14501 results for "PLOS+ONE+Pennsylvania+German+ACS+language+code+pdc+open+access+study"

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• Evolutionary Origins of Recurrent Pancreatic Cancer

  Surgery is the only curative option for patients with Stage I/II pancreatic cancer, nonetheless most patients will recur after surgery and die of their disease. To identify novel opportunities for management of recurrent pancreatic cancer we performed whole exome or targeted sequencing of 10 resected primary cancers and their matched intrapancreatic recurrences or distant metastases. We identified that recurrent disease develops from a monophyletic or polyphyletic origin, and this distinction has potential clinical relevance. In all patients, treatment induced genetic bottlenecks led to a modified genetic landscape and subclonal heterogeneity for driver gene alterations in part due to intermetastatic seeding. In one patient what was believed to be recurrent disease was an independent (second) primary tumor. These findings strongly advocate for routine post-treatment sampling in the management of recurrent pancreatic cancer.

  Study EGAS00001004097

• A collection of 142 samples used to evaluate the sensitivity and specificity of small-scale variation detection in exome-capture data with a particular focus on indel detection.

  The dataset includes exome sequencing data and 704 Sanger sequencing validations for the 142 samples. The 704 Sanger sequencing validations are comprised of 416 variants and 288 sites known to be negative, including 293 indels and 247 negative indel sites. DNA libraries were prepared from genomic DNA using the Illumina TruSeq sample preparation kit. DNA was fragmented using Covaris technology and the libraries were prepared without gel size selection. Target enrichment was performed in pools of six libraries using the Illumina TruSeq Exome Enrichment kit. The captured DNA libraries were PCR amplified using the supplied paired-end PCR primers. Sequencing was performed with an Illumina HiSeq2000 (v3 flow cell, one pool per lane) generating 2x101-bp reads. Technology – Illumina HiSeq 2000

  Study EGAS00001001332

• A benchmarking resource for NGS testing of cancer predisposition genes

  A benchmarking resource of 639 individuals, to assess the analytical sensitivity of cancer predisposition gene (CPG) testing.The dataset includes sequencing data generated using the TruSight Cancer Panel (TSCP) a targeted NGS assay for analysis of CPGs and orthogonally generated data supporting at least one pathogenic variant in a CPG for a total of 645 pathogenic CPG variants.The set of pathogenic CPG variants includes strong representation of some of the most challenging types of pathogenic variants, with 339 indels, including 16 complex indels and 24 insertions or deletions with length greater than 5bp, and 74 exon CNVs, including 23 single exon CNVs. There are 502 pathogenic variants in BRCA1 or BRCA2, making this an important first-line validation dataset for laboratories performing NGS testing of BRCA1 and BRCA2.

  Study EGAS00001002993

• Mullighan - PAX5-driven Subtypes

  Using integrated genomic analysis of 1.988 childhood and adult cases, we describe a revised taxonomy of B-cell acute lymphoblastic leukemia, which incorporates 23 subtypes defined by chromosomal rearrangements, sequence mutations, or heterogeneous genomic alterations. Two subtypes have frequent alterations of the B lymphoid transcription factor gene PAX5. One, PAX5alt, has diverse PAX5 alterations, and a second subtype is defined by a single mutation, PAX5 P80R. We show that P80R impairs B lymphoid development and promotes the development of B-ALL in vivo. These results demonstrate the utility of transcriptome sequencing to classify B-ALL and reinforce the central role of PAX5 as a checkpoint in B lymphoid maturation and leukemogenesis.

  Study EGAS00001003266

• Single cell whole genome sequencing of high hyperdiploid acute lymphoblastic leukemia

  This dataset was collected from viable bone marrow cells obtained at diagnosis from nine patients with high hyperdiploid ALL and one normal bone marrow sample. All samples were subjected to low pass single cell whole genome sequencing with the median sequencing coverage of 0.02x. Single nuclei in G0/G1 phase were isolated using a fluorescence-activated cell sorting (FACS) cytometer. DNA libraries were constructed and associated next-generation sequencing was carried out by European Research Institute for the Biology of Ageing (ERIBA), University of Groningen, University Medical Center Groningen, Groningen, The Netherlands. Further details regarding the DNA libraries construction are available by Bos et. al., 2019 (https://link.springer.com/protocol/10.1007/978-1-4939-8931-7_15). The dataset has been used for copy number aberrations analysis.

