• step7:ssGSEA (single sample GSEA)was used to estimate pathway activities of the gastric cancer cell line in the Molecular Signature Database v3.1 (Msigdb v3.1) , . The pathway activities are represented in enrichment scores which were rank normalized to [0.0, 1.0].
  • Building a universal genomic signature predicting the intensity of FDG uptake in diverse metastatic tumors may allow us to understand better the biological processes underlying this phenomenon and their requirements of glucose uptake. A balanced training set (n = 71) of metastatic tumors including some of the most frequent histologies, with matched PET/CT quantification measurements and whole ...
  • I have a one gene expression input file (.gct) and one geneset (.gmt) file and need to run ssGSEA Input files and databases can be specified via Windows file dialogs that will be automatically invoked.
  • Plasmablastic lymphoma (PBL) is an aggressive B-cell non-Hodgkin lymphoma associated with immunodeficiency in the context of human immunodeficiency virus (HIV) infection or iatrogenic immunosuppression. While a rare disease in general, the incidence is dramatically increased in regions of the world with high HIV prevalence. The molecular pathogenesis of this disease is poorly characterized ...
  • do.signatures - this step runs a single-sample gene set enrichment analysis (ssGSEA) for a set of predefined signatures (see the object human.egc or mouse.egc). This step may also take long, and can be set to FALSE to shorten computation time. min.cells, npca and regress.out are all passed directly to Seurat to create a Seurat object.
  • Gene set enrichment analysis (GSEA) (also functional enrichment analysis) is a method to identify classes of genes or proteins that are over-represented in a large set of genes or proteins, and may have an association with disease phenotypes.
  • The function gsva in the homonym package from the R Bioconductor repository was used to compute ssGSEA scores, with “method=ssgsea” and default settings. The ssGSEA scores were calculated for each of the signatures (Barbie et al , 2009), in the 148 TCGA‐GBM samples as well as the Rheb1 fl/fl and Rheb1 Δ/Δ bulk GL261 tumours and TAM‐MG ...
  • Sep 05, 2018 · The ssGSEA method can be applied to an independent expression data set directly without recomputing a correlation matrix and the eigengenes. ... input to the gene co ...

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ssgsea.norm: Logical, set to TRUE (default) with method="ssgsea" runs the SSGSEA method from Barbie et al. (2009) normalizing the scores by the absolute difference between the minimum and the maximum, as described in their paper. When ssgsea.norm=FALSE this last normalization step is skipped. verbose: Gives information about each calculation step.
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By using the Player Input component any new input can be added by just swapping out the component and the rest of the code does not need to change. If your character is an AI agent then no input...
Jun 12, 2019 · The present study aimed to explore the mechanism by which the immune landscape of the tumor microenvironment influences bladder cancer. CIBERSORT and ssGSEA analyses revealed that M2 macrophages accounted for the highest proportion from 22 subsets of tumor‑infiltrating immune cells and were enriched in higher histologic grade and higher pathologic stage bladder cancer and ‘basal’ subtype ...

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Objective: The E3 ubiquitin ligase RNF6 (RING-finger protein 6) plays a crucial role in carcinogenesis. However, the copy number and expression of RNF6 were rarely reported in colorectal cancer. We aimed to explore the mechanical, biological, and clinical role of RNF6 in colorectal cancer initiation and progression. Design: The copy number and expression of RNF6 were analyzed from Tumorscape ...
Pancreatic ductal adenocarcinoma (PDAC) is the most lethal common malignancy, with little improvement in patient outcomes over the past decades. Recently, subtypes of pancreatic cancer with different prognoses have been elaborated; however, the inability to model these subtypes has precluded mechanistic investigation of their origins.