A Gene Correlation Measurement Method for Spatial Transcriptome Data Based on Partitioning and Distribution.

Spatial transcriptome (ST) technology provides both the spatial location and transcriptional profile of spots, as well as tissue images. ST data can be utilized to construct gene regulatory networks, which can help identify gene modules that facilitate the understanding of biological processes such as cell communication. Correlation measurement is the core basis for constructing a gene regulatory network. However, due to the high noise and sparsity in ST data, common correlation measurement methods such as the Pearson correlation coefficient (PCC) and Spearman correlation coefficient (SPCC) are not suitable. In this work, a new gene correlation measurement method called STgcor is proposed. STgcor defines vertexes as spots in a two-dimensional coordinate plane consisting of axes X and Y from the gene pair (X and Y). The joint probability density of Gaussian distribution of the gene pair (X and Y) is calculated to identify and eliminate outliers. To overcome sparsity, the degree, trend, and location of the distribution of vertexes are used to measure the correlation between gene pairs (X, Y). To validate the performance of the STgcor method, it is compared with the PCC and SPCC in a weighted coexpression network analysis method using two ST datasets of breast cancer and prostate cancer. The gene modules identified by these methods are then compared and analyzed. The results show that the STgcor method detects some special gene modules and cancer-related pathways that cannot be detected by the other two methods.

Reduced airway microbiota diversity is associated with elevated allergic respiratory inflammation.

BACKGROUND: An increased prevalence of allergic disorders in developed countries has been associated with decreased exposure to environmental micro-organisms and an alteration of microbiota colonization. An appropriate model is needed to investigate the mechanisms by which hygiene environment-driven changes in microbiota could regulate allergic disorders. OBJECTIVE: To discover the correlation between the higher incidence and severity of allergies with the relative hygiene environment in a developed country. METHODS: Allergic respiratory inflammation was induced in specific pathogen-free and control rats by sensitization and challenge with ovalbumin. The diversity of lower airway bacteria community was analyzed by polymerase chain reaction denaturing gradient gel electrophoresis and sequencing before ovalbumin sensitization. Allergic respiratory inflammation resulting in cellular infiltrate was measured after the last challenge. RESULTS: The diversity of microbiota in the airway of specific pathogen-free rats decreased compared with the control rats; the more frequent microbiota in the control rats were Proteobacteria and Bacteroidetes. In addition, increased nasal rubbing and sneezing combined with exaggerated IgE production and leukocyte number was observed in ovalbumin-treated specific pathogen-free rats. CONCLUSION: These data indicate that the excessive "hygienic" environment resulted in a decreased bacterial diversity in the airway during infancy, leading to an increased susceptibility to allergic disease.