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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.


The percentage of papers throughout all three searches that use the Z′-factor, plotted by year of publication. The fractions indicate the number of papers that use the Z′-factor divided by the total number of papers in each year. Overall, 40% use the Z′-factor (dotted line).
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fig4-1087057114528537: The percentage of papers throughout all three searches that use the Z′-factor, plotted by year of publication. The fractions indicate the number of papers that use the Z′-factor divided by the total number of papers in each year. Overall, 40% use the Z′-factor (dotted line).

Mentions: Interestingly, the screening community has adopted the Z′-factor as a quality control statistic for HCS as well. Of the 118 papers identified above, 40% used the Z′-factor (Fig. 4); the majority of these came from the HCS-title group (Suppl. Fig. 2). Many of the remainder also used a Gaussian assumption of univariate controls, for example in t tests.


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

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

The percentage of papers throughout all three searches that use the Z′-factor, plotted by year of publication. The fractions indicate the number of papers that use the Z′-factor divided by the total number of papers in each year. Overall, 40% use the Z′-factor (dotted line).
© Copyright Policy - open-access
Related In: Results  -  Collection

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

fig4-1087057114528537: The percentage of papers throughout all three searches that use the Z′-factor, plotted by year of publication. The fractions indicate the number of papers that use the Z′-factor divided by the total number of papers in each year. Overall, 40% use the Z′-factor (dotted line).
Mentions: Interestingly, the screening community has adopted the Z′-factor as a quality control statistic for HCS as well. Of the 118 papers identified above, 40% used the Z′-factor (Fig. 4); the majority of these came from the HCS-title group (Suppl. Fig. 2). Many of the remainder also used a Gaussian assumption of univariate controls, for example in t tests.

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.