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• Genome and transcriptome sequence data from a synovial sarcoma tumor patient

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

  Dataset EGAD00001015313

• Genome and transcriptome sequence data from a recurrence nasopharyngeal rhabdomyosarcoma tumor patient

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

  Dataset EGAD00001015314

• Genome and transcriptome sequence data from a ewing sarcoma tumor patient

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

  Dataset EGAD00001015315

• 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 EGAD00001015316

• Genome and transcriptome sequence data from a pineal parenchymal tumor tumor patient

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

  Dataset EGAD00001015317

• 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 EGAD00001015318

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

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

  Dataset EGAD00001015319

• Genome and transcriptome sequence data from a rosette-forming glioneuronal tumor (RGNT) tumor patient

  Genome and transcriptome sequence data from a rosette-forming glioneuronal tumor (RGNT) patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015320

• Genome and transcriptome sequence data from a choroid plexus carcinoma tumor patient

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

  Dataset EGAD00001015321

• Sperm sequencing reveals extensive positive selection in the human germline -WGS

  Mutations that occur during human ageing in the cell lineages of sperm or eggs have the potential to be transmitted to offspring. In males, positive selection of driver mutations during spermatogenesis is known to increase the birth prevalence of certain developmental disorders and cancer predisposition syndromes. However, direct observation of the scope of this selection in sperm has been limited by the error rates of sequencing technologies. Using the duplex sequencing method known as NanoSeq, we sequenced bulk sperm samples from individuals aged 24 to 75 years. Our findings revealed a linear accumulation mutations per year and mutational signatures consistent with pedigree studies. Deep targeted and deep exome NanoSeq of sperm samples identified genes subject to significant positive selection in the male germline, which are linked to diverse cellular pathways including RAS/MAPK and BMP signaling. Strikingly, nearly all positively selected genes are associated with developmental or cancer predisposition disorders in children. We find that this effect drives an elevated risk of known likely disease-causing mutations in sperm across a wide age range. This implies that the disorders attributed to these genes likely exhibit elevated birth prevalence in human populations, particularly among older fathers. These findings shed light on the dynamics of germline mutations and highlight an increased disease risk for children born to fathers of advanced age.

  Dataset EGAD00001015592

• Sperm sequencing reveals extensive positive selection in the human germline -NanoSeq

  Mutations that occur during human ageing in the cell lineages of sperm or eggs have the potential to be transmitted to offspring. In males, positive selection of driver mutations during spermatogenesis is known to increase the birth prevalence of certain developmental disorders and cancer predisposition syndromes. However, direct observation of the scope of this selection in sperm has been limited by the error rates of sequencing technologies. Using the duplex sequencing method known as NanoSeq, we sequenced bulk sperm samples from individuals aged 24 to 75 years. Our findings revealed a linear accumulation mutations per year and mutational signatures consistent with pedigree studies. Deep targeted and deep exome NanoSeq of sperm samples identified genes subject to significant positive selection in the male germline, which are linked to diverse cellular pathways including RAS/MAPK and BMP signaling. Strikingly, nearly all positively selected genes are associated with developmental or cancer predisposition disorders in children. We find that this effect drives an elevated risk of known likely disease-causing mutations in sperm across a wide age range. This implies that the disorders attributed to these genes likely exhibit elevated birth prevalence in human populations, particularly among older fathers. These findings shed light on the dynamics of germline mutations and highlight an increased disease risk for children born to fathers of advanced age.

  Dataset EGAD00001015590

• Sperm sequencing reveals extensive positive selection in the human germline -TargetedNanoSeq

