EasyFlow: User-friendly Workflow for Image-based Droplet Analysis with Multipurpose Modules

Droplet-based experimental platforms allow researchers to perform massive parallelization and high-throughput studies, such as single-cell experiments. Even though there are various options of image analysis software to evaluate the experiment, selecting the right tools require experience and is time consuming. Experts and sophisticated workflow are required to perform the analysis, especially to detect the droplets and analyze their content. There is need for user-friendly droplet analysis pipelines that can be adapted in laboratories with minimum learning curve. Here, we provide a user-friendly workflow for image-based droplet analysis. The workflow comprises of a) CellProfiler-based image-analysis pipeline and b) accompanied with web application that simplifies the analysis and visualization of the droplet-based experiment. We construct necessary modules in CellProfiler (CP) to detect droplets and export the results into our web application. Using the web application, we are able to process and provide basic profiles of the droplet experiment (droplet sizes, droplet signals, sizes-signals plot, and strip plot for each label/condition). We also add a specific module for growth heterogeneity studies in bacteria populations that includes single cell viability analysis and probability distribution of minimum inhibition concentration (MIC) values in population. Our pipeline is usable for both poly- and monodisperse droplet emulsions.

A massively scalable Time-to-Digital Converter with a PLL-free calibration system in a commercial 130 nm process

A 33.6 ps LSB Time-to-Digital converter was designed in 130 nm BiCMOS technology. The core of the converter is a differential 9-stage ring oscillator, based on a multi-path architecture. A novel version of this design is proposed, along with an analytical model of linearity. The model allowed us to understand the source of the performance superiority (in terms of linearity) of our design and to predict further improvements. The oscillator is integrated in a event-by-event self-calibration system that allows avoiding any PLL-based synchronization. For this reason and for the compactness and simplicity of the architecture, the proposed TDC is suitable for applications in which a large number of converters and a massive parallelization are required such as High-Energy Physics and medical imaging detector systems. A test chip for the TDC has been fabricated and tested. The TDC shows a DNL≤1.3 LSB, an INL≤2 LSB and a single-shot precision of 19.5 ps (0.58 LSB). The chip dissipates a power of 5.4 mW overall.

GPU accelerated voxel-based machining simulation

The simulation of subtractive manufacturing processes has a long history in engineering. Corresponding predictions are utilized for planning, validation and optimization, e.g., of CNC-machining processes. With the up-rise of flexible robotic machining and the advancements of computational and algorithmic capability, the simulation of the coupled machine-process behaviour for complex machining processes and large workpieces is within reach. These simulations require fast material removal predictions and analysis with high spatial resolution for multi-axis operations. Within this contribution, we propose to leverage voxel-based concepts introduced in the computer graphics industry to accelerate material removal simulations. Corresponding schemes are well suited for massive parallelization. By leveraging the computational power offered by modern graphics hardware, the computational performance of high spatial accuracy volumetric voxel-based algorithms is further improved. They now allow for very fast and accurate volume removal simulation and analysis of machining processes. Within this paper, a detailed description of the data structures and algorithms is provided along a detailed benchmark for common machining operations.

Optical Detection Methods for High-Throughput Fluorescent Droplet Microflow Cytometry

High-throughput microflow cytometry has become a focal point of research in recent years. In particular, droplet microflow cytometry (DMFC) enables the analysis of cells reacting to different stimuli in chemical isolation due to each droplet acting as an isolated microreactor. Furthermore, at high flow rates, the droplets allow massive parallelization, further increasing the throughput of droplets. However, this novel methodology poses unique challenges related to commonly used fluorometry and fluorescent microscopy techniques. We review the optical sensor technology and light sources applicable to DMFC, as well as analyze the challenges and advantages of each option, primarily focusing on electronics. An analysis of low-cost and/or sufficiently compact systems that can be incorporated into portable devices is also presented.

Novel Approach for Parallelizing Pairwise Comparison Problems as Applied to Detecting Segments Identical By Decent in Whole-Genome Data

Motivation Pairwise comparison problems arise in many areas of science. In genomics, datasets are already large and getting larger, and so operations that require pairwise comparisons—either on pairs of SNPs or pairs of individuals—are extremely computationally challenging. We propose a generic algorithm for addressing pairwise comparison problems that breaks a large problem (of order n2 comparisons) into multiple smaller ones (each of order n comparisons), allowing for massive parallelization. Results We demonstrated that this approach is very efficient for calling identical by descent (IBD) segments between all pairs of individuals in the UK Biobank dataset, with a 250-fold savings in time and 750-fold savings in memory over the standard approach to detecting such segments across the full dataset. This efficiency should extend to other methods of IBD calling and, more generally, to other pairwise comparison tasks in genomics or other areas of science.