3794 results for "*oma"

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• sc-RNA and sc-BCR sequencing of multiple myeloma and precursors

  bam files of sc-RNA and sc-BCR sequencing of multiple myeloma and precursors from 65 samples

  Dataset EGAD00001009648

• Sequencing data for ICGC Oesophageal Adenocarcinoma tissue samples - 100_all_samples

  All samples from the "100" project

  Dataset EGAD00001001457

• Sequencing data for ICGC Oesophageal Adenocarcinoma tissue samples - dcc_release_24_dataset

  WGS sequencing for cases from the ICGC ESAD-UK project Tumours 50x Normals 30x HiSeq X BAM files These samples are all available in ICGC release 24

  Dataset EGAD00001003292

• Sequencing data for ICGC Oesophageal Adenocarcinoma tissue samples - 129_cohort

  Sequencing data for ICGC Oesophageal Adenocarcinoma tissue samples - 129_cohort EAC whole genomic sequencing data - Publication Secrier & Li et al., 2016, Nature Genetics

  Dataset EGAD00001002218

• Sequencing data for ICGC Oesophageal Adenocarcinoma tissue samples - chemo_cohort

  Sequencing data for ICGC Oesophageal Adenocarcinoma tissue samples - chemo_cohort

  Dataset EGAD00001002241

• Illumina_450K

  Primary renal cell carcinoma (RCC), RCC metastases and cell lines by Illumina 450K

  Dataset EGAD00010001001

• Sequencing data for ICGC Oesophageal Adenocarcinoma tissue samples - ds_190916_2

  ICGC Oesophageal Adenocarcinoma tissue samples

  Dataset EGAD00001002689

• Sequencing data for oesophageal and related samples - Xiaodun Li et al (WGS, RNA)

  Data supporting: "Esophageal adenocarcinoma organoid cultures recapitulate human disease heterogeneity and provide a model for clonality studies and precision therapeutics." Li et al. WGS (BAM files) RNAseq (BAM files) Tumours, organoids, normals

  Dataset EGAD00001004007

• RNAseq of neuroblastoma PDX and cell lines

  This dataset contains 72 RNAseq (BAM and Fastq files are available for each sample).

  Dataset EGAD00001006558

• 20191008_EGA_MELA_Uveal_WGS

  Illumina platform sequencing of whole genome libraries prepared from paired tumour/normal samples from 103 cases of melanoma Uveal subtype

  Dataset EGAD00001005454

• scRNAseq of neuroblastoma patients

  This dataset contains 19 scRNAseq realized on neuroblastoma patients biopsies straight after surgical act.

  Dataset EGAD00001006556

• ChIPseq of neuroblastoma

  This dataset contains 4 samples (2x input and 2x H3K27ac ChIPseq) in the IC-pPDXC-63 cell line.

  Dataset EGAD00001006557

• Sequencing data for oesophageal and related samples - Scott et al (WGS, RNA)

  Data supporting: "Evidence that polyploidy in esophageal adenocarcinoma originates from mitotic slippage caused by defective chromosome attachments" Scott et al. WGS and RNAseq sequencing data Organoid, tumour and normal samples BAM files

  Dataset EGAD00001006738

• Sequencing data for oesophageal and related samples - Izadi et al (WGS, RNA)

  Data supporting: "Genomic analysis of response to neoadjuvant chemotherapy in esophageal adenocarcinoma" Izadi et al. WGS for tumour and normal samples. RNAseq for tumour samples.

  Dataset EGAD00001007493

• Sequencing data for oesophageal and related samples - Mourikis et al (WGS)

  Data supporting: "Patient-specific detection of cancer genes reveals recurrently perturbed processes in esophageal adenocarcinoma." Mourikis et al. WGS (BAM files) 521 samples

  Dataset EGAD00001004775

• scRNAseq of neuroblastoma PDX and cell lines

  This dataset contains the 22 bam files coresponding to the scRNAseq done in PDX models and cell lines.

  Dataset EGAD00001007870

• Sequencing data for oesophageal and related samples - Ng, Contino et al (WGS)

  Data supporting "Interplay of processes shapes structural variations undergoing selection in oesophageal adenocarcinoma" Ng, Contino et al. WGS (BAM files) 383 oesophageal adenocarcinoma samples 383 normal samples

  Dataset EGAD00001007808

• Sequencing data for oesophageal and related samples - OACs 496 release (WGS)

  Data from 496 OCCAMS (Oesophageal Cancer Clinical And Molecular Stratification) cases. WGS BAM files 496x oesophageal adenocarcinoma samples 496x normal samples

  Dataset EGAD00001007785

• DLP+ Single Cell Genomic Library A98193

  DLP+ Single Cell Genomic Library A98193 for Follicular lymphoma patient sample TFRI_Pair_6_FL

  Dataset EGAD00001010241

• scRNA-seq and scATAC-seq data of bone marrow

  17 scRNA-seq and 16 scATAC-seq datasets on bone marrows derived from 16 patients. The sequencing dataset consists of 5 samples without bone marrow infiltration, defined as controls (C1, C2, C3, C4, and C5) and 11 neuroblastoma infiltrated bone marrow samples from patients with MYCN amplification (M1, M2, M3, M4), ATRX mutations (A1, A2), and cases lacking either alteration (S1, S2, S3, S4, S5).

  Dataset EGAD00001008635

• 20210708_EGA_Melanoma_mk2 WGS 570 donors

  Illumina platform whole genome sequencing data for matched tumour-normal DNA samples from 570 melanoma patients

  Dataset EGAD00001008798

• Oropharyngeal Squamous Cell Carcinoma Mutanome

  This dataset comprises genetic variation data (as somatic indels and snvs VCFs) of 38 OPSCC tumors. WES was done using NextSeq 500 System running in 150 cycles (2x 75bp paired-end) mode. Sequence information was converted to FASTQ format using bcl2fastq v2.20.0.422. VCFs were generated using the Strelka package.

  Dataset EGAD00001009167

• RCC_HTA2.0_Reustle2020

  GeneChip HTA 2.0 data of primary renal cell carcinoma (RCC) related to Reustle et al, Genome Med 12:2020 32. Preprocessing of microarray data was performed using Robust Multi-array Average (RMA).

  Dataset EGAD00010002323

• RCC_HTA2.0_Buettner2022

  GeneChip HTA 2.0 data of primary renal cell carcinoma (RCC) related to Buettner et al, Genome Med 2022. Microarrays were normalized individually using the SCAN method from the R package SCAN.UPC (version 2.26.0, R version 3.6.1). Probe sets were summarized on the Entrez GeneID level using the annotation provided by BrainArray (version 23).

  Dataset EGAD00010002353

• RCC_HTA2.0_Reustle2022

  GeneChip HTA 2.0 data of primary renal cell carcinoma (RCC) related to Reustle et al., Clin Transl Med 12:2022 e883. Microarrays were normalized individually using the SCAN method from the R package SCAN.UPC (version 2.26.0, R version 3.6.1). Probe sets were summarized on the Entrez GeneID level using the annotation provided by BrainArray (version 23).

  Dataset EGAD00010002352