Inference of chromosome selection parameters and missegregation rate in cancer from DNA-sequencing data Article Open access 31 July 2024 scAbsolute: measuring single-cell ploidy and replication status Article Open access 04 March 2024 NestedBD: Bayesian inference of phylogenetic trees from single-...
Nanopore sequencers can select which DNA molecules to sequence, rejecting a molecule after analysis of a small initial part. Currently, selection is based on predetermined regions of interest that remain constant throughout an experiment. Sequencing efforts, thus, cannot be re-focused on molecules li...
Single-cell assay for transposase-accessible chromatin by sequencing (scATAC-seq) has emerged as a powerful tool for dissecting regulatory landscapes and cellular heterogeneity. However, an exploration of systemic biases among scATAC-seq technologies has remained absent. In this study, we benchmark the...
MinKNOW carries out several core tasks—data acquisition; real-time analysis and feedback; data streaming while providing device control (including run parameter selection); as well as sample identification and tracking—thus ensuring that the platform chemistry performs correctly in processing the ...
Upon DE gene selection, Principal Component Analysis (PCA) [16] is performed to reduce the dimensionality of the data using the DE genes as features. The number of principal components (PCs) to be used can be selected using an elbow plot. For the datasets used here, we found 15 PCs to...
(Top) The same network as in panel b, trained with dropout on hidden nodes. Dropout nodes are randomly selected at each training iteration. (Bottom) Learning with dropout results in robust and highly correlated weights (inset) for the two redundant nodes.dNode weights of weakly and strongly ...
(Top) The same network as in panel b, trained with dropout on hidden nodes. Dropout nodes are randomly selected at each training iteration. (Bottom) Learning with dropout results in robust and highly correlated weights (inset) for the two redundant nodes.dNode weights of weakly and strongly ...
(Fig.1). The batch correction algorithms tested are either available in the R or Python language environment. For Seurat 2, Harmony, MNN Correct, fastMNN, and limma, the data preprocessing steps of normalization, scaling, and highly variable gene (HVG) selection were performed using the Seurat...
importance of RT and cell cycle properties in studying the genomic evolution of aneuploid tumors. Similar content being viewed by others Inference of chromosome selection parameters and missegregation rate in cancer from DNA-sequencing data ArticleOpen access31 July 2024...
Both selection and mutation procedures were repeated formgenerations, each of them with the same size ofnindividuals and elite size ofne, before the most highly scored candidate peptide according to the selected fitness function was returned as the final peptide sequence of the given spectrum. Hyper...