Selected article for: "seed gene and select seed gene"

Author: Courtney R. Sullivan; Catharine A. Mielnik; Sinead M. O’Donovan; Adam J. Funk; Eduard Bentea; Erica A.K. DePasquale; Zhexing Wen; Vahram Haroutunian; Pavel Katsel; Amy J. Ramsey; Jarek Meller; Robert E. McCullumsmith
Title: Connectivity analyses of bioenergetic changes in schizophrenia: Identification of novel treatments
  • Document date: 2018_6_5
  • ID: ltb6l5xz_21
    Snippet: For unsupervised clustering analyses, we used iLINCS to cluster the union of the top 50 differentially expressed L1000 genes from each of the 6 seed gene knockdown signatures using Pearson correlation coefficients (Figures 3 and 4) . Due to gene overlap between top 50 differentially expressed L1000 genes in seed gene knockdown signatures, this resulted in the clustering of expression data for 260 L1000 genes. We next used the dendrogram function .....
    Document: For unsupervised clustering analyses, we used iLINCS to cluster the union of the top 50 differentially expressed L1000 genes from each of the 6 seed gene knockdown signatures using Pearson correlation coefficients (Figures 3 and 4) . Due to gene overlap between top 50 differentially expressed L1000 genes in seed gene knockdown signatures, this resulted in the clustering of expression data for 260 L1000 genes. We next used the dendrogram function in iLINCS to select panels of mRNAs with increased expression across clustered seed gene knockdown signatures ("panels of clustered upregulated genes") and with decreased expression across clustered seed gene knockdown signatures ("panels of clustered downregulated genes").

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