Editing High-throughput screening (section)

=== Quality control ===
High-quality HTS assays are critical in HTS experiments. The development of high-quality HTS assays requires the integration of both experimental and computational approaches for quality control (QC). Three important means of QC are (i) good plate design, (ii) the selection of effective positive and negative chemical/biological controls, and (iii) the development of effective QC metrics to measure the degree of differentiation so that assays with inferior data quality can be identified.
<ref name=ZhangetalJBS2008>{{cite journal |vauthors=Zhang XH, Espeseth AS, Johnson EN, Chin J, Gates A, Mitnaul LJ, Marine SD, Tian J, Stec EM, Kunapuli P, Holder DJ, Heyse JF, Strulocivi B, Ferrer M |title=Integrating experimental and analytic approaches to improve data quality in genome-scale RNAi screens
|journal=Journal of Biomolecular Screening  |volume=13 |issue= 5|pages=378–89
|year=2008 |pmid= 18480473|doi=10.1177/1087057108317145 |s2cid=22679273
|doi-access=free}}</ref>
A good plate design helps to identify systematic errors (especially those linked with well position) and determine what normalization should be used to remove/reduce the impact of systematic errors on both QC and hit selection.<ref name="ZhangBook2011" />

Effective analytic QC methods serve as a gatekeeper for excellent quality assays. In a typical HTS experiment, a clear distinction between a positive control and a negative reference such as a negative control is an index for good quality. Many quality-assessment measures have been proposed to measure the degree of differentiation between a positive control and a negative reference. Signal-to-background ratio, signal-to-noise ratio, signal window, assay variability ratio, and [[Z-factor]] have been adopted to evaluate data quality.
<ref name="ZhangBook2011" />
<ref name=ZhangJHetalJBS1999>{{cite journal |vauthors=Zhang JH, Chung TD, Oldenburg KR |title=A simple statistical parameter for use in evaluation and validation of high throughput screening assays
|journal=Journal of Biomolecular Screening  |volume=4 |issue= 2|pages=67–73
|year=1999 |pmid= 10838414|doi=10.1177/108705719900400206 |s2cid=36577200
|doi-access=free}}</ref>
Strictly standardized mean difference ([[SSMD]]) has recently been proposed for assessing data quality in HTS assays.
<ref name=ZhangGenomics2007>{{cite journal |author=Zhang, XHD
|title=A pair of new statistical parameters for quality control in RNA interference high-throughput screening assays
|journal=Genomics  |volume=89 |issue= 4|pages=552–61
|year=2007 |pmid= 17276655|doi=10.1016/j.ygeno.2006.12.014 |doi-access=}}</ref>
<ref name=ZhangJBS2008>{{cite journal |author=Zhang XHD
|title=Novel analytic criteria and effective plate designs for quality control in genome-scale RNAi screens
|journal=Journal of Biomolecular Screening  |volume=13 |issue= 5|pages=363–77
|year=2008 |pmid= 18567841|doi=10.1177/1087057108317062 |s2cid=12688742
|doi-access=free}}</ref>