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
After an initial golden age typified by Cajal’s morphological classification of neuronal types based on Golgi’s stain at the turn of the twentieth century,followed by relative doldrums a few decades ago,Neuroanatomy...After an initial golden age typified by Cajal’s morphological classification of neuronal types based on Golgi’s stain at the turn of the twentieth century,followed by relative doldrums a few decades ago,Neuroanatomy has recently undergone a renaissance,driven by exponential decreases in storage and computing costs as well as major advances in biochemistry and microscopic techniques.This can be seen through citations of the term“connectomics”recently coined to denote the study of neuroanatomical connectivity,which retrieves nearly 8000 hits in PubMed and over 20,000 in Google Scholar in the 15 years since the term appeared in print[1].It is broadly recognized that regional connectivity at the mesoscopic scale underlies distributed brain function and single neuron axonal projections underlie mesoscale connectivity[2,3].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supported by the National Institutes of Health grants(R01NS39600,U01MH114829,R01NS86082,and RF1MH128693)。
文摘After an initial golden age typified by Cajal’s morphological classification of neuronal types based on Golgi’s stain at the turn of the twentieth century,followed by relative doldrums a few decades ago,Neuroanatomy has recently undergone a renaissance,driven by exponential decreases in storage and computing costs as well as major advances in biochemistry and microscopic techniques.This can be seen through citations of the term“connectomics”recently coined to denote the study of neuroanatomical connectivity,which retrieves nearly 8000 hits in PubMed and over 20,000 in Google Scholar in the 15 years since the term appeared in print[1].It is broadly recognized that regional connectivity at the mesoscopic scale underlies distributed brain function and single neuron axonal projections underlie mesoscale connectivity[2,3].
