Single-cell RNA-sequencing (scRNA-seq) offers unparalleled insight into the transcriptional pro- grams of different cellular states by measuring the transcriptome of thousands individual cells. An emerging problem in the analysis of scRNA-seq is the inference of transcriptional gene regulatory net- works and a number of methods with different learning frameworks have been developed. Here we present a expanded benchmarking study of eleven recent network inference methods on six published single-cell RNA-sequencing datasets in human, mouse, and yeast considering different types of gold standard networks and evaluation metrics. We evaluate methods based on their computing requirements as well as on their ability to recover the network structure. We find that while no method is a universal winner and most methods have a modest recovery of experimentally derived interactions based on global metrics such as AUPR, methods are able to capture targets of regulators that are relevant to the system under study. Based on overall performance we grouped the methods into three main categories and found a combination of information-theoretic and regression-based methods to have a generally high perfor- mance. We also evaluate the utility of imputation for gene regulatory network inference and find that a small number of methods benefit from imputation, which further depends upon the dataset. Finally, comparisons to inferred networks for comparable bulk conditions showed that networks inferred from scRNA-seq datasets are often better or at par to those from bulk suggesting that scRNA-seq datasets can be a cost-effective way for gene regulatory network inference. Our analysis should be beneficial in selecting algorithms for performing network inference but also argues for improved methods and better gold standards for accurate assessment of regulatory network inference methods for mammalian systems.

No abstract

No abstract

t Due to the advent of technology, electronic equipments are much more sensitive to harmonic and its analysis play an important role whereby reducing the distortion due to harmonics needs attention. To meet the requirements of the industries, harmonic free-high rating power sources are in high demand. Total Harmonic Distortion (THD) is an indicator of AC voltage source quality. In case of inverters, one such way to reduce THD would be the use of Pulse Width Modulation (PWM). The existing methods mainly use the low frequency pulse width modulation techniques for the switching. Control methods employing high frequency switching techniques held in controlling THD with proper application of filters. This paper analyses THD in multilevel inverters using multicarrier PWM technique with five pulse width modulation technique through MATLAB simulations. Finally, a comparison is done to find the less harmonic generated PWM method using fewerfilters.