Many fields,such as neuroscience,are experiencing the vast prolife ration of cellular data,underscoring the need fo r organizing and interpreting large datasets.A popular approach partitions data into manageable subse...Many fields,such as neuroscience,are experiencing the vast prolife ration of cellular data,underscoring the need fo r organizing and interpreting large datasets.A popular approach partitions data into manageable subsets via hierarchical clustering,but objective methods to determine the appropriate classification granularity are missing.We recently introduced a technique to systematically identify when to stop subdividing clusters based on the fundamental principle that cells must differ more between than within clusters.Here we present the corresponding protocol to classify cellular datasets by combining datadriven unsupervised hierarchical clustering with statistical testing.These general-purpose functions are applicable to any cellular dataset that can be organized as two-dimensional matrices of numerical values,including molecula r,physiological,and anatomical datasets.We demonstrate the protocol using cellular data from the Janelia MouseLight project to chara cterize morphological aspects of neurons.展开更多
The present study investigated the genetic diversity of 24 germplasms of Polianthes tuberosa L.via 16 inter simple sequence repeat(ISSR)marker techniques.The research findings revealed that the ISSR markers presented ...The present study investigated the genetic diversity of 24 germplasms of Polianthes tuberosa L.via 16 inter simple sequence repeat(ISSR)marker techniques.The research findings revealed that the ISSR markers presented higher levels of band reproducibility andweremore efficient at clustering germplasms.Among the 16markers examined in this study,12 had a complete polymorphism rate of 100%.Themolecular analysis revealed a PICranging from0.079 to 0.373,with amean value of 0.30,whereas the range of themarker index was from0.0001 to 0.409,with an average value of 0.03,and the primer resolving power ranged from 0.173 to 4.173,with a mean value of 2.02.The UPGMA clustering dendrogram indicated that all 24 germplasms were grouped into three main clusters.The study revealed a variable range of tree distances between 0.185 and 0.621,with the highest tree distance(0.621)detected between germplasms BR-24 and BR-1.Through these studies,the dissimilarity among the germplasms was evaluated,and diverse parents were identified for further crop improvement programs.展开更多
基金supported in part by NIH grants R01NS39600,U01MH114829RF1MH128693(to GAA)。
文摘Many fields,such as neuroscience,are experiencing the vast prolife ration of cellular data,underscoring the need fo r organizing and interpreting large datasets.A popular approach partitions data into manageable subsets via hierarchical clustering,but objective methods to determine the appropriate classification granularity are missing.We recently introduced a technique to systematically identify when to stop subdividing clusters based on the fundamental principle that cells must differ more between than within clusters.Here we present the corresponding protocol to classify cellular datasets by combining datadriven unsupervised hierarchical clustering with statistical testing.These general-purpose functions are applicable to any cellular dataset that can be organized as two-dimensional matrices of numerical values,including molecula r,physiological,and anatomical datasets.We demonstrate the protocol using cellular data from the Janelia MouseLight project to chara cterize morphological aspects of neurons.
基金funded by Uttar Banga Krishi Viswavidyalaya,IndiaBangladesh Wheat and Maize Research Institute,Dinajpur 5200,Bangladeshfunded by Taif University,Saudi Arabia,Project No.(TU-DSPP-2025-30).
文摘The present study investigated the genetic diversity of 24 germplasms of Polianthes tuberosa L.via 16 inter simple sequence repeat(ISSR)marker techniques.The research findings revealed that the ISSR markers presented higher levels of band reproducibility andweremore efficient at clustering germplasms.Among the 16markers examined in this study,12 had a complete polymorphism rate of 100%.Themolecular analysis revealed a PICranging from0.079 to 0.373,with amean value of 0.30,whereas the range of themarker index was from0.0001 to 0.409,with an average value of 0.03,and the primer resolving power ranged from 0.173 to 4.173,with a mean value of 2.02.The UPGMA clustering dendrogram indicated that all 24 germplasms were grouped into three main clusters.The study revealed a variable range of tree distances between 0.185 and 0.621,with the highest tree distance(0.621)detected between germplasms BR-24 and BR-1.Through these studies,the dissimilarity among the germplasms was evaluated,and diverse parents were identified for further crop improvement programs.
