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• Transcriptome profiling of HNSCC treated with PD1/PDL1

  Immune checkpoint inhibitors have improved survival in several solid tumors, including head and neck squamous cell carcinoma (HNSCC). However, current use of PD-1/PD-L1 inhibitors relies on PD-L1 expression, which does not reliably predict patient response. Therefore, better predictive biomarkers are needed to identify which patients benefit from immunotherapy. Previous studies suggest that genomic and transcriptomic features may help predict treatment response. This study aims to integrate genomic, transcriptomic, and methylomic data from 31 patients with recurrent/metastatic HNSCC to identify new biomarkers of resistance to anti-PD-1/PD-L1 therapy.

  Dataset EGAD50000002506

• Whole genome sequence and RNA-seq data from paired tumour and germline samples from mesothelioma patients

  Whole genome sequencing from paired tumour and germline malignant pleural mesothelioma samples

  Dataset EGAD00001008341

• scMultiome

  This dataset gather scMultiomic data including RNA-seq and ATAC-seq in MM.1S in control and dex condition at 1h and 4h

  Dataset EGAD00001011140

• National Cancer Institute (NCI) Primary Human Melanocyte QTL Study

  In order to create a melanocyte-specific QTL resource, we obtained primary human melanocyte cultures isolated from foreskin of 106 healthy newborn males predominantly of European descent. Melanocytes were cultured in lot-matched culture medium in randomized batches to minimize variability that could be introduced by culturing conditions. RNA sequencing and direct SNP genotyping of these samples produced an average of ~87.9 million reads (paired-end, stranded, 126bps), and ~713,000 SNP genotypes, respectively. Illumina 450K methylation array covered over 485,000 CpGs distributed genome wide.

  Study phs001500

• NCI Laboratory of Translational Genomics (LTG) Human Pancreas QTL study

  We created a human histologically normal pancreas eQTL resource using 91 fresh frozen tissue samples from patients diagnosed with pancreatic cancer (Mayo Clinic and Memorial Sloan Kettering Cancer Center) or from organ donors without a history of pancreatic cancer (Penn State University) by RNA-Sequencing. Genome wide genotyping was done using blood derived DNA samples or normal derived tissue samples. An average of ~369,4 million reads (paired end, stranded, 101 bp) and 724981 genotypes (per sample) were generated.

  Study phs001776

• Plasma cfDNA dsDNA and ssDNA shallow whole genome and exome sequencing data

  This dataset includes fastq files from sWGS and exome sequencing data derived from dsDNA and ssDNA libraries of plasma cfDNA samples extracted by a column- or bead-based DNA extraction method

  Dataset EGAD00001007019

• University College London Great Ormond Street Institute of Child Health DAC

  This DAC oversees access to de-identified datasets generated by the University College London (UCL) Great Ormond Street Institute of Child Health.

  Dac EGAC50000000985

• Bulk RNA-seq

  This RNA-seq dataset comprises 57 samples, from which the proportions of immune cell fractions were estimated using CIBERSORTx.

  Dataset EGAD50000001797

• DETECT-A protein data

  This dataset includes all protein biomarker measurements from the DETECT-A study. All protein biomarkers were evaluated with Luminex bead-based immunoassays obtained from Millipore.

  Dataset EGAD50000000444

• Single cell RNA-Seq of Clear Cell Sarcoma of the Kidney

  Dataset EGAD00001007498

• Tumor-derived exosomes modulate PD-L1 expression in monocytes

  Small RNA expression profiles of the blood plasma-derived exosomes from B-cell chronic lymphocytic leukemia patients

  Dataset EGAD00001003230

• RNA-Seq Medulloblastoma data

  RNA-Seq data from 12 medulloblastoma samples, all group 4 medulloblastomas. The data consists of BAM files aligned using STAR

  Dataset EGAD00001010850

• RNAseq data

  RNA-seq data from PAXgene extracted whole blood of patients enrolled in the COVACTA trial. This dataset includes raw FASTQ files.

  Dataset EGAD00001011168

• ICGC PCAWG Dataset: LIRI-JP_PCAWG_RNA-Seq_TopHat2

  ICGC PCAWG Dataset for RNA-Seq BAM aligned using TopHat2. Project: LIRI-JP.

  Dataset EGAD00001003546

• ICGC PCAWG Dataset: LIRI-JP_PCAWG_RNA-Seq_Star

  ICGC PCAWG Dataset for RNA-Seq BAM aligned using Star. Project: LIRI-JP.

  Dataset EGAD00001003547

• ICGC PCAWG Dataset: CLLE-ES_PCAWG_RNA-Seq_TopHat2

  ICGC PCAWG Dataset for RNA-Seq BAM aligned using TopHat2. Project: CLLE-ES.

  Dataset EGAD00001003548

• ICGC PCAWG Dataset: CLLE-ES_PCAWG_RNA-Seq_Star

  ICGC PCAWG Dataset for RNA-Seq BAM aligned using Star. Project: CLLE-ES.

  Dataset EGAD00001003549

• ICGC PCAWG Dataset: RECA-EU_PCAWG_RNA-Seq_Star

  ICGC PCAWG Dataset for RNA-Seq BAM aligned using Star. Project: RECA-EU.

  Dataset EGAD00001003558

• ICGC PCAWG Dataset: RECA-EU_PCAWG_RNA-Seq_TopHat2

  ICGC PCAWG Dataset for RNA-Seq BAM aligned using TopHat2. Project: RECA-EU.

  Dataset EGAD00001003559

• ICGC PCAWG Dataset: MALY-DE_PCAWG_RNA-Seq_Star

  ICGC PCAWG Dataset for RNA-Seq BAM aligned using Star. Project: MALY-DE.

  Dataset EGAD00001003560

• ICGC PCAWG Dataset: MALY-DE_PCAWG_RNA-Seq_TopHat2

  ICGC PCAWG Dataset for RNA-Seq BAM aligned using TopHat2. Project: MALY-DE.

  Dataset EGAD00001003561

• Fecal WMS UC metadata

  Metadata for fecal WMS data from NCT02749630 ulcerative colitis patients.

  Dataset EGAD00001008820

• Fecal 16S HV metadata

  Metadata for fecal 16S-V4 rRNA gene sequence data from NCT02749630 healthy volunteers.

  Dataset EGAD00001008821

• Fecal 16S UC metadata

  Metadata for fecal 16S-V4 rRNA gene sequence data from NCT02749630 ulcerative colitis patients.

  Dataset EGAD00001008822

• A108757B

  Whole genome sequencing for single cells for library A108757B 1644 cells; filetype=bam

  Dataset EGAD00001007086