pyComBat, a Python tool for batch effects correction in high-throughput molecular data using empirical Bayes methods.

BACKGROUND: Variability in datasets is not only the product of biological processes: they are also the product of technical biases. ComBat and ComBat-Seq are among the most widely used tools for correcting those technical biases, called batch effects, in, respectively, microarray and RNA-Seq expression data. RESULTS: In this technical note, we present a new Python implementation of ComBat and ComBat-Seq. While the mathematical framework is strictly the same, we show here that our implementations: (i) have similar results in terms of batch effects correction; (ii) are as fast or faster than the original implementations in R and; (iii) offer new tools for the bioinformatics community to participate in its development. pyComBat is implemented in the Python language and is distributed under GPL-3.0 ( https://www.gnu.org/licenses/gpl-3.0.en.html ) license as a module of the inmoose package. Source code is available at https://github.com/epigenelabs/inmoose and Python package at https://pypi.org/project/inmoose . CONCLUSIONS: We present a new Python implementation of state-of-the-art tools ComBat and ComBat-Seq for the correction of batch effects in microarray and RNA-Seq data. This new implementation, based on the same mathematical frameworks as ComBat and ComBat-Seq, offers similar power for batch effect correction, at reduced computational cost.

A Minimal yet Flexible Likelihood Framework to Assess Correlated Evolution.

An evolutionary process is reflected in the sequence of changes of any trait (e.g., morphological or molecular) through time. Yet, a better understanding of evolution would be procured by characterizing correlated evolution, or when two or more evolutionary processes interact. Previously developed parametric methods often require significant computing time as they rely on the estimation of many parameters. Here, we propose a minimal likelihood framework modeling the joint evolution of two traits on a known phylogenetic tree. The type and strength of correlated evolution are characterized by a few parameters tuning mutation rates of each trait and interdependencies between these rates. The framework can be applied to study any discrete trait or character ranging from nucleotide substitution to gain or loss of a biological function. More specifically, it can be used to 1) test for independence between two evolutionary processes, 2) identify the type of interaction between them, and 3) estimate parameter values of the most likely model of interaction. In the current implementation, the method takes as input a phylogenetic tree with discrete evolutionary events mapped on its branches. The method then maximizes the likelihood for one or several chosen scenarios. The strengths and limits of the method, as well as its relative power compared to a few other methods, are assessed using both simulations and data from 16S rRNA sequences in a sample of 54 $\gamma$-enterobacteria. We show that, even with data sets of fewer than 100 species, the method performs well in parameter estimation and in evolutionary model selection. [Correlated evolution; maximum likelihood; model.].

Trends in bacterial bloodstream infections and resistance in immuno-compromised patients with febrile neutropenia: a retrospective analysis.

Bacterial infections remain a major cause of morbidity and mortality in immunocompromised children. From the onset of fever, an early administration of broad-spectrum antibiotics is begun; this strategy could induce emergence of multi-drug resistant bacteria (MDR). We describe the incidence and microbiological spectrum, including MDR bacteria of bacterial documented blood-stream infections (BSI) in immunocompromised children. A retrospective, descriptive study was conducted in a tertiary referral centre in France from January 2014 to December 2017. Our cohort included a large scale of patients with febrile neutropenia: haematological and oncological malignancies, haematopoietic stem cell transplantations, severe combined immunodeficiency syndromes. BSI were defined by positive blood culture samples associated with fever. Among 760 febrile neutropenia episodes in 7301 admitted patients, we identified 310 documented BSI with a mean of 7.4 BSI/1000 patient bed days. Only 2.9% BSIs were caused by MDR bacteria, none vancomycin resistant. Coagulase-negative staphylococci were identified in 49.7% BSI and Staphylococcus aureus caused 6.5% infections. Gram-negative bacilli accounted for 21.6% of isolated bacteria, Pseudomonas for 4.8%. The incidence of BSI annually decreased by 0.75% (p = 0.002).Conclusion: With a step-down strategy at 48 h of initial broad-spectrum antibiotic therapy, we reported a low number of MDR bacteria, no deaths related to BSI. What is Known: • Bacterial bloodstream infections are a leading cause of morbidity and mortality in immunocompromised children • Multi-drug resistant bacteria are emerging worldwide. What is New: • Initial broad-spectrum antibiotic therapy with a step-down strategy at 48 h: no deaths related to bloodstream infections with a low number of resistant bacteria. • Parental and nurse stewardship to decrease bloodstream infections incidence with a drop of staphylococcal infections.

