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Increasing the Content of High-Content Screening: An Overview.

Singh S, Carpenter AE, Genovesio A - J Biomol Screen (2014)

Bottom Line: This includes practical problems related to managing large and multidimensional HCS data sets as well as the adoption of assay quality statistics from HTS to HCS.Both may have led to the simplification or systematic rejection of assays carrying complex and valuable phenotypic information.We predict that advanced data analysis methods that enable full multiparametric data to be harvested for entire cell populations will enable HCS to finally reach its potential.

View Article: PubMed Central - PubMed

Affiliation: Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA.

No MeSH data available.


Related in: MedlinePlus

The necessary steps required to use the Z′-factor as a quality metric drastically simplify assay readout and analysis but typically also reduce the power and value of an HCS assay. (A) The Z′-factor is a univariate statistic, so assay developers typically select a single feature as a readout, ignoring a large part of other available information; (B) the per-cell measurements need to be aggregated into a single value per replicate sample, and assays presenting heterogeneous cell responses detectable only via subtleties in their population distributions will often fail to yield acceptable Z′-factor values and be discarded; and (C) the Z′-factor requires that the distributions of controls’ values are Gaussian—a condition that is met by choosing the method of aggregation to be the mean throughout the cell population—but this biases the selection of assays considerably, as discussed in the text.
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fig5-1087057114528537: The necessary steps required to use the Z′-factor as a quality metric drastically simplify assay readout and analysis but typically also reduce the power and value of an HCS assay. (A) The Z′-factor is a univariate statistic, so assay developers typically select a single feature as a readout, ignoring a large part of other available information; (B) the per-cell measurements need to be aggregated into a single value per replicate sample, and assays presenting heterogeneous cell responses detectable only via subtleties in their population distributions will often fail to yield acceptable Z′-factor values and be discarded; and (C) the Z′-factor requires that the distributions of controls’ values are Gaussian—a condition that is met by choosing the method of aggregation to be the mean throughout the cell population—but this biases the selection of assays considerably, as discussed in the text.

Mentions: There are several problems with using the Z′-factor in HCS (Fig. 5). First, the statistic requires that the readout be univariate, so typically only a single cellular feature is retained. Second, although multivariate extensions to the Z′-factor have been proposed,6,7 they still require that the per-cell readouts be summarized into a single value per replicate sample. By doing so, the rich information captured from single-cell measurements is effectively discarded. Together, these two transformations coerce a matrix of readouts into a single value per sample, thereby losing many of the benefits of HCS.


Increasing the Content of High-Content Screening: An Overview.

Singh S, Carpenter AE, Genovesio A - J Biomol Screen (2014)

The necessary steps required to use the Z′-factor as a quality metric drastically simplify assay readout and analysis but typically also reduce the power and value of an HCS assay. (A) The Z′-factor is a univariate statistic, so assay developers typically select a single feature as a readout, ignoring a large part of other available information; (B) the per-cell measurements need to be aggregated into a single value per replicate sample, and assays presenting heterogeneous cell responses detectable only via subtleties in their population distributions will often fail to yield acceptable Z′-factor values and be discarded; and (C) the Z′-factor requires that the distributions of controls’ values are Gaussian—a condition that is met by choosing the method of aggregation to be the mean throughout the cell population—but this biases the selection of assays considerably, as discussed in the text.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2 - License 3
Show All Figures
getmorefigures.php?uid=PMC4230961&req=5

fig5-1087057114528537: The necessary steps required to use the Z′-factor as a quality metric drastically simplify assay readout and analysis but typically also reduce the power and value of an HCS assay. (A) The Z′-factor is a univariate statistic, so assay developers typically select a single feature as a readout, ignoring a large part of other available information; (B) the per-cell measurements need to be aggregated into a single value per replicate sample, and assays presenting heterogeneous cell responses detectable only via subtleties in their population distributions will often fail to yield acceptable Z′-factor values and be discarded; and (C) the Z′-factor requires that the distributions of controls’ values are Gaussian—a condition that is met by choosing the method of aggregation to be the mean throughout the cell population—but this biases the selection of assays considerably, as discussed in the text.
Mentions: There are several problems with using the Z′-factor in HCS (Fig. 5). First, the statistic requires that the readout be univariate, so typically only a single cellular feature is retained. Second, although multivariate extensions to the Z′-factor have been proposed,6,7 they still require that the per-cell readouts be summarized into a single value per replicate sample. By doing so, the rich information captured from single-cell measurements is effectively discarded. Together, these two transformations coerce a matrix of readouts into a single value per sample, thereby losing many of the benefits of HCS.

Bottom Line: This includes practical problems related to managing large and multidimensional HCS data sets as well as the adoption of assay quality statistics from HTS to HCS.Both may have led to the simplification or systematic rejection of assays carrying complex and valuable phenotypic information.We predict that advanced data analysis methods that enable full multiparametric data to be harvested for entire cell populations will enable HCS to finally reach its potential.

View Article: PubMed Central - PubMed

Affiliation: Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA.

No MeSH data available.


Related in: MedlinePlus