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• Spiradenocarcinoma

  • Spiradenocarcinoma is a rare cutaneous sweat gland adnexal cancer with potential for aggressive behaviour. They are classified histologically into low- and high-grade tumours, with morphologically low-grade tumours thought to behave more favourably. However, limited information is available, with only 18 published cases. • We have collected morphologically low-grade spiroadenocarcinomas (one with a lung metastasis) and high-grade spiroadenocarcinomas, as well as some spiradenomas (benign lesions), cylindromas (another type of malignant cutaneous sweat gland adnexal tumour) and hybrid spiradenoma-cylindromas. • H&E-stained sections were reviewed, follow-up was obtained, and immunohistochemistry for Ki-67, p53 and, MYB has been performed. The tumours were solitary, measuring 0.8-7?cm (median: 2.7?cm), with a predilection for the head and neck of elderly patients (median age: 72 years; range 53-92) without gender bias. Histologically, the tumours were multinodular and located in deep dermis and subcutis. A pre-existing spiradenoma was present in all cases. The malignant component was characterized by expansile growth with loss of the dual cell population, up to moderate cytological atypia and increased mitotic activity (median: 10/10 HPF; range 1-28). Additional findings included squamoid differentiation (n=9), necrosis (n=7), and ulceration (n=5). P53 expression was variable and no significant differences were noted in the benign compared with the malignant parts of the tumours. In contrast, in the malignant components the Ki-67 proliferative index was slightly increased, and MYB expression was lost. Follow-up (median: 67 months; range: 13-132) available for 16 patients (84%) revealed a local recurrence rate of 19% but no metastases or disease-related mortality. • Here we wish to exome sequence these cases to define the first genomic landscape for this malignancy.

  Study EGAS00001001799

• Analysis of error profiles in deep next-generation sequencing data

  BackgroundSequencing errors are key confounding factors for detecting low-frequency genetic variants that are important for cancer molecular diagnosis, treatment, and surveillance using deep next-generation sequencing (NGS). However, there is a lack of comprehensive understanding of errors introduced at various steps of a conventional NGS workflow, such as sample handling, library preparation, PCR enrichment, and sequencing. In this study, we use current NGS technology to systematically investigate these questions.ResultsBy evaluating read-specific error distributions, we discover that the substitution error rate can be computationally suppressed to 10-5 to 10-4, which is 10- to 100-fold lower than generally considered achievable (10-3) in the current literature. We then quantify substitution errors attributable to sample handling, library preparation, enrichment PCR, and sequencing by using multiple deep sequencing datasets. We find that error rates differ by nucleotide substitution types, ranging from 10-5 for A>C/T>G, C>A/G>T, and C>G/G>C changes to 10-4 for A>G/T>C changes. Furthermore, C>T/G>A errors exhibit strong sequence context dependency, sample-specific effects dominate elevated C>A/G>T errors, and target enrichment PCR led to aprox 6-fold increase of overall error rate. We also find that more than 70% of hotspot variants can be detected at 0.1% - 0.01% frequency with the current NGS technology by applying in-silico error suppression.ConclusionsWe present the first comprehensive analysis of sequencing error sources in conventional NGS workflows. The error profiles revealed by our study highlight new directions for further improving NGS analysis accuracy both experimentally and computationally, ultimately enhancing the precision of deep sequencing.

