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Sholl Analysis

137 bytes added, 12:19, 25 October 2016
Document v3.6.8 changes
| source = {{GitHub|org=tferr|repo=ASA}}
| released = December 2012
| latest version = '''3.6.7 8 October 2016'''
| status = Active ({{GitHub|org=tferr|repo=ASA||label=Release Notes}})
| category = [[:Category:Plugins|Plugins]], [[:Category:Analysis|Analysis]], [[:Category:Neuroanatomy|Neuroanatomy]]
<div style="font-size:175%;border-bottom:1px dotted #ccc;margin-bottom:0.55em;">Quick links</div>
;Analysis of traced arbors?:Jump to [[#Analysis of Traced Cells|Traced Cells]] or [[#external-traces|Other tracing software]]
;Segmentation issues?:Jump to [[#Cf. Segmentation|Cf. Segmentation]] or [[#Pre-processing|Pre-processing]]
;Having Problems?:Jump to [[#FAQ|FAQs]]
| tip = With binary images, ''Sholl Analysis'' treats zero intensities as the background, independently of the image lookup table or the state of the ''Black background option'' in <span style="border-bottom:1px dotted #ccc;">Process▷ Binary▷ Options...</span> As with any other [ ImageJ routine], confusing background with foreground pixels will lead to aberrant results, including: 1) overestimation of branches and 2) artifacts at distances intersecting the boundaries of the image canvas.}}
<span id="Traces"></span>
== Analysis of Traced Cells ==
[[ File:ShollTracingsPrompt.png|400px|right |Main prompt (version 3.6.8), when input is traced data ({{bc|color=white|Analysis|Sholl|Sholl Analysis (Tracings)...}})]]In this mode, the plugin analyzes reconstructed arbors. This is particularly relevant for stainings that do not allow single-cell resolution. [[#Batch Processing |Batch processing]] is also possible. # Run {{bc|color=white|Analysis|Sholl|Sholl Analysis (Tracings)...}} and specify input files: a tracing file (a <code>.swc</code> or a [[Simple Neurite Tracer]] <code>.traces</code> file) . The command is macro recordable, and the respective image associate to such filesthus, [[#Batch Processing|batch processing]] is also possible. # Choose the center of analysis using the drop down menu in the main prompt listing SWC tags (''axon'', ''dendrite'', ''soma'', etc.). If you have Note that if your tracings are not tagged your traces, you will still be able to choose the center of the analysis through the can do so in [[Simple Neurite Tracer]] interface.# Adjust the default [[#Parameters|Parameters]] in the ''Sholl Analysis'' prompt.
# Problems? Read the [[#FAQ|FAQs]]
Note that if you don't {{Tip| id = external-traces| tip = You can use [[Simple Neurite Tracer]], you can still {{bc|color=white|Sholl Analysis (Tracings)...}} to analyze reconstructed data created by from any software capable of [ SWC] export such as [ Neuromantic], [ NeuronStudio], [ Py3DN] or [ Vaa3D]), not just [[Simple Neurite Tracer]]. In addition, [ L-Measure], [ NLMorphologyConverter] or [ Neuron] can also be used to convert several file formats (including proprietary formats from closed-source commercial software such as Neurolucida®, MicroBrightField, Inc.) into SWC.}}
<span id="Importing"></span>
== Analysis of Existing Profiles ==
| id = Nomenclature
| tip = '''Nomenclature''': [[#References|Previous authors]] have used different terms to describe the largest value taken by the Sholl profile, including ''Dendrite maximum''. Since the Sholl technique is not restricted to dendritic arbors and can be applied to any tree-like structure such as axonal arbors, mammary ducts or blood vessels (cf. [[#Citations|List of citations]]), ''Sholl Analysis'' introduces the term [[#CriticalRadius|Critical radius]], renaming ''Dendrite maximum'' (''N<sub>m</sub>'') to [[#CriticalValue|Critical value]]. Thus, ''Sholl Analysis'' may not follow the conventions adopted by [[Simple_Neurite_Tracer:_Sholl_analysis|Simple Neurite Tracer]].
;<span id="MeanValueOfFunction"></span>Mean value
Sure. But it would hardly be relevantfor data sampled at fixed intervals. The area under the curve (AUC, the area between the sampled curve and the horizontal axis, i.e., its definite integral) could be estimated using, e.g., the [[wikipedia:Trapezoidal rule|trapezoidal rule]]. However, because data is always sampled at equally spaced intervals, doing so would be the same as multiplying [[#MeanInters|Mean inters.]] by the distance between [[#EndRadius|Ending radius]] and [[#StartRadius|Starting radius]]. Thus, effectively, AUC is redundant with [[#MeanInters|Mean inters.]], that is already an integrated measurement of the sampled data. On the other hand,
one could retrieve the AUC of the polynomial fit, but such property is already covered by [[#MeanValueOfFunction|Mean value]].