33:
3134:
usually criterion D (and occasionally criterion C) should be adopted because this control usually has very or extremely strong effects; (ii) for RNAi HTS assays in which cell viability is the measured response, criterion D should be adopted for the controls without cells (namely, the wells with no cells added) or background controls; (iii) in a viral
1709:
of log fold change with respect to a negative reference. In other words, SSMD is the average fold change (on the log scale) penalized by the variability of fold change (on the log scale) . For quality control, one index for the quality of an HTS assay is the magnitude of difference between a positive
168:
To derive a better interpretable parameter for measuring the differentiation between two groups, Zhang XHD proposed SSMD to evaluate the differentiation between a positive control and a negative control in HTS assays. SSMD has a probabilistic basis due to its strong link with d-probability (i.e., the
2528:
HTS assay, a strong or moderate positive control is usually more instructive than a very or extremely strong positive control because the effectiveness of this control is more similar to the hits of interest. In addition, the positive controls in the two HTS experiments theoretically have different
3133:
In application, if the effect size of a positive control is known biologically, adopt the corresponding criterion based on this table. Otherwise, the following strategy should help to determine which QC criterion should be applied: (i) in many small molecule HTS assay with one positive control,
4761:
1680:
3141:
Similar SSMD-based QC criteria can be constructed for an HTS assay where the positive control (such as an activation control) theoretically has values greater than the negative reference. More details about how to apply SSMD-based QC criteria in HTS experiments can be found in a book.
2398:
2071:
1286:
2529:
sizes of effects. Consequently, the QC thresholds for the moderate control should be different from those for the strong control in these two experiments. Furthermore, it is common that two or more positive controls are adopted in a single experiment. Applying the same
4505:
3162:
with a desired size of effects in an HTS screen is called a hit. The process of selecting hits is called hit selection. There are two main strategies of selecting hits with large effects. One is to use certain metric(s) to rank and/or classify the
493:
2536:
The SSMD-based QC criteria listed in the following table take into account the effect size of a positive control in an HTS assay where the positive control (such as an inhibition control) theoretically has values less than the negative reference.
2246:
1099:
589:
4332:
144:
through the comparison of two investigated types of wells. However, the S/B does not take into account any information on variability; and the S/N can capture the variability only in one group and hence cannot assess the quality of
2503:
1738:
The number of wells for the positive and negative controls in a plate in the 384-well or 1536-well platform is normally designed to be reasonably large . Assume that the positive and negative controls in a plate have sample
4626:
1544:
692:
2261:
1899:
1114:
1533:
857:
867:
In the situation where the two groups are independent, Zhang XHD derived the maximum-likelihood estimate (MLE) and method-of-moment (MM) estimate of SSMD. Assume that groups 1 and 2 have sample
4766:
In many cases, scientists may use both SSMD and average fold change for hit selection in HTS experiments. The dual-flashlight plot can display both average fold change and SSMD for all test
3138:
in which the amount of viruses in host cells is the interest, criterion C is usually used, and criterion D is occasionally used for the positive control consisting of siRNA from the virus.
1798:
1730:
and a negative reference. SSMD directly measures the magnitude of difference between two groups. Therefore, SSMD can be used for both quality control and hit selection in HTS experiments.
926:
6120:"Inhibition of calcineurin-mediated endocytosis and alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptors prevents amyloid beta oligomer-induced synaptic disruption"
3550:
2126:
1381:
3858:
3583:
3781:
3473:
3891:
3704:
3627:
3932:
3814:
3506:
2884:
4386:
3965:
3737:
3660:
4374:
3396:
3319:
3001:
2962:
2923:
2840:
2801:
2762:
2723:
1851:
979:
3429:
3352:
392:
4210:
4141:
804:
350:
285:
4579:
4102:
3036:
5574:
Birmingham A, Selfors LM, Forster T, Wrobel D, Kennedy CJ, Shanks E, Santoyo-Lopez J, Dunican DJ, Long A, Kelleher D, Smith Q, Beijersbergen RL, Ghazal P, Shamu CE (2009).
