14666 results for "PLOS+ONE+Pennsylvania+German+ACS+language+code+pdc+open+access+study"

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• Idiopathic Collapsing Glomerulopathy in Brazilian patients

  Collapsing glomerulopathy is a severe kidney disease that often leads to chronic dialysis or kidney transplantation. To expand its understanding, we performed a broad clinical and genetic analysis of a highly admixed patient population with idiopathic collapsing glomerulopathy.

  Study EGAS50000000064

• WES data from tumors and matching controls collected from 11 UTSW translocation renal cell carcinoma (tRCC) patients.

  This study investigates translocation renal cell carcinoma (tRCC) to identify mutations contributing to tRCC progression. The analysis relies on Whole Exome Sequencing (WES) data obtained from 11 patients treated at University of Texas Southwestern Medical Center (UTSW) affiliated hospitals, including Parkland Hospital and Children’s Medical Center. Tumor samples and their corresponding normal DNA were sequenced using the Illumina platform.

  Dataset EGAD50000000171

• Cityscape Serum peptide Mass Spec data

  Matrix of counts from the serum peptide mass spec data from patients enrolled in the CITYSCAPE trial, and the sample annotation. Specifically, serum samples at C1D1, C2D1, C3D1, SCRN were collected from a total of 132 patients and subject to Mass Spec at Biognosys. The current study focused on patients who have samples at both C1D1 and C2D1 (n = 64 pairs). Associated metadata also included.

  Dataset EGAD50000000369

• RNAseq of preneoplasia lung adenocarcinoma

  RNA sequencing of 168 pulmonary samples including lung preneoplasia atypical adenomatous hyperplasia (AAH, N=38), adenocarcinoma in situ (AIS, N=22), minimally invasive adenocarcinoma (MIA, N=19) and invasive lung adenocarcinoma (ADC, N=38) and adjacent lung tissues (Normal, N=62).

  Study EGAS50000000271

• Blood Handling and Leukocyte Isolation Methods Impact the Global Transcriptome of Immune Cells

  In order to characterize the effects of upstream sample handling on the transcriptome of isolated leukocyte populations, we simulated various sample handling methods on whole blood prior to leukocyte isolation for low-input RNA-sequencing.

  Study phs001563

• Advanced Genomic Techniques in Sequencing of Colorectal Cancer

  We developed a method that uses allelic imbalance information in combination with phased genomic sequencing to generate mega-haplotypes that can encompass entire chromosome arms. We applied this technique to characterize aneuploidy and chromosomal alterations in colorectal cancers.

  Study phs001400

• Large Cancer Fingerprint Screening for Detection of Minimal Residual Disease.

  We describe an approach for large cancer fingerprint screening and its application to cell-free DNA from patients with cancer. Our approach involves tracking somatic mutations identified from patients' tumor biopsies, in the cell-free DNA from a blood draw.

  Study phs001977

• Molecular Characterization of Germ Cell Tumors

  We performed comprehensive molecular profiling of germ cell tumors, including whole exome sequencing and transcriptome sequencing, derived from patient samples. This project additionally explores mechanisms of chemosensivity in these patients, as well as mechanisms of tumor evolution in the context of treatment.

  Study phs000923

• miRNA Profiling of Maternal and Non-Maternal Healthy Adult Blood Plasma Using Small RNA-Sequencing

  We compared several performance characteristics of four miRNA profiling methods: small RNA-sequencing, HTG EdgeSeq, Abcam FirePlex, and NanoString nCounter. We used pools of synthetic miRNAs and extracellular RNA from healthy individuals to assess these characteristics.

  Study phs001892

• Whole Exome Sequencing of Parathyroid Cancer Identifies Candidate Driver Mutations and Core Pathways

  Here we performed genomic characterization of twenty-nine sporadic parathyroid cancers using next generation whole exome sequencing. Thirty-three novel candidate driver genes for sporadic parathyroid cancer were proposed, in addition to previously known driver genes CDC73 and MEN1.

  Study phs001765