15038 results for "cancer studies using rna-seq"

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• CNA vcf files for CPCG Subclonal Heterogeneity in multiple and single regions

  CNA calls generated using the MuTect-Battenberg-PhyloWGS from the CPC-GENE Subclonal Heterogeneity study using single and multiple regions

  Dataset EGAD00001004443

• SNV vcf files for CPCG Subclonal Heterogeneity in multiple and single regions

  SNV calls generated using the SomaticSniper-Battenberg-PhyloWGS from the CPC-GENE Subclonal Heterogeneity study using single and multiple regions

  Dataset EGAD00001004432

• CNA vcf files for CPCG Subclonal Heterogeneity in multiple and single regions

  CNA calls generated using the MuTect-TITAN-PhyloWGS from the CPC-GENE Subclonal Heterogeneity study using single and multiple regions

  Dataset EGAD00001004442

• SNV vcf files for CPCG Subclonal Heterogeneity in multiple and single regions

  SNV calls generated using the SomaticSniper-TITAN-PhyloWGS from the CPC-GENE Subclonal Heterogeneity study using single and multiple regions

  Dataset EGAD00001004431

• CNA vcf files for CPCG Subclonal Heterogeneity in multiple and single regions

  CNA calls generated using the SomaticSniper-TITAN-PhyloWGS from the CPC-GENE Subclonal Heterogeneity study using single and multiple regions

  Dataset EGAD00001004441

• Primary plasma cell leukemia genomic abnormalities

  Primary plasma cell leukemia (pPCL) samples were sequenced using the Nimblegen MedExome Plus hybridization capture to detect translocations, copy number changes, and mutations in 20 pPCL samples and patient matched controls. Sequencing was performed on a NextSeq500 using 75 bp paired end reads.

  Dataset EGAD00001004323

• SNV vcf files for CPCG Subclonal Heterogeneity in multiple and single regions

  SNV calls generated using the MuTect-TITAN-PhyloWGS from the CPC-GENE Subclonal Heterogeneity study using single and multiple regions

  Dataset EGAD00001004433

• Capture-based NGS

  Capture-based NGS obtained using the "all-CLL" panel (also known as SOPHiA DDM (TM) Community CLL Clonality Solution). Library preparation was performed following SOPHiA GENETICS recommendations using 200 ng genomic DNA. Libraries were sequenced on a MiSeq instrument (2x300 bp, Illumina) aiming at a mean coverage of 1,000x.

  Dataset EGAD00001011151

• Validation of Gene Array to Predict Bacterial Co-infection In Adults Hospitalized with Viral Lower Respiratory Tract Infections (LRTI)

  Accurate tests for microbiologic diagnosis of lower respiratory tract infections (LRTI) are needed. Gene expression profiling of whole blood represents a powerful new approach for analysis of the host response during respiratory infection that can be used to supplement pathogen detection testing. Using qPCR, we prospectively validated the differential expression of 10 genes previously shown to discriminate bacterial and non-bacterial LRTI confirming the utility of this approach. In addition, a novel approach using RNAseq analysis identified 141 genes differentially expressed in LRTI subjects with bacterial infection. Using "pathway-informed" dimension reduction, we identified a novel 11 gene set (selected from lymphocyte, α-linoleic acid metabolism, and IGF regulation pathways) and demonstrated a predictive accuracy for bacterial LRTI (nested CV-AUC=0.87). RNAseq represents a new and an unbiased tool to evaluate host gene expression for the diagnosis of LRTI.

  Study phs001248

• NIDDK International IBD Genetics Consortium Repository Global Screening Array

  The purpose of this GWAS meta-analysis is to assess IBD risk alleles using data collected by members of the International IBD Genetics Consortium and their collaborators around the world. Data from over 30 cohorts have been identified and are being combined for analysis. Genotyping has been conducted using a variety of chips with most samples genotyped using GSAMD-24v1-0 or GSA-CHO-Custom. Individual level genotype data will be made available whenever possible (some groups are only able to provide summary statistics due to institutional and/or governmental restrictions on data sharing), together with information on sex, self-reported ancestry, IBD affection status and diagnosis. This first batch includes data from North American sites who are members of the NIDDK-funded IBD Genetics Consortium. Additional data will be provided in an update as soon as they have gone through the QC process.

  Study phs002336