Biology subjects

Le Clercq, L. S.

Publications and source records attributed to Le Clercq, L. S..

2 recordsLinked to original sources

bioRxiv2023

ABCal: a Python package for Author Bias Computation and Scientometric Plotting for Reviews and Meta-Analyses

Systematic reviews are critical summaries of the exiting literature on a given subject and, when combined with meta-analysis, provides a quantitative synthesis of evidence to direct and inform future research. Such reviews must, however, account for complex sources of between study heterogeneity and possible sources of bias, such as publication bias. This paper presents the methods and results of a research study using a newly developed software tool called ABCal (version 1.0.2) to compute and assess author bias in the literature, providing a quantitative measure for the possible effect of overrepresented authors introducing bias to the overall interpretation of the literature. ABCal includes a new metric referred to as author bias, which is a measure of potential biases per paper when the frequency or proportions of contributions from specific authors are considered. The metric is able to account for a significant portion of the observed heterogeneity between studies included in meta-analyses. A meta-regression between observed effect measures and author bias values revealed that higher levels of author bias were associated with higher effect measures while lower author bias was evident for studies with lower effect measures. Furthermore, the softwares capabilities to analyse authorship contributions and produce scientometric plots was able to reveal distinct patterns in both the temporal and geographic distributions of publications, which may relate to any evident publication bias. Thus, ABCal can aid researchers in gaining a deeper understanding of the research landscape and assist in identifying both key contributors and holistic research trends.

scientific communication and education↗

bioRxiv2023

Intra-host quasispecies reconstructions resemble inter-host variability of transmitted chronic hepatitis B virus strains

The hepatitis B virus is a partially double stranded DNA virus in the Hepadnaviridae family of viruses that infect the liver cells of vertebrates including humans. The virus replicates through the reverse transcription of an RNA intermediate by a viral poly-merase, akin to retroviruses. The viral polymerase has high replication capacity but low fidelity and no proofreading activity resulting in a high mutation rate. This contributes to the emergence of a cloud of mutants or quasispecies within host systems during infection. Several host and viral factors have been identified that contribute to mutations and mutation frequency in shaping viral evolution, however, because the dynamics of viral evolution cannot be understood from the fittest strain alone, the need exists to sequence and reconstruct intra-host diversity, recently made possible through next generation sequencing. Due to the extensive pipeline of bioinformatic analyses associated with next generation sequencing studies are needed to ascertain if quasispecies reconstruction methods and diversity measures accurately model known diversity. Here, next generation sequencing and various quasispecies reconstruction methods are used to model the natural evolution of viral populations across the full genome of hepatitis B virus strains from South Africa. This study illustrates that (i) different methods of quasispecies reconstruction reconstruct the same amount of diversity, (ii) intra-host diversity derived from full quasispecies analyses re-sembles diversity measures obtained from previous methods, (iii) inter-host diversity resembles the diversity between closely related quasispecies variants, (iv) diversity is increased in HIV-negative individuals, and (v) corroborate that seroconversion of HBV biomarkers increases mutation rates.

molecular biology↗