PubMed · 15335207
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Jeffrey Scott Coker, Eric Davies. 2004. Identifying adaptor contamination when mining DNA sequence data.. https://doi.org/10.2144/04372bm03
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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.
In this experiment, we have measured surface EMG of the first dorsal interosseus during predefined submaximal isometric contractions (5, 15, 30, 50, and 70% of maximal force) of the index finger simultaneously with fMRI measurements. Since we have used sparse sampling fMRI (3-s scanning; 2-s non-scanning), we were able to compare the mean amplitude of the undisturbed EMG (non-scanning) intervals with the mean amplitude of the EMG intervals during scanning, after MRI artifact correction. The agreement between the mean amplitudes of the corrected and the undisturbed EMG was excellent and the mean difference between the two amplitudes was not significantly different. Furthermore, there was no significant difference between the corrected and undisturbed amplitude at different force levels. In conclusion, we have shown that it is feasible to record surface EMG during scanning and that, after MRI artifact correction, the EMG recordings can be used to quantify isometric muscle activity, even at very low activation intensities.
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