3796 results for "*oma"

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• Small molecule screen reveals synergy of cell cycle checkpoint kinase inhibitors with DNA-damaging chemotherapies in medulloblastoma (methylation dataset)

  human medulloblastoma xenograft isolated from mouse brain was frozen and genomic DNA or RNA was extracted. Bisulfite converted DNA was processed and hybridised to illumina EPIC or 450K arrays using standard protocols. RNAseq was performed on total RNA.

  Dataset EGAD00001006583

• RNA data of neuroblastoma patients

  94 sample with multi-omics analysis of ALT-positive neuroblastoma tumors, rna sequencing

  Dataset EGAD00001006587

• Transcriptomic profiling of primary tumor and paired hepatic oligometastasis of PDAC

  The dataset was generated for studying metastatic mechanism of pancreatic ductal adenocarcinoma (PDAC). It is consisted of pair-end raw RNA sequencing reads of 33 fresh froze PDAC specimens, which includes 6 tumor-adjacent normal tissues (N), 13 primary tumors (PT), and 14 hepatic metastases (HM) from 14 PDAC patients (6 N-PT-HM trios, 7 PT-HM paires, and 1 HM).

  Dataset EGAD00001006598

• Whole exome sequencing of paired primary tumor (PT) and hepatic metastasis (HM) of PDAC

  This data set contains pair-end raw whole exome sequencing data of matched primary tumors (PT) and hepatic metastases (HM) of pancreatic ductal adenocarcinoma (PDAC). Eight tumor adjacent normal tissues (N) were also evaluated. In total, there are 30 specimens generated from 11 PDAC cases, including 8 PT-HM-N trios and 3 PT-HM paires.

  Dataset EGAD00001006599

• RNAseq of NSCLC and melanoma tumor xenografts treated with ADC

  RNAseq of tumours derived from NSCLC (n=3 PDX; n=1 CDX) and melanoma (n=1 CDX) xenograft models treated with ADC or controls (64 samples; 189 FASTQ files).

  Dataset EGAD00001006620

• Alveolar Rhabdomyosarcoma sequencing data

  This dataset comprises DNA sequencing for tumor and matched normal from an Alveolar Rhabdomyosarcoma patient. It also include RNA sequencing data from the tumor sample.

  Dataset EGAD00001006622

• Sequencing data for Hepatoblastoma samples

  This dataset contains DNA sequencing data for twelve hepatoblastoma tumor samples, four of which have matched normals. Nine of the samples also have RNA sequencing data from the tumor sample. The dataset comprises six samples from patient tissues and six from cell lines; see metadata for details.

  Dataset EGAD00001006621

• scRNA data of neuroblastoma patients

  31 single-cell transcriptomes of neuroblastomas and normal human developing adrenal glands at various stages of embryonic and fetal development

  Dataset EGAD00001006624

• Chip-Seq data of neuroblastoma patients

  144 sample from individuals with ALT-positive neuroblastoma tumors, chip-seq sequencing

  Dataset EGAD00001006625

• hcWGS data of neuroblastoma patients

  238 samples from individuals with ALT-positive neuroblastoma tumors, high coverage whole genome sequencing

  Dataset EGAD00001006626

• Leiomyosarcoma RNA-Seq

  RNA was extracted from fresh frozen LMS material for 29 untreated tumors (24 primary tumors, 5 metastatic12 relapses) and 13 tumors treated with radiation(7 primaries, 6 metastatic relapses). RNA-Seq sequencing was performed using established protocols on Illumina HiSeq 2500

  Dataset EGAD00001006628

• WES inform samples

  89 samples of individuals with ALT-positive neuroblastoma tumors, exome sequencing

  Dataset EGAD00001006637

• lcWGS inform data of neuroblastoma patients

  97 samples of individuals with ALT-positive neuroblastoma tumors, low coverage whole genome sequencing

  Dataset EGAD00001006638

• hcWGS inform data of neuroblastoma patients

  63 samples of individuals with ALT-positive neuroblastoma tumors, high coverage whole genome sequencing

  Dataset EGAD00001006639

• The mutational landscape of human somatic and germline cells

  During the course of a lifetime normal human cells accumulate mutations. Here, using multiple samples from the same individuals we compared the mutational landscape in 29 anatomical structures from soma and the germline. Two ubiquitous mutational signatures, SBS1 and SBS5/40, accounted for the majority of acquired mutations in most cell types but their absolute and relative contributions varied substantially. SBS18, potentially reflecting oxidative damage, and several additional signatures attributed to exogenous and endogenous exposures contributed mutations to subsets of cell types. The mutation rate was lowest in spermatogonia, the stem cell from which sperm are generated and from which most genetic variation in the human population is thought to originate. This was due to low rates of ubiquitous mutation processes and may be partially attributable to a low cell division rate of basal spermatogonia. The results provide important insights into how mutational processes affect the soma and germline.

