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• Whole-exome ultra-high throughput sequencing in brain samples of suicide victims who had suffered from major depressive disorder and control subjects who had died from other causes.

  We carried out whole-exome ultra-high throughput sequencing in brain samples of suicide victims who had suffered from major depressive disorder and control subjects who had died from other causes. This study aimed to reveal the selective accumulation of rare variants in the coding and the UTR sequences within the genes of suicide victims. We also analysed the potential effect of STR and CNV variations, as well as the infection of the brain with neurovirulent viruses in this behavioural disorder. As a result, we have identified several candidate genes, among others three calcium channel genes that may potentially contribute to completed suicide. We also explored the potential implication of the TGF-β signalling pathway in the pathogenesis of suicidal behaviour. To our best knowledge, this is the first study that uses whole-exome sequencing for the investigation of suicide.

  Study EGAS00001003081

• WES dataset of a TIL-ACT metastatic melanoma cohort

  Whole-exome sequencing (WES) data from 13 patients with metastatic melanoma in a TIL-ACT cohort, generated to characterize tumor genomics and neoantigen landscapes relevant to adoptive T cell therapy.

  Dataset EGAD50000001731

• alopecia areata

  exome sequencing files from 25 alopecia areata samples from spain.

  Dataset EGAD00001006370

• EGAD00010000500

  Case samples using U133 Plus 2.0 Array

  Dataset EGAD00010000500

• Single-cell RNA sequence analysis of iPS cell-derived cardiomyocytes treated with S-RBD-sfGFP or GFP

  To determine the transcriptional response in human cardiomyocytes treated with SARS-CoV-2 spike receptor-binding domain (S-RBD-sfGFP), human cardiomyocytes differentiated from induced pluripotent stem cells (iPSC-CMs) were replated on day 21 after differentiation and treated with S-RBD-sfGFP or control-GFP for 48 hours on day 26-28. iPSC-CMs were dissociated and the single cell suspension was analyzed by single cell RNA-sequence.

  Study JGAS000620

• RNA-Sequencing and Somatic Mutation Status of Adrenocortical Tumors: Novel Pathogenetic Insights

  To investigate the relationship between transcriptome profile and genetic background in a large series of adrenocortical tumors and to identify new potential pathogenetic mechanisms, we performed transcriptome profiling by high-throughput sequencing. We collected snap-frozen tissue from patients with adrenocortical tumors (n = 59) with known genetic background: 26 adenomas with Cushing syndrome, 17 adenomas with mild autonomous cortisol secretion, 9 endocrine-inactive adenomas, 7 adrenocortical carcinomas. Additionally, we sequenced 4 control samples.

  Study EGAS00001004533

• High-depth whole genome sequencing of paired ductal carcinoma in-situ (DCIS) and germline control samples from 26 individuals.

  Deposited here are whole-genome sequencing data for 26 paired breast cancer DCIS and matched-normal samples taken from the same individual. Average sequence coverage is 118x for DCIS samples and 41x for matched-normals. Matched-normal samples are from blood. Sequencing was performed on an Illumina HiseqX. Due to specific restrictions imposed by the ethical approval at sample collection, the use of the germline data is restricted to filtering of somatic mutation calls only and cannot be used outside this purpose.They are a part of a broader project that uses high-depth WGS to investigate the somatic mutation genomic landscape of DCIS in order to uncover biological insights into breast cancer progression as well as possible methods to stratify DCIS patients for individualised therapy or disease monitoring.

  Dataset EGAD50000002237

• Breast Cancer Single-Cell RNA-Seq Dataset

  Single-cell RNA-Sequencing of 26 primary breast cancers from Wu et al. (2021) study. Data was generated using the Chromium controller (10X Genomics) and sequenced on the NextSeq 500 platform.

  Dataset EGAD00001007495

• Liquid biopsy-based minimal residual disease monitoring for early risk stratification and decision-making in advanced non-small cell lung cancer - Biobank co-hort

  Liquid biopsies generated for minimal residual disease monitoring of advanced non-small cell lung cancer. Ultra deep targeted sequencing of lung cancer specific genes, with UMIs. This dataset consists of the biobank cohort

  Dataset EGAD50000002231

• Liquid biopsy-based minimal residual disease monitoring for early risk stratification and decision-making in advanced non-small cell lung cancer - DEDICATION co-hort

  Liquid biopsies generated for minimal residual disease monitoring of non-small cell lung cancer. Ultra deep targeted sequencing of lung cancer related genes with UMIs. This dataset contains the dedication cohort

  Dataset EGAD50000002230