  Study EGAS00001003444

• How to use the EGA search box

  Tips on how to search Tip 1: Use simple and clear keywords No matter what you are searching: a study, a dataset or a committee; the search will look recursively in all the fields of all the entities in the database. Thus, there is no need to specify which type of data you are looking for. Try to use single and specific words and avoid long and complex expressions. Try it out: cancer rna-seq instead of cancer studies using RNA-seq. Tip 2: Narrow your results using search operators Search operators give you more control over the results. They manage the way keywords are used to restrict the search. By default, the search engine applies an OR operator when a space is inserted between two words. Include AND (capitalised) between the keywords in your search in order to show only pages containing both terms. Try it out: Search all the studies based on transcriptomic data, including those ones that use RNA sequencing to obtain this data. Tip 3: Do not worry about details The search engine automatically checks for the most common spelling mistakes of given words and suggests the use of the correct version. It also ignores capital letters and most punctuation so none of these mistakes will hamper the accuracy of your search. Besides, when using a combination of words, the search engine will suggest similar combinations with a higher number of results. Tip 4: Use words that are likely to appear within the text Unfortunately, our search engine is not able to interpret words yet. Therefore, words which do not appear in the body text will not return any result despite them denoting a group of present terms. For instance, if we are looking for studies focused on neurological diseases, using neurological as a keyword would not be the best option. Instead, you should use the name of each neurological disease such as bipolar disorder, schizophrenia or depression. In the same fashion, incomplete words do not return any result. Please include an asterisk (*) before and/or after the incomplete word in order to allow for partial matching. Try it out: canc* instead of canc(without wildcard). Also you can try out *oma, or even *geneti* Tip 5: Narrow down your search by filtering the results You can filter the results by the following options: general, study, and dataset. Under these categories, you will find more sub-filters to refine your search. Make sure that you click on Apply in order to filter the results. You can clear the filtering anytime. Advanced Searches Additional example queries: Search for DUO:0000005 and word lung example query Or write: DUO:0000005 AND lung Search for an exome sequencing study in dbGaP example query Or write: study_type: "exome sequencing" AND repository:dbGaP Search for an exome sequencing study in EGA example query Or write: study_type: "exome sequencing" AND repository:ega Search for a dataset that is at the EGA beacon and with type "Whole genome sequencing" and with number of samples between 100 and 2000 and with technology "Illumina HiSeq 2000" example query Or write: is_in_beacon:true AND dataset_types:"Whole genome sequencing" AND samples:[100 TO 2000] AND dataset_technologies:"Illumina HiSeq 2000" Search for PMIDS example query Or write: pmids:32025007

  Documentation discovery/metadata/search-box

• An exome sequencing study of the HIV elite-long term non progressors and rapid progressors (CASCADE cohorts)

  Background: A rare subgroup of HIV infected individuals naturally controls infection without treatment. These ?elite controllers? constitute an important model for the natural control of HIV infection. Indeed, the study of these individuals may provide insights into strategies for the development of HIV vaccines. Although several HLA and chemokine alleles are known to be over-represented in elite controllers, only a small portion of HIV phenotypic variation is explained by known genetic variants. The elite controller phenotype is rare and distinct, representing the extreme of an infectious disease trait. As such, this phenotype may be partly explained by variation in host immune control, which may be characterized by differences in rare functional genetic variants. Genomic regions underlying elite control can be potentially identified by comparing the presence or frequency of variants in this group to that representing the opposite extreme. In this context, ?rapid progressors? is a group defined by its rapid immunological and clinical disease progression. Aim: To extend an existing study, in order to identify DNA sequence variants involved in the control of HIV infection with greater statistical resolution. Specifically, we aim to sequence up to 200 exomes from multiple cohort studies within the EuroCoord CASCADE collaboration (a collaboration of 25 HIV seroconversion cohort studies across Europe).

  Dataset EGAD00001002179

• Clonal haematopoiesis in patients with AAA (2019-04-03)

  Recent advances in genomics have demonstrated that clonal haemopoiesis driven by leukaemia associated somatic mutations is a relatively common phenomenon that increases in frequency with advancing age. Whilst individuals with clonal haemopoiesis have an increased risk of developing haematological malignancies, they also have an increased mortality from other causes. Additionally, certain mutations are almost exclusively seen in individuals aged 70 years or older, whilst others are seen in individuals with non-haematological cancers including breast and ovarian. Recently, clonal haemopoiesis was found to be associated with a significantly increased risk of atherosclerotic cardiovascular disease. This association is thought to be causative with clonally-derived macrophages showing elevated expression of several chemokine and cytokine genes that contribute to atherosclerosis. Another vascular pathology, abdominal aortic aneurysm (AAA), increases with age and shares risk factors with atherosclerosis (including smoking, male sex, high cholesterol). However, the impact of these risk factors and the overlap between AAA and atherosclerosis is poorly understood. To investigate a possible link between clonal haemopoiesis and AAA, we will study DNA samples from 300 patients with AAA and up to 200 controls for evidence of clonal haemopoiesis. This will be done using target DNA enrichment with biotinylated RNA baits followed by high throughput sequencing. . This dataset contains all the data available for this study on 2019-04-03.

