PubMed · 9581356
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J Lemon. 1998-03-28. Dramatic condition.. https://doi.org/10.1038/sj.bdj.4809595
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MOTIVATION: 10x Genomics VisiumHD enables spatial transcriptomics at 2 µm × 2 µm resolution but exhibits slide-specific, non-periodic striping artifacts due to lane-width variability. These multiplicative row/column effects distort bin total counts and can bias downstream analyses. The state-of-the-art destriping approach is the normalization procedure used as a preprocessing step in bin2cell; it applies sequential high-quantile row- then column-wise normalization, which is asymmetric and can introduce edge effects/macro-stripes and distortions of large-scale total-count structure. RESULTS: We propose a statistical destriping approach that leverages nuclei segmentation from the co-registered H&E image. Assuming transcript abundance is constant within each nucleus, we model bin counts with a negative binomial distribution whose mean is a product of a nucleus-specific concentration and row- and column-specific stripe-factors reflecting lane-width variation. We fit all parameters in a generalized linear modeling framework with cross-validated regularization on stripe-factors and iterative dispersion estimation, and use the fitted parameters to correct the observed counts into a destriped image. On synthetic data with known ground truth, our method improves stripe-factor estimation accuracy and reduces error in corrected counts relative to bin2cell and bin2cell-derived baselines. Across four public VisiumHD slides, it consistently lowers striping intensity while substantially better preserving biological signal present in the large-scale global count structure and avoiding the artifacts introduced by other methods. AVAILABILITY AND IMPLEMENTATION: All source code and links to publicly available data used for this study are available at https://github.com/paolamalsot/destriping-GLM.
The power spectrum of human heart rate (HR) measured over 24 h exhibits "power-law" 1/f alpha-type spectral behavior with alpha approximately 1. We investigate possible nonstationarity in time of the exponent alpha using maximum likelihood estimation, which allows relatively short data segments to be used. Examination of 24-h HR records from ambulatory normal and congestive heart failure (CHF) subjects indicates that the power-law structure of HR is nonstationary. In addition, alpha varies with time scale and is different for normal (alpha approximately 1) and CHF (alpha approximately 1.5) subjects. Simulations suggest that a possible mechanism underlying the observed power-law spectrum may be a switching between values of alpha near zero (white noise) and near two (Brownian motion). This mechanism generates power-law forms quantitatively similar to CHF subjects when the switching occurs very rapidly and similar to normal subjects when the switching is less rapid.
We describe the development of a sensitive fluorescence-based solution assay for RNA using a new dye, RiboGreen RNA quantitation reagent. RiboGreen reagent exhibits >1000-fold fluorescence enhancement and high quantum yield (0.65) upon binding nucleic acids, with excitation and emission maxima near those of fluorescein. Unbound dye is essentially nonfluorescent and has a large extinction coefficient (67,000 cm-1 M-1). The RiboGreen assay allows detection of as little as 1.0 ng/ml RNA in a standard fluorometer, filter fluorometer, or fluorescence microplate reader-surpassing the sensitivity achieved with ethidium bromide by 200-fold. The linear quantitation range for RiboGreen reagent extends over three orders of magnitude in RNA concentration. Using 750 nM RiboGreen reagent, we quantitated 20 ng/ml to 1.0 microg/ml RNA. By diluting the reagent to 75 nM, we could quantitate 1.0 to 50 ng/ml RNA. Both assay ranges exhibited linear fluorescence increases versus RNA concentration (r2 = 0.999). Assay linearity was maintained in the presence of salts, protein, urea, ethanol, chloroform, agarose, and some detergents. Several different RNA types yielded similar signal intensities and detection sensitivities. The assay is easy to use, rapid, and readily adaptable for automation.