  Study EGAS00001006347

• The Collaborative Study on the Genetics of Alcoholism (COGA)

  COGA is a family study of alcoholism, in which the subjects have been drawn from the Collaborative Study on the Genetics of Alcoholism (COGA), a large, ongoing family-based study that includes subjects from seven sites around the US. COGA has gathered detailed, standardized data on study participants, including diagnostic and neurophysiological assessments. This project has already proved successful in identifying several genes that influence the risk for alcoholism and neurophysiological endophenotypes, which have been independently replicated. COGA data were included as part of two Genetic Analysis Workshops, and the phenotypes are familiar to the genetics community. Alcoholic probands were recruited from treatment facilities, assessed by personal interview, and after securing permission, other family members were also assessed. A set of comparison families was drawn from the same communities as the families recruited through an alcoholic proband. Assessment involved a detailed personal interview developed for this project, the Semi-Structured Assessment for the Genetics of Alcoholism (SSAGA), which gathers detailed information on alcoholism related symptoms along with other drugs and psychiatric symptoms. Many participants also came to the laboratories for electroencephalographic studies. Neurophysiological features that have been shown to be useful endophenotypes for which we have linkage and in some cases association results, are included for a subset of the case-control sample: the beta power of the resting electroencephalogram (EEG), the P3(00) amplitude of the visual event-related potential (ERP), and the theta and delta event-related oscillations (EROs) underlying the P3. As part of COGA, a set of informative families was selected to have Genome-Wide Association data obtained within families. Genotyping was performed using the Illumina Human OmniExpress array 12.VI to genotype 2,282 subjects selected from 118 densely affected families. Genotyping was performed at the Genome Technology Access Center at Washington University School of Medicine in St. Louis. In addition, we also included genotypes for subjects (n=275 subjects) from these 118 families who were genotyped in a previous case-control GWAS using the Illumina 1M array. For quality control purposes, 51 of the 275 subjects were genotyped again on the Illumina Human OmniExpress array at the Washington University School of Medicine core facility.In addition, exome sequencing data on a subset of individuals with GWAS were added in version 2 (v2). For v2, a subset had 30X Whole Genome Sequencing (WGS) as part of the NIDA Sequencing Initiative. The subset contained two distinct sets: Sibling pairs where one sibling had at least two dependence diagnoses in the set (alcohol, cannabis, cocaine, and opioid), and the other had none, and non-related Case-Control pairs matched for age and ethnicity where the cases had alcohol and at least 2 other dependence diagnoses and controls had none. After sequencing, some sibling pairs are re-classified as half siblings. Three VCF files (small variants, structural variants, and copy number variations) are provided. Additional substance use variables are made available in v2. We note that the full sample data are deposited in four dbGaP submissions and the sequenced samples are split across all four: CIDR: Collaborative Study on the Genetics of Alcoholism Case Control Study [phs000125]. GWAS data on cases (primarily probands) and controls drawn from the families. Families with highest density of alcohol dependence and/or extreme event-related oscillation data [phs000763]. GWAS data on 119 extended families of European descent are available here, along with extensive documentation. Study on the Genetics of Alcoholism (COGA): African American Family GWAS [phs000976]. GWAS data on all available COGA families of African descent are available. COGA: Smokescreen GWAS [phs001208]. GWAS data on all remaining COGA DNA samples, primarily of other racial background, were genotyped on the Smoke Screen array. A listing of all sequenced pairs is provided in the documentation to facilitate the merging of these samples.

  Study phs000763

• Single-cell somatic copy number variants in brain using different amplification methods and reference genomes

  This dataset contains 224 paired fastq files (112 single cells) from the following samples: brains from two Multiple System Atrophy patients and one control, and non-brain controls (fibroblasts, NA12878)

  Dataset EGAD50000000030

• Single cell sequencing data from Shwachman-Diamond syndrome bone marrow samples

  This dataset includes single cell amplicon based sequencing from 10 samples from SDS patient bone marrow samples, including one patient with serial samples. There are two fastq files per sample.

  Dataset EGAD00001006799

• Whole genome sequencing generated from metastatic gliosarcoma patient samples

  This dataset contains whole genome sequencing data aligned to the b37 reference genome for 4 spatially and temporally distinct tumors from one patient with a matched normal blood sample.

  Dataset EGAD00001005745

• Lowpass whole genome sequencing of single circulating tumor cells (CTCs) in ALK-rearranged non-small-cell lung cancer resistant to ALK inhibitors

  Lowpass whole genome sequencing of 43 single CTCs and one tumor biopsy

  Dataset EGAD00001007700