3248:
2679:
2649:
2619:
2589:
384:
3275:
3126:
3096:
3066:
2134:
987:
722:
1891:
1329:
622:
1436:
4614:
1471:
3997:
772:
315:
250:
3200:
212:
4171:
4063:
4036:
504:
4532:
4222:
1404:
742:
169:
probability that the difference between two groups is positive). To some extent, the d-probability is equivalent to the well-established probabilistic index P(
4914:"A new method with flexible and balanced control of false negatives and false positives for hit selection in RNA interference high-throughput screening assays"
1893:. Usually, the assumption that the controls have equal variance in a plate holds. In such a case, The SSMD for assessing quality in that plate is estimated as
4774:
and help to integrate both of them to select hits in HTS experiments . The use of SSMD for hit selection in HTS experiments is illustrated step-by-step in
5298:
Zhang XHD, Espeseth AS, Johnson E, Chin J, Gates A, Mitnaul L, Marine SD, Tian J, Stec EM, Kunapuli P, Holder DJ, Heyse JF, Stulovici B, Ferrer M (2008).
3179:
has effects strong enough to reach a pre-set level. In this strategy, false-negative rates (FNRs) and/or false-positive rates (FPRs) must be controlled.
2406:
53:
5200:
Acion L, Peterson JJ, Temple S, Arndt S (2006). "Probabilistic index: an intuitive non-parametric approach to measuring the size of treatment effects".
3154:
with a desired size of inhibition or activation effect. The size of the compound effect is represented by the magnitude of difference between a test
724:
is first to obtain paired observations from the two groups and then to estimate SSMD based on the paired observations. Based on a paired difference
5999:
Zhang XHD, Kuan PF, Ferrer M, Shu X, Liu YC, Gates AT, Kunapuli P, Stec EM, Xu M, Marine SD, Holder DJ, Stulovici B, Heyse JF, Espeseth AS (2009).
5623:
Klinghoffer RA, Frazier J, Annis J, Berndt JD, Roberts BS, Arthur WT, Lacson R, Zhang XHD, Ferrer M, Moon RT, Cleary MA (2010). Bereswill S (ed.).
4756:{\displaystyle {\text{SSMD}}={\frac {\Gamma ({\frac {n-1}{2}})}{\Gamma ({\frac {n-2}{2}})}}{\sqrt {\frac {2}{n-1}}}{\frac {{\bar {d}}_{i}}{s_{i}}}}
1675:{\displaystyle {\hat {\beta }}={\frac {\Gamma ({\frac {n-1}{2}})}{\Gamma ({\frac {n-2}{2}})}}{\sqrt {\frac {2}{n-1}}}{\frac {\bar {D}}{s_{D}}}.}
4958:
Zhang XHD (2010). "Strictly standardized mean difference, standardized mean difference and classical t-test for the comparison of two groups".
4832:"Optimal High-Throughput Screening: Practical Experimental Design and Data Analysis for Genome-scale RNAi Research, Cambridge University Press"
1701:
of the difference between two groups. When the data is preprocessed using log-transformation as we normally do in HTS experiments, SSMD is the
5752:
630:
6118:
Zhao WQ, Santini F, Breese R, Ross D, Zhang XD, Stone DJ, Ferrer M, Townsend M, Wolfe AL, Seager MA, Kinney GG, Shughrue PJ, Ray WJ (2010).
177:) which has been studied and applied in many areas. Supported on its probabilistic basis, SSMD has been used for both quality control and
2393:{\displaystyle {\hat {\beta }}={\frac {{\tilde {X}}_{P}-{\tilde {X}}_{N}}{1.4826{\sqrt {{\tilde {s}}_{P}^{2}+{\tilde {s}}_{N}^{2}}}}},}
2066:{\displaystyle {\hat {\beta }}={\frac {{\bar {X}}_{P}-{\bar {X}}_{N}}{\sqrt {{\frac {2}{K}}((n_{P}-1)s_{P}^{2}+(n_{N}-1)s_{N}^{2})}}},}
1281:{\displaystyle {\hat {\beta }}={\frac {{\bar {X}}_{1}-{\bar {X}}_{2}}{\sqrt {{\frac {2}{K}}((n_{1}-1)s_{1}^{2}+(n_{2}-1)s_{2}^{2})}}},}
132:, and negative controls differ from one another. This QC characteristic can be evaluated using the comparison of two well types in HTS
6048:
Zhang XHD (2009). "A method for effectively comparing gene effects in multiple conditions in RNAi and expression-profiling research".
5349:"The use of strictly standardized mean difference for hit selection in primary RNA interference high-throughput screening experiments"
5486:
Zhang XHD, Lacson R, Yang R, Marine SD, McCampbell A, Toolan DM, Hare TR, Kajdas J, Berger JP, Holder DJ, Heyse JF, Ferrer M (2010).
