ISoLDE: a data-driven statistical method for the inference of allelic imbalance in datasets with reciprocal crosses.

MOTIVATION: Allelic imbalance (AI), i.e. the unequal expression of the alleles of the same gene in a single cell, affects a subset of genes in diploid organisms. One prominent example of AI is parental genomic imprinting, which results in parent-of-origin-dependent, mono-allelic expression of a limited number of genes in metatherian and eutherian mammals and in angiosperms. Currently available methods for identifying AI rely on data modeling and come with the associated limitations. RESULTS: We have designed ISoLDE (Integrative Statistics of alleLe Dependent Expression), a novel nonparametric statistical method that takes into account both AI and the characteristics of RNA-seq data to infer allelic expression bias when at least two biological replicates are available for reciprocal crosses. ISoLDE learns the distribution of a specific test statistic from the data and calls genes 'allelically imbalanced', 'bi-allelically expressed' or 'undetermined'. Depending on the number of replicates, predefined thresholds or permutations are used to make calls. We benchmarked ISoLDE against published methods, and showed that ISoLDE compared favorably with respect to sensitivity, specificity and robustness to the number of replicates. Using ISoLDE on different RNA-seq datasets generated from hybrid mouse tissues, we did not discover novel imprinted genes (IGs), confirming the most conservative estimations of IG number. AVAILABILITY AND IMPLEMENTATION: ISoLDE has been implemented as a Bioconductor package available at http://bioconductor.org/packages/ISoLDE/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Valine/isoleucine variants drive selective pressure in the VP1 sequence of EV-A71 enteroviruses.

BACKGROUND: In 2011-2012, Northern Vietnam experienced its first large scale hand foot and mouth disease (HFMD) epidemic. In 2011, a major HFMD epidemic was also reported in South Vietnam with fatal cases. This 2011-2012 outbreak was the first one to occur in North Vietnam providing grounds to study the etiology, origin and dynamic of the disease. We report here the analysis of the VP1 gene of strains isolated throughout North Vietnam during the 2011-2012 outbreak and before. METHODS: The VP1 gene of 106 EV-A71 isolates from North Vietnam and 2 from Central Vietnam were sequenced. Sequence alignments were analyzed at the nucleic acid and protein level. Gene polymorphism was also analyzed. A Factorial Correspondence Analysis was performed to correlate amino acid mutations with clinical parameters. RESULTS: The sequences were distributed into four phylogenetic clusters. Three clusters corresponded to the subgenogroup C4 and the last one corresponded to the subgenogroup C5. Each cluster displayed different polymorphism characteristics. Proteins were highly conserved but three sites bearing only Isoleucine (I) or Valine (V) were characterized. The isoleucine/valine variability matched the clusters. Spatiotemporal analysis of the I/V variants showed that all variants which emerged in 2011 and then in 2012 were not the same but were all present in the region prior to the 2011-2012 outbreak. Some correlation was found between certain I/V variants and ethnicity and severity. CONCLUSIONS: The 2011-2012 outbreak was not caused by an exogenous strain coming from South Vietnam or elsewhere but by strains already present and circulating at low level in North Vietnam. However, what triggered the outbreak remains unclear. A selective pressure is applied on I/V variants which matches the genetic clusters. I/V variants were shown on other viruses to correlate with pathogenicity. This should be investigated in EV-A71. I/V variants are an easy and efficient way to survey and identify circulating EV-A71 strains.

Modeling the Dynamic of Multiwave Diseases: The Model of Hand, Foot and Mouth Disease.

An HFMD outbreak spread over the city of Hai Phòng from summer 2011 to autumn 2012. This epidemic was chosen because it was the very first HFMD epidemic in North Vietnam, eliminating thus interferences with previous outbreaks. This epidemic displayed three separate waves. A complete dataset was collected for more than 9500 patients during this period, which enabled us to analyze this epidemic at different scales. Access to the healthcare system was crucial during this period, which was possible due to a reorganization of the system in February-March 2012. An analysis at the commune level enabled us to track the epidemic along certain communication routes. The three-waves structure reveals a wide disparity at the district level. We developed a mathematical model showing high accuracy at the adjustment of data for both the total number of cases and for the number of cases per week. As a consequence, the model was able to accurately determine the dates of the beginning and end of each wave and to show that they overlapped. Using mathematical functions associated with this model, it was possible to calculate the probability for a patient to belong to a specific wave.