  Mutations that occur during human ageing in the cell lineages of sperm or eggs have the potential to be transmitted to offspring. In males, positive selection of driver mutations during spermatogenesis is known to increase the birth prevalence of certain developmental disorders and cancer predisposition syndromes. However, direct observation of the scope of this selection in sperm has been limited by the error rates of sequencing technologies. Using the duplex sequencing method known as NanoSeq, we sequenced bulk sperm samples from individuals aged 24 to 75 years. Our findings revealed a linear accumulation mutations per year and mutational signatures consistent with pedigree studies. Deep targeted and deep exome NanoSeq of sperm samples identified genes subject to significant positive selection in the male germline, which are linked to diverse cellular pathways including RAS/MAPK and BMP signaling. Strikingly, nearly all positively selected genes are associated with developmental or cancer predisposition disorders in children. We find that this effect drives an elevated risk of known likely disease-causing mutations in sperm across a wide age range. This implies that the disorders attributed to these genes likely exhibit elevated birth prevalence in human populations, particularly among older fathers. These findings shed light on the dynamics of germline mutations and highlight an increased disease risk for children born to fathers of advanced age.

  Dataset EGAD00001015591

• Multiple Myeloma treated with anti-BCMA T-cell-redirecting therapy (1st Batch)

  Bone marrow samples were collected from patients treated with either anti-BCMA CART and/or anti-BCMA TCE. All samples were sorted using the StemCell EasySep Human CD138 positive selection kit II (StemCell, Cambridge, MA). The positive CD138+ were submitted for WGS, using peripheral blood mononuclear cells as normal matched. WGS was carried out by the Molecular Genomics Core Facility at Moffitt Cancer Center contingent on the availability of high-quality pre-treatment samples. Germline DNA was obtained from peripheral blood mononuclear cells, while tumor DNA was extracted from CD138-enriched bone marrow aspirate specimens using magnetic bead-based selection. Genomic DNA was isolated using the AllPrep DNA/RNA/miRNA Universal Kit (Qiagen). For library preparation, 100 ng of genomic DNA was fragmented using the Covaris ML230 focused ultrasonicator (Covaris, Inc.), followed by library construction with the TruSeq DNA Nano Library Prep Kit (Illumina) in accordance with manufacturer instructions. Library quality and fragment size distribution were assessed via Agilent TapeStation, and quantification was performed using the Kapa Library Quantification Kit (Roche). Sequencing was conducted on the Illumina NovaSeq 6000 system using S4-300 reagent kits with a 2×150 bp paired-end configuration. Tumor samples were sequenced to a median coverage of 60×, and matched germline controls to 30×. Reference Genome: GRCh38.

  Dataset EGAD50000002632

• Building a Database of Genomic Structural Variants in Japanese population

  Purified genomic DNA was purchased from Japanese Collection of Research Bioresources (Japanese B cell DNA bank), National Institutes of Biomedical Innovation, Health and Nutrition in Japan. We sequenced those genomic DNAs using PacBio Sequel II and analyzed genomic structural variations.

  Study JGAS000596

• Building a Database of Genomic Structural Variants in Japanese population

  Purified genomic DNA was purchased from Japanese Collection of Research Bioresources (Japanese B cell DNA bank), National Institutes of Biomedical Innovation, Health and Nutrition in Japan. We sequenced those genomic DNAs using PacBio Sequel II and analyzed genomic structural variations.

  Study JGAS000505

• Ankara Bilkent City Hospital Clinical Research Ethics Committee

  Ankara Bilkent City Hospital Clinical Research Ethics Committee is responsible for the oversight and management of access to genomic and phenotypic data generated by the IDH1 Somatic Mutation Profile in Intrahepatic Cholangiocarcinoma . The committee reviews applications for data access to ensure that the proposed research is consistent with the informed consent provided by participants and meets ethical standards. Access is granted to qualified researchers for non-commercial research purposes upon signing a Data Access Agreement (DAA).

  Dac EGAC50000000940

• Transcriptome analysis of human muscle/myofibers carrying the human nemaline myopathy type 6-associated KBTBD13-R408C variant.

