Effect of hyperparameters on variable selection in random forests

Random forests (RFs) are well suited for prediction modeling and variable selection in high-dimensional omics studies. The effect of hyperparameters of the RF algorithm on prediction performance and variable importance estimation have previously been investigated. However, how hyperparameters impact RF-based variable selection remains unclear. We evaluate the effects on the Vita and the Boruta variable selection procedures based on two simulation studies utilizing theoretical distributions and empirical gene expression data. We assess the ability of the procedures to select important variables (sensitivity) while controlling the false discovery rate (FDR). Our results show that the proportion of splitting candidate variables (mtry.prop) and the sample fraction (sample.fraction) for the training dataset influence the selection procedures more than the drawing strategy of the training datasets and the minimal terminal node size. A suitable setting of the RF hyperparameters depends on the correlation structure in the data. For weakly correlated predictor variables, the default value of mtry is optimal, but smaller values of sample.fraction result in larger sensitivity. In contrast, the difference in sensitivity of the optimal compared to the default value of sample.fraction is negligible for strongly correlated predictor variables, whereas smaller values than the default are better in the other settings. In conclusion, the default values of the hyperparameters will not always be suitable for identifying important variables. Thus, adequate values differ depending on whether the aim of the study is optimizing prediction performance or variable selection.Comment: 18 pages, 2 figures + 2 figures in appendix, 3 table

Frequency and genotypic distribution of GB virus C (GBV-C) among Colombian population with Hepatitis B (HBV) or Hepatitis C (HCV) infection

<p>Abstract</p> <p>Background</p> <p>GB virus C (GBV-C) is an enveloped positive-sense ssRNA virus belonging to the <it>Flaviviridae </it>family. Studies on the genetic variability of the GBV-C reveals the existence of six genotypes: genotype 1 predominates in West Africa, genotype 2 in Europe and America, genotype 3 in Asia, genotype 4 in Southwest Asia, genotype 5 in South Africa and genotype 6 in Indonesia. The aim of this study was to determine the frequency and genotypic distribution of GBV-C in the Colombian population.</p> <p>Methods</p> <p>Two groups were analyzed: i) 408 Colombian blood donors infected with HCV (n = 250) and HBV (n = 158) from Bogotá and ii) 99 indigenous people with HBV infection from Leticia, Amazonas. A fragment of 344 bp from the 5' untranslated region (5' UTR) was amplified by nested RT PCR. Viral sequences were genotyped by phylogenetic analysis using reference sequences from each genotype obtained from GenBank (n = 160). Bayesian phylogenetic analyses were conducted using Markov chain Monte Carlo (MCMC) approach to obtain the MCC tree using BEAST v.1.5.3.</p> <p>Results</p> <p>Among blood donors, from 158 HBsAg positive samples, eight 5.06% (n = 8) were positive for GBV-C and from 250 anti-HCV positive samples, 3.2%(n = 8) were positive for GBV-C. Also, 7.7% (n = 7) GBV-C positive samples were found among indigenous people from Leticia. A phylogenetic analysis revealed the presence of the following GBV-C genotypes among blood donors: 2a (41.6%), 1 (33.3%), 3 (16.6%) and 2b (8.3%). All genotype 1 sequences were found in co-infection with HBV and 4/5 sequences genotype 2a were found in co-infection with HCV. All sequences from indigenous people from Leticia were classified as genotype 3. The presence of GBV-C infection was not correlated with the sex (p = 0.43), age (p = 0.38) or origin (p = 0.17).</p> <p>Conclusions</p> <p>It was found a high frequency of GBV-C genotype 1 and 2 in blood donors. The presence of genotype 3 in indigenous population was previously reported from Santa Marta region in Colombia and in native people from Venezuela and Bolivia. This fact may be correlated to the ancient movements of Asian people to South America a long time ago.</p

The African intellectuals’ project

Soon after taking the position of editor of IJARS at the beginning of 2019, I was contacted by the dean of Unisa’s College of Graduate Studies (CGS), Prof. Lindiwe Zungu, who informed me that the university’s principal and vice-chancellor, Prof. Mandla Makhanya, had decided to revive his project, the African Intellectuals’ Project (AIP). I was asked to coordinate this project, through which Makhanya sought to invite scholars, academics, and intellectuals, both on and outside of the African continent, to deliver presentations reflecting on the ills afflicting Africa and, at the same time, to offer possible solutions. In pursuing the AIP, Prof. Makhanya was carrying on a perennial tradition

Slavery and the Revival of Anti-slavery Activism

This chapter sets out the volumes critical approach to the dominant discourse on modern slavery and its impulse to question the assumptions and the politics behind that discourse. It explores the limits of the modern slavery rhetoric for understanding the complicated logics of agency, freedom and belonging, and of past, present and future, for those who are constituted as slaves. Document type: Part of book or chapter of boo