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• Whole genome sequencing of 76 tumor and normal samples from 11 SI-NET patients

  We have sampled 11 patients with multifocal SI-NETs. The complete genome sequences of 65 tumor and tissue samples including 42 intestinal lesions, 14 adjacent lymph node metastases, 5 distant metastases, as well as of 4 normal tissue and 11 normal blood samples were determined. This allowed elucidation of phylogenetic relationships between tumors within individual patients.

  Study EGAS00001005096

• TRACERx NSCLC - whole genome sequencing for ctDNA study

  Data used in "An ultra-sensitive and specific ctDNA assay provides novel pre-operative disease stratification in early stage lung adenocarcinoma"

  Dataset EGAD50000000452

• Genomic Landscape of Chordoid Glioma

  This data set consist genomic information of 10 Chordoid Glioma samples: - Exome sequencing: 10 tumors and matched normal DNA for four of them (BAM files) - RNAseq : 10 tumors (fastq files) - CNV array: 9 tumors (IDAT files)

  Dataset EGAD00001004112

• Integrative genomic study of CML patients

  This dataset contains WES and RNA-Seq fastq files for 65 CML patient samples at various stages of disease progression.

  Dataset EGAD00001004179

• Epigentic sequence data of monocytes and macrophages

  Data for paper: Epigenetic dynamics of monocyte to macrophage differentiation with Chip Seq, NOMe, mRNA, total RNA, noncoding RNA, whole genome bisulfite seq,

  Dataset EGAD00001002201

• Fecal 16S rRNA gene sequencing

  Human fecal 16S rRNA gene sequencing data from patients treated with combined anti-CTLA-4 and anti-PD-1 immunotherapy for advanced melanoma.

  Dataset EGAD00001006735

• CASCADE Metastatic Melanoma Rapid Autopsy sequencing data

  Sequence data (paired-end FASTQ format) for 209 samples from 73 sample sites, from 7 individuals. Samples include primary melanomas, metastatic tumours and ctDNA

  Dataset EGAD00001006867

• SMRT-seq

  In this study, we enhanced 5mC detection using SMRT sequencing by holistically analyzing kinetic signals of a DNA polymerase and sequence context for every base within a measurement window. We employed a convolutional neural network to train a methylation classification model.

  Dataset EGAD00001006875

• CBD-RAW-RNASEQ: Bulk RNAseq data

  Bulk RNAseq data from whole blood. For further information regarding this dataset, please contact Katie Burnham and Andew Kwok at contact@combat.ox.ac.uk.

  Dataset EGAD00001007957

• CBD-RAW-SC-ATAC: 10X Single-Cell ATAC

  Raw Illumina sequencing data from single-cell ATACSeq experiments. For further information regarding this dataset, please contact Julian Knight and Tatjana Sauka-Spengler at contact@combat.ox.ac.uk.

  Dataset EGAD00001007963