14676 results for "PLOS+ONE+Pennsylvania+German+ACS+language+code+pdc+open+access+study"

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• The transcriptomic response of skeletal muscle in life-long high-level trained and untrained men and women after acute exercise

  To investigate the influence of lifelong exercise training on the response of skeletal muscle to a bout of acute exercise we generated global transcriptomic data from long-term endurance (8 men, 8 women) and strength (8 men, 8 women) trained individuals and healthy age-matched untrained controls (8 men, 8 women). Skeletal muscle biopsies were taken from M. vastus lateralis before, directly after, and after 1h and 3hrs following acute exercise. All subjects completed one bout of acute endurance exercise and one bout of acute resistance exercise, separated by 4-8 weeks. All 384 samples were multiplexed in 4 lanes and sequenced (2x250bp paired end) on the Illumina NovaSeq 6000.

  Dataset EGAD00001008663

• Reading about genomic analysis of pan-neuroblastoma

  There are virtually no research fields that do not benefit from the large-scale genomic analysis that are so popular nowadays. For research into diseases with highly diverse clinical behavior like pediatric neuroblastoma, nevertheless, this type of approach has been a game-changer. Samuel W. Brady and colleagues, from St. Jude Children’s Research Hospital in Memphis, have gathered data from 702 neuroblastomas which were profiled by whole genome sequencing (WGS, n = 205), whole exome sequencing (WES, n = 539), and/or RNA-Seq. Less than half of the samples were generated during this study, while the others were obtained from previous work. Part of the WES data was indeed deposited in EGA in 2012 (EGA study EGAS00001000213). A scratchy summary about the huge work from Samuel W. Brady and colleagues, published in Nature Communications this October 2020 “These findings suggest that the sympathetic nervous system, the tissue from which neuroblastoma arises, is susceptible to different oncogenic insults at different times during development, which could be explored in future investigations using animal models.” Conclude the authors, highlighting the importance of their findings. Pediatric neuroblastomas are classified according to clinical and molecular features into low, intermediate, and high risk. Age plays a critical role in the classification, with younger children having an overall better prognosis. The samples included in this study belonged to all ages and risk-groups: the aim of such set up is the identification of age-associated molecular aberrations. The authors defined a mutational landscape of pediatric neuroblastoma including rare driver events, impossible to pick with a smaller data set. Interestingly, most driver mutations' frequency was found to be age-related. Those include alterations on MYCN, TERT, PTPRD, and Ras pathway, in addition to the previously reported ATRX. In addition, the large data set allowed the authors to define co-existence relations between the mutations (mutual exclusion or co-occurrence) which is a crucial puzzle piece to unravel the mechanisms driving the pathogenesis. Enjoy this really interesting article, open source on Pubmed.

  Blog genomic-analysis-of-pan-neuroblastoma

• Picuris Pueblo Genomic Project (Modern Data)

  Data Access Committee for the present-day dataset of the project "Picuris Pueblo oral history and genomics reveal continuity in US Southwest".

  Dac EGAC50000000526

• Chun Lab DAC

  Data Access Committee (DAC) for datasets produced by the Chun Lab @ Sanford Burnham Prebys Medical Discovery Institute in La Jolla, California.

  Dac EGAC50000000011

• NGS-based monitoring of the T cell receptor repertoire in living donor kidney transplant patients undergoing combination cell therapy

  PBMCs from six kidney transplant recipients receiving as part of the Trex001 study autologous Tregs and donor bone marrow and six control patients not receiving either of the two treatments were collected pre-transplant and at one, three and six month post-transplant. Donor reactive T-cells were identified by mixed lymphocyte reactions (MLR) and lineage specific T-cell receptor (TCR) repertoires of native T-cells and proliferating and non-proliferating T-cells from MLRs were determined by next generation sequencing based profiling of the TCR.

  Dataset EGAD50000000302

• DAC for Breast Invasive Lobular Carcinoma CDH1 study

  We developed an artificial intelligence (AI)-model applied to histological images trained using CDH1 biallelic mutations, pathognomonic for breast invasive lobular carcinoma (ILC), as ground truth. We evaluated the performance of the AI-model to predict the presence of CDH1 biallelic mutations and to diagnose ILC. Subsequently, we investigated the molecular underpinning of cases predicted by the model to harbor a CDH1 biallelic mutations but lacking these alterations according to targeted sequencing. We then subjected one ILC lacking CDH1 biallelic mutations and lacking CDH1 promoter methylation to whole genome sequencing (WGS) to determine the molecular basis of its lobular phenotype.

  Dac EGAC50000000333

• WGS data subfolder HFG3FCCXY from multifocal ileal NETs study

  This dataset includes linked-read whole-genome sequencing data (subfolder HFG3FCCXY) for multifocal ileal tumor samples from one patient. Samples were sequenced using the 10x Genomics linked-read whole-genome sequencing (WGS) approach.

  Dataset EGAD00001008496

• WGS data subfolder HF3FKCCXY from multifocal ileal NETs study

  This dataset includes linked-read whole-genome sequencing data (subfolder HF3FKCCXY) for multifocal ileal tumor samples from one patient. Samples were sequenced using the 10x Genomics linked-read whole-genome sequencing (WGS) approach.

  Dataset EGAD00001008492

• Long-read mRNA sequencing of retinal organoids

  Long-read (PacBio) sequencing of two retinal organoid samples. One sample was treated with cyclohexamide. Files are ccs BAM format files generated by a Sequel IIe machine.

  Dataset EGAD50000000100

• ATAC Dataset for 19 T-ALL patient samples and 1 normal control sample

  19 ATAC-seq from T-ALL patient samples and one healthy normal control sample. Reads were aligned to HG38 reference

  Dataset EGAD50000000024