  This dataset contains mRNA-seq results from eleven samples from human donors, each sample being composed of 5-10 rebulked fiber type-specific myofibers. This sample set includes; 1) Three FT-I and three FT-IIa rebulked samples from control individuals 2) Three FT-I and two FT-IIa rebulked samples from NEM6 patients with a KBTBD13R408C variant (NP_001094832.1: p.Arg408Cys)

  Dataset EGAD50000002408

• Sequencing data from the study "Somatic rearrangements causing oncogenic ectodomain deletions of FGFR1 in squamous cell lung cancer"

  This dataset consists of 71 whole-genome samples and 47 RNA-seq samples. All WGS samples are provided in .bam format and RNA-seq samples are provided as .fq.gz (paired-end). Next-generation sequencing data on whole genomes were processed by aligning sequencing reads to a reference genome (NCBI build 37/hg19) using bwa-mem (0.7.13-r1126).

  Dataset EGAD50000001978

• Spatial CosMx Human 6K

  we profiled the cellular composition and TME spatial organization in 4 ICB-resistant HCC patients using single-cell spatial transcriptomics (CosMx Human 6K Discovery Panel). We identified 397 fields-of-view (0.51 mm by 0.51 mm) of hematoxylin and eosin (H&E)-defined tumor and stromal regions followed by cell segmentation using a nuclear stain plus 4 protein markers, yielding 485,209 high-confidence single-cell profiles that were subsequently categorized into distinct cell types based on marker gene annotation.

  Dataset EGAD50000002052

• 10X single-cell Multiome (RNA+ATAC) of bone marrow-derived HSPC

  10X genomics chromium single-cell ATAC+RNA (Multiome) was use to prepare single-nucleus RNA- and ATAC-seq libraries, sequenced on an Illumina NovaSeq 6000 platform. BAM files are provided. Samples from 6 donors were sequenced after sorting for primitive HSPCs in 5 libraries; each library comprises a single donor, except one with cells from 1 male and 1 female donor.

  Dataset EGAD50000002326

• scRNA and V(D)J sequencing of WM under ibrutinib

  Single-cell RNA sequencing (5′ gene expression) and single-cell V(D)J sequencing (B-cell receptor and T-cell receptor) were performed on bone marrow mononuclear cells from patients with Waldenström macroglobulinemia treated with ibrutinib monotherapy. Sequential bone marrow aspirate samples were collected at baseline and after treatment. A total of 222 BAM files are included in this dataset.

  Dataset EGAD50000002279

• Raw data (FASTQ) and processed data (VCF) of 7 patient-derived Sézary Syndrome (SS) cells

  We profile the whole-transcriptome (bulk RNAseq) of 7 patient-derived Sézary Syndrome (SS) cells to identify expression patterns, functional programs and expressed gene mutations that may provide clues on new therapeutic options for SS patients. The libraries were sequenced on NextSeq500 (Illumina) with a paired-end read length of 2x75bp. Raw data (FASTQ) and obtained processed data (VCF) including all called raw variants are available.

  Dataset EGAD50000001646

• scRNA-seq data set for 13 AML patients

  This dataset includes single cell (sc)RNA-seq of N=13 AML patients. The dataset includes bam files that have been purged of reads mapping to cells where a majority of the reads from that cell mapped to the human genome. All scRNA-seq data were generated using the Chromium Next GEM Single Cell 5' Reagent Kits v2 (Dual Index) from 10X Genomics.

  Dataset EGAD50000001346

• mRNA profiling of CAFs and cancer cells in response to TGF-β and BMP signaling

  TGF-β and BMP signalings are important signaling pathways in the tumor microenvironment during cancer progression. This RNA-sequencing (62 fastq pairs) analysis explored how cancer-associated fibroblasts (CAFs) from human (19TT) and mice (Balbc A/B) respond to TGF-β, BMP2, or Gremlin antibody, as well as how cancer cells (66cl4) respond to Gremlin antibodies.

  Dataset EGAD50000001351

• Smart-seq2 analysis of 11 ETMR patient samples (4,031 high-quality single cells/nuclei).

  We analyzed 11 ETMR patient samples using single-cell transcriptomics (6 from fresh and 5 from frozen material). Samples were profilied by paired-end scRNA-sequencing using the Smart-Seq2 protocol on a NextSeq 500 sequencer (Illumina). The dataset contains 8,062 fastq files of 4,031 high-quality single cells/nuclei. Raw fastq files of high-quality cells are shared.

  Dataset EGAD50000001379