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• Genome and transcriptome sequence data from a breast invasive ductal adenocarcinoma patient

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

  Dataset EGAD00001010999

• Genome and transcriptome sequence data from a metastatic breast carcinoma (er positive) patient

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

  Dataset EGAD00001011002

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

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

  Dataset EGAD00001011005

• Genome and transcriptome sequence data from a inflammatory myofibroblastic lung tumor patient

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

  Dataset EGAD00001011007

• Genome and transcriptome sequence data from a metastatic pancreatic neuroendocrine tumour patient

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

  Dataset EGAD00001011009

• Genome and transcriptome sequence data from a metastatic adenocarcinoma of lung patient

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

  Dataset EGAD00001011010

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

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

  Dataset EGAD00001011011

• 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 EGAD00001011013

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

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

  Dataset EGAD00001011014

• Genome and transcriptome sequence data from a metastatic adenocarcinoma of colon patient

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

  Dataset EGAD00001011015

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

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

  Dataset EGAD00001011016

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

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

  Dataset EGAD00001011017

• Genome and transcriptome sequence data from a metastatic pancreatic neuroendocrine tumour patient

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

  Dataset EGAD00001011019

• GCAT| WGS FASTQ V1

  This dataset include FASTQ files of 808 samples from GCAT cohort. Technology used HiSeq 4000, read length 150 bp, inner mate distance 300 bp. For each sample the paired -ends are generated in separated files. Each FASTQ is splitted in multiple LANEs and grouped by the Multiplex index.

  Dataset EGAD00001008201

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX021_SA854_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 3 samples; filetype=fastq

  Dataset EGAD00001005141

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX021_SA854_002

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 3 samples; filetype=fastq

  Dataset EGAD00001005142

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX021_SA854_003

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 3 samples; filetype=fastq

  Dataset EGAD00001005143

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX021_SA854_004

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 3 samples; filetype=fastq

  Dataset EGAD00001005144

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX023_SA604X9XB02413_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005145

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX023_SA604X9XB02413_002

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 24 samples; filetype=fastq

  Dataset EGAD00001005146

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX024_SA604X9XB02417_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005147

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX024_SA604X9XB02417_002

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005148

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX020_SA604X8XB02164_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 3 samples; filetype=fastq

  Dataset EGAD00001005149

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX019_SA604X7XB02089_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 36 samples; filetype=fastq

  Dataset EGAD00001005150

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX019_SA604X7XB02089_002

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 36 samples; filetype=fastq

  Dataset EGAD00001005151