Identification of significant gene expression changes in multiple perturbation experiments using knockoffs.

Large-scale multiple perturbation experiments have the potential to reveal a more detailed understanding of the molecular pathways that respond to genetic and environmental changes. A key question in these studies is which gene expression changes are important for the response to the perturbation. This problem is challenging because (i) the functional form of the nonlinear relationship between gene expression and the perturbation is unknown and (ii) identification of the most important genes is a high-dimensional variable selection problem. To deal with these challenges, we present here a method based on the model-X knockoffs framework and Deep Neural Networks to identify significant gene expression changes in multiple perturbation experiments. This approach makes no assumptions on the functional form of the dependence between the responses and the perturbations and it enjoys finite sample false discovery rate control for the selected set of important gene expression responses. We apply this approach to the Library of Integrated Network-Based Cellular Signature data sets which is a National Institutes of Health Common Fund program that catalogs how human cells globally respond to chemical, genetic and disease perturbations. We identified important genes whose expression is directly modulated in response to perturbation with anthracycline, vorinostat, trichostatin-a, geldanamycin and sirolimus. We compare the set of important genes that respond to these small molecules to identify co-responsive pathways. Identification of which genes respond to specific perturbation stressors can provide better understanding of the underlying mechanisms of disease and advance the identification of new drug targets.

SCSIM: Jointly simulating correlated single-cell and bulk next-generation DNA sequencing data.

BACKGROUND: Recently, it has become possible to collect next-generation DNA sequencing data sets that are composed of multiple samples from multiple biological units where each of these samples may be from a single cell or bulk tissue. Yet, there does not yet exist a tool for simulating DNA sequencing data from such a nested sampling arrangement with single-cell and bulk samples so that developers of analysis methods can assess accuracy and precision. RESULTS: We have developed a tool that simulates DNA sequencing data from hierarchically grouped (correlated) samples where each sample is designated bulk or single-cell. Our tool uses a simple configuration file to define the experimental arrangement and can be integrated into software pipelines for testing of variant callers or other genomic tools. CONCLUSIONS: The DNA sequencing data generated by our simulator is representative of real data and integrates seamlessly with standard downstream analysis tools.

Prevalence of dental caries among school children of Bharatpur city, India.

BACKGROUND: Healthy teeth and oral tissues and the need for oral health care are important for any section of society. Dental caries is an infectious microbial disease of multifactorial origin in which diet, host, and microbial flora interacts over a period of time in such a way so as to encourage demineralization of the tooth enamel with resultant caries formation. Dental caries, the product of man's progress towards civilization, has a very high morbidity potential and thus, is coming into focus of the mankind. AIMS AND OBJECTIVES: To assess the prevalence of dental caries among 12-15 year old government and private school children of Bharatpur city. MATERIALS AND METHODS: This was a cross-sectional study carried out on total 1400 school children, of which 700 school children were from government schools and 700 were from private schools. Simple random sampling methodology was used to select the sample. The subjects were examined for dental caries according to WHO 1997 assessment form. Significant Caries Index was also used to assess the prevalence of dental caries. RESULTS: The prevalence of dental caries was found higher among government school children, that is, 53%, when compared to private school children, that is, 47% and this difference was found to be statistically significant. The mean decayed, missing, and filled teeth were found to be higher in government school children (7.61 ± 2.86) as compared to private school children (4.76 ± 2.42). CONCLUSION: Dental caries was found to be the major public health problems among both the government and private school children of Bharatpur city, which need immediate attention. Regular dental checkups and practice of routine oral hygiene procedures will enable them to lead a healthier life.