Fundamental properties of the mammalian innate immune system revealed by multispecies comparison of type I interferon responses.

The host innate immune response mediated by type I interferon (IFN) and the resulting up-regulation of hundreds of interferon-stimulated genes (ISGs) provide an immediate barrier to virus infection. Studies of the type I 'interferome' have mainly been carried out at a single species level, often lacking the power necessary to understand key evolutionary features of this pathway. Here, using a single experimental platform, we determined the properties of the interferomes of multiple vertebrate species and developed a webserver to mine the dataset. This approach revealed a conserved 'core' of 62 ISGs, including genes not previously associated with IFN, underscoring the ancestral functions associated with this antiviral host response. We show that gene expansion contributes to the evolution of the IFN system and that interferomes are shaped by lineage-specific pressures. Consequently, each mammal possesses a unique repertoire of ISGs, including genes common to all mammals and others unique to their specific species or phylogenetic lineages. An analysis of genes commonly down-regulated by IFN suggests that epigenetic regulation of transcription is a fundamental aspect of the IFN response. Our study provides a resource for the scientific community highlighting key paradigms of the type I IFN response.

Transmission ecology of canine parvovirus in a multi-host, multi-pathogen system.

Understanding multi-host pathogen maintenance and transmission dynamics is critical for disease control. However, transmission dynamics remain enigmatic largely because they are difficult to observe directly, particularly in wildlife. Here, we investigate the transmission dynamics of canine parvovirus (CPV) using state-space modelling of 20 years of CPV serology data from domestic dogs and African lions in the Serengeti ecosystem. We show that, although vaccination reduces the probability of infection in dogs, and despite indirect enhancement of population seropositivity as a result of vaccine shedding, the vaccination coverage achieved has been insufficient to prevent CPV from becoming widespread. CPV is maintained by the dog population and has become endemic with approximately 3.5-year cycles and prevalence reaching approximately 80%. While the estimated prevalence in lions is lower, peaks of infection consistently follow those in dogs. Dogs exposed to CPV are also more likely to become infected with a second multi-host pathogen, canine distemper virus. However, vaccination can weaken this coupling, raising questions about the value of monovalent versus polyvalent vaccines against these two pathogens. Our findings highlight the need to consider both pathogen- and host-level community interactions when seeking to understand the dynamics of multi-host pathogens and their implications for conservation, disease surveillance and control programmes.

Testing for Independence between Evolutionary Processes.

Evolutionary events co-occurring along phylogenetic trees usually point to complex adaptive phenomena, sometimes implicating epistasis. While a number of methods have been developed to account for co-occurrence of events on the same internal or external branch of an evolutionary tree, there is a need to account for the larger diversity of possible relative positions of events in a tree. Here we propose a method to quantify to what extent two or more evolutionary events are associated on a phylogenetic tree. The method is applicable to any discrete character, like substitutions within a coding sequence or gains/losses of a biological function. Our method uses a general approach to statistically test for significant associations between events along the tree, which encompasses both events inseparable on the same branch, and events genealogically ordered on different branches. It assumes that the phylogeny and themapping of branches is known without errors. We address this problem from the statistical viewpoint by a linear algebra representation of the localization of the evolutionary events on the tree.We compute the full probability distribution of the number of paired events occurring in the same branch or in different branches of the tree, under a null model of independence where each type of event occurs at a constant rate uniformly inthephylogenetic tree. The strengths andweaknesses of themethodare assessed via simulations;we then apply the method to explore the loss of cell motility in intracellular pathogens.

We are what we eat, plus some per mill: Using stable isotopes to estimate diet composition in Gyps vultures over space and time.

