequence data from a osteosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015338

• Genome and transcriptome sequence data from a metastatic colorectal carcinoma patient

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

  Dataset EGAD00001001307

• Genome and transcriptome sequence data from a primary unknown cancer patient

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

  Dataset EGAD00001001308

• Dataset Plasma-seq

  We performed low coverage whole genome sequencing of plasma DNA from prostate cancer patients to establish copy number profiles on both a genome-wide and a gene-specific level. The data include plasma samples from prostate cacner patients (n=13), non-malignant controls (males, n=10 and females, n=9), plasma samples from pregnancies with aneuploid and euploid fetuses (n=4). Furthermore, we sequenced different tumor samples (n=6) of one patients and a serial dilution of HT29 in a background of normal DNA (n=9).

  Dataset EGAD00001000364

• 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 EGAD00001002534

• 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 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 EGAD00001002533

• 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 EGAD00001002532

• Genome and transcriptome sequence data from a uterine sarcoma patient

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

  Dataset EGAD00001002538