  Dataset EGAD00001006641

• The mutational landscape of human somatic and germline cells

  During the course of a lifetime normal human cells accumulate mutations. Here, using multiple samples from the same individuals we compared the mutational landscape in 29 anatomical structures from soma and the germline. Two ubiquitous mutational signatures, SBS1 and SBS5/40, accounted for the majority of acquired mutations in most cell types but their absolute and relative contributions varied substantially. SBS18, potentially reflecting oxidative damage, and several additional signatures attributed to exogenous and endogenous exposures contributed mutations to subsets of cell types. The mutation rate was lowest in spermatogonia, the stem cell from which sperm are generated and from which most genetic variation in the human population is thought to originate. This was due to low rates of ubiquitous mutation processes and may be partially attributable to a low cell division rate of basal spermatogonia. The results provide important insights into how mutational processes affect the soma and germline.

  Dataset EGAD00001006642

• The mutational landscape of human somatic and germline cells

  During the course of a lifetime normal human cells accumulate mutations. Here, using multiple samples from the same individuals we compared the mutational landscape in 29 anatomical structures from soma and the germline. Two ubiquitous mutational signatures, SBS1 and SBS5/40, accounted for the majority of acquired mutations in most cell types but their absolute and relative contributions varied substantially. SBS18, potentially reflecting oxidative damage, and several additional signatures attributed to exogenous and endogenous exposures contributed mutations to subsets of cell types. The mutation rate was lowest in spermatogonia, the stem cell from which sperm are generated and from which most genetic variation in the human population is thought to originate. This was due to low rates of ubiquitous mutation processes and may be partially attributable to a low cell division rate of basal spermatogonia. The results provide important insights into how mutational processes affect the soma and germline.

  Dataset EGAD00001006643

• RRBS analysis to characterize the epigenomic conservation between species in the context of Aging and Cancer.

  This dataset contains Raw Reduced Representation DNA bisulfite-sequencing data obtained from human brain samples corresponding to 3 Young and 3 Old individuals (aging context), and 3 normal and 3 Glioblastoma samples (tumor context). RRBS libraries were prepared at Diagenode SA and samples were sequenced using the Illumina Novaseq6000 sequencing platform.The accompanying samples from this study (mouse tissues) are located at the ENA database under the accession number PRJEB41460.

  Dataset EGAD00001006650

• DKFZ-St.Jude Medulloblastoma - 41 MB germline cases, exome data

  Germline exome tumor/control pairs for 41 medulloblastoma cases, MBG cohort sequenced on Illumina machines from the paper "Germline Elongator mutations in Sonic Hedgehog medulloblastoma" (Waszak et al. 2020 Nature).

  Dataset EGAD00001006658

• DKFZ-St.Jude Medulloblastoma - 218 CEF control exomes

  218 control exomes, CEF cohort, sequenced on Illumina machines from the paper "Germline Elongator mutations in Sonic Hedgehog medulloblastoma" (Waszak et al. 2020 Nature).

  Dataset EGAD00001006659

• DKFZ-St.Jude Medulloblastoma - 8 MB cases, exome/WGS data

  Tumor/Control pairs for 8 medulloblastoma cases, MB cohort, mixed exome and whole genome data, sequenced on Illumina machines from the paper "Germline Elongator mutations in Sonic Hedgehog medulloblastoma" (Waszak et al. 2020 Nature).

  Dataset EGAD00001006660

• DKFZ-St.Jude Medulloblastoma - 70 PAN-GATC control exomes

  Exome controls for 70 individuals, PAN-GATC cohort, sequenced on Illumina machines from the paper "Germline Elongator mutations in Sonic Hedgehog medulloblastoma" (Waszak et al. 2020 Nature).

  Dataset EGAD00001006661

• DKFZ-St.Jude Medulloblastoma - 3 XI046 SF controls, WGS data

  3 control whole genomes, SF cohort, sequenced on Illumina machines from the paper "Germline Elongator mutations in Sonic Hedgehog medulloblastoma" (Waszak et al. 2020 Nature).

  Dataset EGAD00001006662

• DKFZ-St.Jude Medulloblastoma - 9 SJMB tumor/control pairs, exome

  9 tumor/control exomes, SJMB samples, sequenced on Illumina machines from the paper "Germline Elongator mutations in Sonic Hedgehog medulloblastoma" (Waszak et al. 2020 Nature).

  Dataset EGAD00001006663

• DKFZ-St.Jude Medulloblastoma - 6 TB control exomes

  6 control exomes, TB cohort, sequenced on Illumina machines from the paper "Germline Elongator mutations in Sonic Hedgehog medulloblastoma" (Waszak et al. 2020 Nature).

  Dataset EGAD00001006664