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• Landscape of AL mutations

  Exome Sequencing to Define the Landscape of Plasma Cells in Systemic Light chain Amyloidosis

  Dataset EGAD00001001861

• Exome sequencing Parkinson's disease patients

  In this project we will sequence the exomes of 250 patients with Parkinson's disease

  Dataset EGAD00001000405

• AI_NF1glioma_WES

  The dataset includes 59 tumor samples from 56 NF1-glioma patients profiled by Whole Exome Sequencing.

  Dataset EGAD00001004375

• ICR MOPOPGEN UK exome control series

  BAM files of individuals from the 1958BC aligned to hg17

  Dataset EGAD00001004396

• Metadata file

  "Master" file of patient clinical characteristics and outcomes, samples, and the results of certain analyses, including immunohistochemistry.

  Dataset EGAD00001008792

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

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

  Dataset EGAD00001004708

• Genome and transcriptome sequence data from a adenocarcinoma of the liver patient

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

  Dataset EGAD00001004706

• Direct transcriptional consequences of somatic mutation in breast cancer

  The disordered transcriptomes of cancer encompass direct effects of somatic mutation on transcription; co-ordinated secondary alterations in transcriptional pathways; and increased transcriptional noise. To catalogue the rules governing how somatic mutation Overall, 59% of 6980 exonic substitutions were expressed. Compared to other classes, nonsense mutations showed lower expression levels than expected with patterns characteristic of nonsense-mediated decay. 14% of 4234 genomic rearrangements caused transcriptional abnormalities, including exon skips, exon reusage, fusion transcripts and premature poly-adenylation. We found productive, stable transcription from sense-to-antisense gene fusions and gene-to-intergenic rearrangements, suggesting that these mutation classes may drive more transcriptional disruption than previously suspected. Systematic integration of transcriptome with genome data therefore reveals the rules by which transcriptional machinery interprets somatic mutation.

  Dataset EGAD00001002237

• Genome and transcriptome sequence data from a metastatic squamous cell carcinoma of the esophagus patient

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

  Dataset EGAD00001005835

• Genome and transcriptome sequence data from a metastatic squamous cell carcinoma of the lung patient

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

  Dataset EGAD00001005850

• Genome and transcriptome sequence data from a metastatic cancer to the breast patient

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

  Dataset EGAD00001010959

• Semmelweis University - Biophysics Data Access Committee

  This DAC belongs to the dataset entitled: Next generation sequencing on cardiac samples in Hungarian patients of dilated cardiomyopathy.

  Dac EGAC50000000053

• DAC IBMsnRNAseq

  This DAC manages the data access to our snRNA-seq and spatial transcriptomic data set on healthy and inflamed human skeletal muscle.

  Dac EGAC50000000220

• Czech Roma and non-Roma array data

  42 Roma and 52 non-Roma Czech volunteers genotyped with the Axiom TM genome-wide human origins array

  Dac EGAC50000000478

• Reproducibility of 10x Genomics single cell RNA sequencing method in the immune cell environment

  Study EGAS00001005905

• Metabolic requirements of the metastasis-initiating tumour cell population using oral squamous cell carcinoma (OSCC) as a model system

  Study EGAS00001004765

• cfDNA shallow Whole-Genome sequencing - healthy donors

  sWGS of the blood samples from 14 (fourteen) healthy donors

  Dataset EGAD50000001860

• BCG prime DNA methylation data

  This dataset contains the DNA methylation data of 384 samples from individuals with one or more comorbidities

  Dataset EGAD00010002767

• KIR region SNP genotypes

  KIR gene content imputation from single-nucleotide polymorphisms in the Finnish population

  Dataset EGAD00010002206

• Trained immunity DNA methylation data

  This dataset contains the DNA methylation data of 904 samples from Dutch healthy individuals.

  Dataset EGAD00010002738

• RNA Editing Transcriptome

  Transcriptome sequencing data of tumor and 10 matched normal samples of the EGAS00001000495 project

  Dataset EGAD00001000627

• Ethiopia_Genome_Project_high_coverage_vcf

  Integrated callset of high coverage Ethiopian genomes from the Pagani et al. 2015 AJHG paper (doi: http://dx.doi.org/10.1016/j.ajhg.2015.04.019)

  Dataset EGAD00001003294

• The UCSF Glioblastoma Genome Project #1

  Dataset contains MeDIP-Seq, MRE-Seq and H3K4me3 ChIP-Seq data on 5 GBM patients.

  Dataset EGAD00001000777

• AI_NF1glioma_WES_control

  The dataset includes 43 matched normal samples from 43 NF1-glioma patients profiled by Whole Exome Sequencing.

  Dataset EGAD00001004374

• BIOKEY: A single-cell catalogue of the dynamic changes underlying Checkpoint Immunotherapy response in Early Breast Cancer

  Checkpoint immunotherapy combined with neoadjuvant chemotherapy improves complete pathologic response in a subset of breast cancer patients. Here, we applied single-cell profiling to tumor biopsies collected before and during anti-PD1 therapy. One-third of tumors exhibited proliferative T-cells expanding along CD8+ or CD4+ lineages, which were either characterized by increased cytotoxicity and exhaustion or improved T-helper function, respectively. Lineage tracing in non-expanding tumors revealed at which point in the lineage T-cells were impaired, while gene expression modeling along these lineages revealed novel genes and underlying transcription factors involved in T-cell expansion. Interestingly, different dendritic and myeloid cell phenotypes could either stimulate or inhibit expanding T-cells, while cell-to-cell communication revealed an integrated immune context highly predictive of T-cell expansion, consisting of immune-stimulatory/-inhibitory interactions between cancer and various immune cell types. Our data yield unprecedented insights into the dynamic changes underlying checkpoint immunotherapy response in breast cancer.

  Study EGAS00001004809