Cytometry Part A 

About: Cytometry Part A is an academic journal published by Wiley-Blackwell. The journal publishes majorly in the area(s): Cytometry & Flow cytometry. It has an ISSN identifier of 1552-4922. Over the lifetime, 2701 publications have been published receiving 82505 citations. The journal is also known as: Cytometry. Part A.

Design and Validation of a Tool for Neurite Tracing and Analysis in Fluorescence Microscopy Images

Abstract: Background: For the investigation of the molecular mechanisms involved in neurite outgrowth and differentiation, accurate and reproducible segmentation and quantification of neuronal processes are a prerequisite. To facilitate this task, we developed a semiautomatic neurite tracing technique. This article describes the design and validation of the technique. Methods: The technique was compared to fully manual delineation. Four observers repeatedly traced selected neurites in 20 fluorescence microscopy images of cells in culture, using both methods. Accuracy and reproducibility were determined by comparing the tracings to high-resolution reference tracings, using two error measures. Labor intensiveness was measured in numbers of mouse clicks required. The significance of the results was determined by a Student t-test and by analysis of variance. Results: Both methods slightly underestimated the true neurite length, but the differences were not unanimously significant. The average deviation from the true neurite centerline was a factor 2.6 smaller with the developed technique compared to fully manual tracing. Intraobserver variability in the respective measures was reduced by a factor 6.0 and 23.2. Interobserver variability was reduced by a factor 2.4 and 8.8, respectively, and labor intensiveness by a factor 3.3. Conclusions: Providing similar accuracy in measuring neurite length, significantly improved accuracy in neurite centerline extraction, and significantly improved reproducibility and reduced labor intensiveness, the developed technique may replace fully manual tracing methods.

FlowSOM: Using self-organizing maps for visualization and interpretation of cytometry data.

Abstract: The number of markers measured in both flow and mass cytometry keeps increasing steadily. Although this provides a wealth of information, it becomes infeasible to analyze these datasets manually. When using 2D scatter plots, the number of possible plots increases exponentially with the number of markers and therefore, relevant information that is present in the data might be missed. In this article, we introduce a new visualization technique, called FlowSOM, which analyzes Flow or mass cytometry data using a Self-Organizing Map. Using a two-level clustering and star charts, our algorithm helps to obtain a clear overview of how all markers are behaving on all cells, and to detect subsets that might be missed otherwise. R code is available at https://github.com/SofieVG/FlowSOM and will be made available at Bioconductor.

Nuclear DNA content and genome size of trout and human.

Abstract: NUCLEAR DNA CONTENT AND GENOME SIZE OF TROUT AND HUMAN In their recent paper, Thomas et al. (1) discussed design, resolution, sensitivity, and reproducibility of the National Aeronautics and Space Administration/American Cancer Society flow cytometer. The results of their study demonstrated high stability and sensitivity of the instrument, which is suitable for detection of near-diploid tumor cells. Although the performance of the instrument is impressive, we believe that Thomas et al. made serious errors in calculating the DNA contents of trout and human. To estimate the DNA content of human cells in picograms of DNA, the authors used trout red blood cell nuclei as the internal reference standard and assumed 2.37 pg of DNA for a trout nucleus. With this value, the DNA contents of human female and male nuclei were estimated to be equal to 3.77 and 3.70 pg of DNA, respectively. The new estimates for trout and human differ drastically from previous ones, which range from 4.9 to 6.3 pg for various species of trout (2–5) and from 6.0 to 7.0 pg for human (5–9). Because trout and human nuclei are often used as internal reference standards to determine genome size in animals and plants (5,10,11), the results published by Thomas et al. (1) need correction to avoid serious mistakes. Careful reading of the paper showed that the DNA content of trout (the authors did not specify the species) was derived after determining the ratio of mean DNA content of human male to trout to be 1.565. The DNA amount of the human nucleus, 3.70 pg, was calculated with the assumption that there are 6.162 10 nucleotides for the human male nucleus and that a mean nucleotide molecular weight of 360 g/mol. We believe these data are not correct.

SPICE: exploration and analysis of post-cytometric complex multivariate datasets.

Abstract: Polychromatic flow cytometry results in complex, multivariate datasets. To date, tools for the aggregate analysis of these datasets across multiple specimens grouped by different categorical variables, such as demographic information, have not been optimized. Often, the exploration of such datasets is accomplished by visualization of patterns with pie charts or bar charts, without easy access to statistical comparisons of measurements that comprise multiple components. Here we report on algorithms and a graphical interface we developed for these purposes. In particular, we discuss thresholding necessary for accurate representation of data in pie charts, the implications for display and comparison of normalized versus unnormalized data, and the effects of averaging when samples with significant background noise are present. Finally, we define a statistic for the nonparametric comparison of complex distributions to test for difference between groups of samples based on multi-component measurements. While originally developed to support the analysis of T cell functional profiles, these techniques are amenable to a broad range of datatypes.

Quantifying colocalization by correlation: the Pearson correlation coefficient is superior to the Mander's overlap coefficient.

Abstract: The Pearson correlation coefficient (PCC) and the Mander's overlap coefficient (MOC) are used to quantify the degree of colocalization between fluorophores. The MOC was introduced to overcome perceived problems with the PCC. The two coefficients are mathematically similar, differing in the use of either the absolute intensities (MOC) or of the deviation from the mean (PCC). A range of correlated datasets, which extend to the limits of the PCC, only evoked a limited response from the MOC. The PCC is unaffected by changes to the offset while the MOC increases when the offset is positive. Both coefficients are independent of gain. The MOC is a confusing hybrid measurement, that combines correlation with a heavily weighted form of co-occurrence, favors high intensity combinations, downplays combinations in which either or both intensities are low and ignores blank pixels. The PCC only measures correlation. A surprising finding was that the addition of a second uncorrelated population can substantially increase the measured correlation, demonstrating the importance of excluding background pixels. Overall, since the MOC is unresponsive to substantial changes in the data and is hard to interpret, it is neither an alternative to nor a useful substitute for the PCC. The MOC is not suitable for making measurements of colocalization either by correlation or co-occurrence.