  Dataset EGAD00001004895

• Studies of Left Ventricular Dysfunction (SOLVD-BioLINCC)

  Data Access NOTE:Please refer to the "Authorized Access" section below for information about how access to the data from this accession. Access differs from many other dbGaP accessions. ObjectivesThis study was initiated in 1986, primarily to evaluate the effects of enalapril, an ACE inhibitor, on long-term mortality and major morbidity in a group of participants with left ventricular dysfunction. Two large separate trials were run concurrently as part of SOLVD: 1) a prevention trial of participants with low ejection fraction but no overt symptoms of CHF and, 2) a treatment trial of participants with low ejection fraction and symptoms of CHF. In addition, participants at selected sites were entered into substudies to evaluate the effect of enalapril on a number of intermediate outcomes such as right and left ventricular function and hemodynamics, LV mass and wall stress, hormones, arrhythmias, exercise capacity, and quality of life in subsets of participants. Lastly, a registry of 6,336 participants with congestive heart failure of LV dysfunction was designed to describe the clinical course of an unselected group of participants. Background Congestive Heart Failure (CHF) is a major and increasingly recognized public health problem. The recognition that participants with CHF often have elevated peripheral vascular resistance has led to the introduction of vasodilator therapy, which has emerged as an important component of its treatment. Of the vasodilators, the angiotensin-converting enzyme (ACE) inhibitors appeared to be the most promising. In 1985, little was known about the impact of any long-term drug treatment on survival. SOLVD Registry: The SOLVD Registry is a hospital-based observational study, conducted at selected SOLVD hospitals, of participants with at least moderate left-ventricular dysfunction (EF ≤ 45%) and/or radiologically confirmed heart failure. It consists of a main study (n=6,273) and a substudy (n=898). Although there is overlap between the Registry and the SOLVD trials, the Registry sample is not a subset of SOLVD nor is it the pool of participants eligible for both trials. Participants A total of 2,569 participants were enrolled into the treatment study and 4,228 participants were enrolled in the prevention study. The dataset available through the NHLBI contains the prevention and treatment study data as well as the registry data. Conclusions In the prevention trial, a significant reduction in the incidence of heart failure and the rate of related hospitalizations was observed for participants in the enalapril arm. A statistically significant reduction in mortality was not observed in the enalapril treatment arm; however, there was a trend toward fewer total deaths and deaths due to cardiovascular causes among the enalapril participants (SOLVD Investigators, et al., 1992, PMID: 1463530).

  Study phs003668

• Illumina GSA-MD v3 genotyping arrays for 183 samples

  Genotyping arrays for 183 samples from patients with a neuroendocrine tumor of the small intestine. All samples have been hybridized on Illumina GSA-MD v3 arrays with standard automated protocols. Reading of the chips was performed on Illumina iScan+ scanners and this file is the result of primary analysis done using Illumina GenomeStudio software. It contains data for 147 tumors, 2 adenomas, 1 lymph node, 19 mesenteric nodules, 6 liver metastasis and 8 normal ileum samples.

  Dataset EGAD50000000905

• Mapping genetic variants underlying gene regulation in healthy intestinal cell types to identify novel IBD drug targets (2020-05-12)

  Biopsies from the terminal ileum and rectum of healthy individuals are digested on ice to single cells and processed for single-cell RNA-sequencing (10X Genomics and Illumina) This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ . This dataset contains all the data available for this study on 2020-05-12.

  Dataset EGAD00001006139

• MASQ targeted amplicon sequencing data of AML samples at presentation, remission, and relapse, and MASQ data demonstrating performance ranges of the method.

  MASQ targeted amplicon sequencing of AML blood or bone marrow at presentation, and relapse, when available, for 5 patients. Remission samples of both blood and bone marrow are included for 5 patients. Multiple batches (b1,b2) are used for 2 patients. There are 25 assays of AML data. MASQ data demonstrating sensitivity, input range, and batch size are also included, as 12 assays. All data is provided in paired FASTQ files.

  Dataset EGAD00001005121

• To profile the landscape of sebaceous tumours_WES

  Sebaceous tumours are a rare cutaneous cancer with potential for aggressive behaviour. However, limited information is available on these cancers with few published cases. Here we wish to exome sequence these cancers to define the first genomic landscape for this malignancy. We will extract DNA from formalin-fixed, paraffin-embedded (FFPE) cores. Cores may be obtained from lesional and non-lesional tissues of primaries as well as matching metastases. The extracted DNA will be used for exome sequencing. Please note that the dataset was last revised on October 16, 2025.

  Dataset EGAD00001015367