flowSim: Near duplicate detection for flow cytometry data.

The analysis of large amounts of data is important for the development of machine learning (ML) models. flowSim is the first algorithm designed to visualize, detect and remove highly redundant information in flow cytometry (FCM) training sets to decrease the computational time for training and increase the performance of ML algorithms by reducing overfitting. flowSim performs near duplicate image detection by combining community detection algorithms with the density analysis of the marker expression values. flowSim clustering compared to consensus manual clustering on a dataset composed of 160 images of bivariate FCM data had a mean Adjusted Rand Index of 0.90, demonstrating its efficiency in identifying similar patterns. flowSim selectively discarded near duplicate files in datasets constructed with known redundancy, and removed 92.6% of FCM images in a dataset of over 500,000 drawn from public repositories.

Modeling the Life Cycle of the Intramitochondrial Bacterium "Candidatus Midichloria mitochondrii" Using Electron Microscopy Data.

"Candidatus Midichloria mitochondrii" is a Gram-negative bacterium that lives in strict intracellular symbiosis with the hard tick Ixodes ricinus, forming one of the most intriguing endosymbiosis described to date. The bacterium is capable of durably colonizing the host mitochondria, a peculiar tropism that makes "Ca. Midichloria mitochondrii" a very interesting tool to study the physiology of these cellular organelles. The interaction between the symbiont and the organelle has, however, been difficult to characterize. A parallelism with the predatory bacterium Bdellovibrio bacteriovorus has been drawn, suggesting the hypothesis that "Ca. Midichloria mitochondrii" could prey on mitochondria and consume them to multiply. We studied the life cycle of the bacterium within the host oocytes using a multidisciplinary approach, including electron microscopy, molecular biology, statistics, and systems biology. Our results were not coherent with a predatory-like behavior by "Ca. Midichloria mitochondrii" leading us to propose a novel hypothesis for its life cycle. Based on our results, we here present a novel model called the "mitochondrion-to-mitochondrion hypothesis." Under this model, the bacterium would be able to move from mitochondrion to mitochondrion, possibly within a mitochondrial network. We show that this model presents a good fit with quantitative electron microscopy data. IMPORTANCE Our results suggest that "Candidatus Midichloria mitochondrii," the intramitochondrial bacterium, does not invade mitochondria like predatory bacteria do but instead moves from mitochondrion to mitochondrion within the oocytes of Ixodes ricinus. A better understanding of the lifestyle of "Ca. Midichloria mitochondrii" will allow us to better define the role of this bacterial symbiont in the host physiology.

Flow cytometry data analysis: Recent tools and algorithms.

Flow cytometry (FCM) allows scientists to rapidly quantify up to 50 parameters for millions of cells per sample. The bottleneck in the application of the technology is data analysis, and the high number of parameters measured by the current generation of instruments requires the use of advanced computational algorithms to make full use of their capabilities. This review summarizes the main steps of FCM data analysis, focusing on the use of the most recent bioinformatic tools developed for an R-based programming environment. In particular, for each stage of the data analysis, libraries and packages currently available are listed, and a brief description of their functioning is included.