Mining, visualizing and comparing multidimensional biomolecular data using the Genomics Data Miner (GMine) Web-Server

Abstract

Genomics Data Miner (GMine) is a user-friendly online software that allows non-experts to mine, cluster and compare multidimensional biomolecular datasets. Various powerful visualization techniques are provided, generating high quality figures that can be directly incorporated into scientific publications. Robust and comprehensive analyses are provided via a broad range of data-mining techniques, including univariate and multivariate statistical analysis, supervised learning, correlation networks, clustering and multivariable regression. The software has a focus on multivariate techniques, which can attribute variance in the measurements to multiple explanatory variables and confounders. Various normalization methods are provided. Extensive help pages and a tutorial are available via a wiki server. Using GMine we reanalyzed proteome microarray data of host antibody response against Plasmodium falciparum. Our results support the hypothesis that immunity to malaria is a higher-order phenomenon related to a pattern of responses and not attributable to any single antigen. We also analyzed gene expression across resting and activated T cells, identifying many immune-related genes with differential expression. This highlights both the plasticity of T cells and the operation of a hardwired activation program. These application examples demonstrate that GMine facilitates an accurate and in-depth analysis of complex molecular datasets, including genomics, transcriptomics and proteomics data.

The immune checkpoint CD96 defines a distinct lymphocyte phenotype and is highly expressed on tumor‐infiltrating T cells

“…CCA was not statistically significant between populations and, compared with ex vivo profiling, fewer genes were differentially expressed between CD96 high and CD96 low T‐cells postactivation, suggesting that the populations become more homogeneous after a strong activation signal. We have previously observed this “blending” phenotype when examining CD8 + and CD4 + human T‐cell lineages post‐T cell receptor (TCR) activation . Nonetheless, important functional genes were differentially expressed during activation including a strong downregulation of the protein tyrosine phosphatase CD45RA in CD96 high cells ( P = 0.0005) and upregulation of the pleotropic cytokine IL23A ( P = 0.02) (Figure c).…”

“…Significant, differentially expressed genes between populations are shown (Supplemental tables 2 & 3). CCA for CD 8 + T cells (a) and CD 4 + T cells (b) were determined using the Gmine software . (c) CD 96 high and CD 96 low cells were sorted from effector memory ( CD 45 RA − / CCR 7 − ) CD 8 + T cells from five donors and stimulated with phorbol myristate acetate/ionomycin for 4 h. To determine differences in functional output, we used log2 of the fold change following activation between CD 96 high and CD 96 low CD 8 + T cells.…”

“…Following hybridization, samples were purified using an nCounter Prep Station before quantification with the nCounter Digital Analyzer. Multivariate analysis and network analysis were conducted using GraphPad PRISM (GraphPad software) and GMine software …”

“…We have previously observed this "blending" phenotype when examining CD8 + and CD4 + human T-cell lineages post-T cell receptor (TCR) activation. 12 Nonetheless, important functional genes were differentially expressed during activation including a strong downregulation of the protein tyrosine phosphatase CD45RA in CD96 high cells (P = 0.0005) and upregulation of the pleotropic cytokine IL23A (P = 0.02) ( Figure 3c). Likewise, activated CD96 low T cells showed strong downregulation of the effector molecule granzyme M (GZMM) (P = 0.012) and immune checkpoint CTLA-4 (P = 0.037) postactivation ( Figure 3c).…”

Dichotomous miR expression and immune responses following primary blood-stage malaria

“…Expression of 135 immune-related genes known to be involved in T cell and B cell responses was assessed using a custom 135-plex nCounter custom codeset of genes involved in immune recognition, survival, migration, adhesion, cytokine/chemokine secretion, activation, differentiation, and exhaustion, as reported previously (38). nCounter codeset hybridization was performed as per manufacturer's instructions using 100 ng of total RNA from the same samples assayed for miR expression (above).…”