High-Throughput Screening Data Analysis

High-throughput screening of biomolecules using cell-free gene expression systems

The incorporation of cell-free transcription and translation systems into high-throughput screening applications enables the in situ and on-demand expression of peptides and proteins. Coupled with modern microfluidic technology, the cell-free methods allow the screening, directed evolution and selection of desired biomolecules in minimal volumes within a short timescale. Cell-free high-throughput screening applications are classified broadly into in vitro display and on-chip technologies. In this review, we outline the development of cell-free high-throughput screening methods. We further discuss operating principles and representative applications of each screening method. The cell-free high-throughput screening methods may be advanced by the future development of new cell-free systems, miniaturization approaches, and automation technologies.

Helios: History and Anatomy of a Successful In-House Enterprise High-Throughput Screening and Profiling Data Analysis System

We describe the main characteristics of the Novartis Helios data analysis software system (Novartis, Basel, Switzerland) for plate-based screening and profiling assays, which was designed and built about 11 years ago. It has been in productive use for more than 10 years and is one of the important standard software applications running for a large user community at all Novartis Institutes for BioMedical Research sites globally. A high degree of automation is reached by embedding the data analysis capabilities into a software ecosystem that deals with the management of samples, plates, and result data files, including automated data loading. The application provides a series of analytical procedures, ranging from very simple to advanced, which can easily be assembled by users in very flexible ways. This also includes the automatic derivation of a large set of quality control (QC) characteristics at every step. Any of the raw, intermediate, and final results and QC-relevant quantities can be easily explored through linked visualizations. Links to global assay metadata management, data warehouses, and an electronic lab notebook system are in place. Automated transfer of relevant data to data warehouses and electronic lab notebook systems are also implemented.

Effect-Size Measures as Descriptors of Assay Quality in High-Content Screening: A Brief Review of Some Available Methodologies

The field of high-content screening (HCS) typically uses measures of screen quality conceived for fairly straightforward high-throughput screening (HTS) scenarios. However, in contrast to HTS, image-based HCS systems rely on multidimensional readouts reporting biological responses associated with complex cellular phenotypes. Not only is the dimensionality in which the screens operate higher, but also the scale of the individual features describing the quantified phenotypic changes is often smaller than what is seen in one-dimensional HTS platforms. Therefore, the use of HTS-type quality measures to characterize HCS screens may severely underestimate the detection power of the assays used, and it may mislead the screening scientists regarding the necessary screen optimization. Also, traditional HTS-based measures are typically reported without any estimation of precision, which makes them unsuitable for computation of confidence intervals or for meta-analysis. This review summarizes the well-established statistical techniques for reporting effect sizes and argues that this broadly accepted methodology could be seamlessly integrated into HCS quality reporting, supplanting or even replacing measures such as Z' or S_w (assay window).