Dietary studies in birds of prey involve direct observation and examination of food remains at resting and nesting sites. Although these methods accurately identify diet in raptors, they are time-consuming, resource-intensive, and associated with biases from the feeding ecology of raptors like Gyps vultures. Our study set out to estimate diet composition in Gyps vultures informed by stable isotopes that provide a good representation of assimilated diet from local systems.We hypothesized that differences in Gyps vulture diet composition is a function of sampling location and that these vultures move between Serengeti National Park and Selous Game Reserve to forage. We also theorized that grazing ungulates are the principal items in Gyps vulture diet.Through combined linear and Bayesian modeling, diet derived from δ13C in Gyps vultures consisted of grazing herbivores across sites, with those in Serengeti National Park consuming higher proportions of grazing herbivores (>87%). δ13C differences in vulture feather subsets did not indicate shifts in vulture diet and combined with blood δ13C, vultures fed largely on grazers for ~159 days before they were sampled. Similarly, δ15N values indicated Gyps vultures fed largely on herbivores. δ34S ratios separated where vultures fed when the two sites were compared. δ34S variation in vultures across sites resulted from baseline differences in plant δ34S values, though it is not possible to match δ34S to specific locations.Our findings highlight the relevance of repeated sampling that considers tissues with varying isotopic turnover and emerging Bayesian techniques for dietary studies using stable isotopes. Findings also suggested limited vulture movement between the two local systems. However, more sampling coupled with environmental data is required to fully comprehend this observation and its implications to Gyps vulture ecology and conservation.

Predicting the presence and titre of rabies virus-neutralizing antibodies from low-volume serum samples in low-containment facilities.

Serology is a core component of the surveillance and management of viral zoonoses. Virus neutralization tests are a gold standard serological diagnostic, but requirements for large volumes of serum and high biosafety containment can limit widespread use. Here, focusing on Rabies lyssavirus, a globally important zoonosis, we developed a pseudotype micro-neutralization rapid fluorescent focus inhibition test (pmRFFIT) that overcomes these limitations. Specifically, we adapted an existing micro-neutralization test to use a green fluorescent protein-tagged murine leukaemia virus pseudotype in lieu of pathogenic rabies virus, reducing the need for specialized reagents for antigen detection and enabling use in low-containment laboratories. We further used statistical models to generate rapid, quantitative predictions of the probability and titre of rabies virus-neutralizing antibodies from microscopic imaging of neutralization outcomes. Using 47 serum samples from domestic dogs with neutralizing antibody titres estimated using the fluorescent antibody virus neutralization test (FAVN), pmRFFIT showed moderate sensitivity (78.79%) and high specificity (84.62%). Despite small conflicts, titre predictions were correlated across tests repeated on different dates both for dog samples (r = 0.93) and in a second data set of sera from wild common vampire bats (r = 0.72, N = 41), indicating repeatability. Our test uses a starting volume of 3.5 µl of serum, estimates titres from a single dilution of serum rather than requiring multiple dilutions and end point titration, and may be adapted to target neutralizing antibodies against alternative lyssavirus species. The pmRFFIT enables high-throughput detection of rabies virus-neutralizing antibodies in low-biocontainment settings and is suited to studies in wild or captive animals where large serum volumes cannot be obtained.

MicNeSs: genotyping microsatellite loci from a collection of (NGS) reads.

Microsatellites are widely used in population genetics to uncover recent evolutionary events. They are typically genotyped using capillary sequencer, which capacity is usually limited to 9, at most 12 loci for each run, and which analysis is a tedious task that is performed by hand. With the rise of next-generation sequencing (NGS), a much larger number of loci and individuals are available from sequencing: for example, on a single run of a GS Junior, 28 loci from 96 individuals are sequenced with a 30X cover. We have developed an algorithm to automatically and efficiently genotype microsatellites from a collection of reads sorted by individual (e.g. specific PCR amplifications of a locus or a collection of reads that encompass a locus of interest). As the sequencing and the PCR amplification introduce artefactual insertions or deletions, the set of reads from a single microsatellite allele shows several length variants. The algorithm infers, without alignment, the true unknown allele(s) of each individual from the observed distributions of microsatellites length of all individuals. MicNeSs, a python implementation of the algorithm, can be used to genotype any microsatellite locus from any organism and has been tested on 454 pyrosequencing data of several loci from fruit flies (a model species) and red deers (a nonmodel species). Without any parallelization, it automatically genotypes 22 loci from 441 individuals in 11 hours on a standard computer. The comparison of MicNeSs inferences to the standard method shows an excellent agreement, with some differences illustrating the pros and cons of both methods.