2520:
based QC criterion is popularly used in HTS assays. However, it has been demonstrated that this QC criterion is most suitable for an
49:
3182:
SSMD can not only rank the size of effects but also classify effects as shown in the following table based on the population value (
71:
42:
5956:
Malo N, Hanley JA, Cerquozzi S, Pelletier J, Nadon R (2006). "Statistical practice in high-throughput screening data analysis".
1479:
6180:
5625:"A lentivirus-mediated genetic screen identifies dihydrofolate reductase (DHFR) as a modulator of beta-catenin/GSK3 signaling"
812:
112:(HTS) and has become a statistical parameter measuring effect sizes for the comparison of any two groups with random values.
5042:
Owen DB, Graswell KJ, Hanson DL (1964). "Nonparametric upper confidence bounds for P(Y < X) and confidence limits for P(
104:
of a difference between two random values each from one of two groups. It was initially proposed for quality control and
5768:
Zhou HL, Xu M, Huang Q, Gates AT, Zhang XD, Castle JC, Stec E, Ferrer M, Strulovici B, Hazuda DJ, Espeseth AS (2008).
4007:
In a primary screen without replicates, assuming the measured value (usually on the log scale) in a well for a tested
2128:. When the assumption of equal variance does not hold, the SSMD for assessing quality in that plate is estimated as
5876:"Illustration of SSMD, z Score, SSMD*, z* Score, and t Statistic for Hit Selection in RNAi High-Throughput Screens"
1745:
873:
222:
of the difference of two random values respectively from two groups. Assume that one group with random values has
5745:
Optimal High-Throughput
Screening: Practical Experimental Design and Data Analysis for Genome-scale RNAi Research
4913:
4867:
4788:
4174:
2510:
121:
109:
3517:
4868:"A pair of new statistical parameters for quality control in RNA interference high-throughput screening assays"
2079:
1334:
157:
over the S/N and S/B is that it takes into account the variabilities in both compared groups. As a result, the
5347:
Zhang XHD, Ferrer M, Espeseth AS, Marine SD, Stec EM, Crackower MA, Holder DJ, Heyse JF, Strulovici B (2007).
3825:
3556:
4500:{\displaystyle {\text{SSMD*}}={\frac {X_{i}-{\tilde {X}}_{N}}{1.4826{\tilde {s}}_{N}{\sqrt {2(n_{N}-1)/K}}}}}
3748:
3440:
4534:
replicates, we calculate the paired difference between the measured value (usually on the log scale) of the
3864:
3671:
3594:
1685:
SSMD looks similar to t-statistic and Cohen's d, but they are different with one another as illustrated in.
6083:
Zhang XHD (2010). "Assessing the size of gene or RNAi effects in multifactor high-throughput experiments".
3902:
3787:
3479:
2851:
697:
In the situation where the two groups are correlated, a commonly used strategy to avoid the calculation of
5444:"An effective method controlling false discoveries and false non-discoveries in genome-scale RNAi screens"
3938:
3710:
3633:
488:{\displaystyle \beta ={\frac {\mu _{1}-\mu _{2}}{\sqrt {\sigma _{1}^{2}+\sigma _{2}^{2}-2\sigma _{12}}}}.}
4995:"A simple statistical parameter for use in evaluation and validation of high throughput screening assays"
4340:
3363:
3286:
2968:
2929:
2890:
2807:
2768:
2729:
2690:
1806:
934:
3402:
3325:
5300:"Integrating experimental and analytic approaches to improve data quality in genome-wide RNAi screens"
4179:
4110:
1386:
In the situation where the two groups are correlated, based on a paired difference with a sample size
6175:
5679:"Experimental design and statistical methods for improved hit detection in high-throughput screening"
5246:"Novel analytic criteria and effective plate designs for quality control in genome-wide RNAi screens"
4818:
4004:
The estimation of SSMD for screens without replicates differs from that for screens with replicates.
2533:-based QC criteria to both controls leads to inconsistent results as illustrated in the literatures.
2241:{\displaystyle {\hat {\beta }}={\frac {{\bar {X}}_{P}-{\bar {X}}_{N}}{\sqrt {s_{P}^{2}+s_{N}^{2}}}}.}
1094:{\displaystyle {\hat {\beta }}={\frac {{\bar {X}}_{1}-{\bar {X}}_{2}}{\sqrt {s_{1}^{2}+s_{2}^{2}}}}.}
777:
323:
258:
4548:
4071:
3012:
3224:
2655:
2625:
2595:
2565:
359:
5488:"The use of SSMD-based false discovery and false non-discovery rates in genome-scale RNAi screens"
3254:
3102:
3072:
3042:
700:
5981:
5708:
5421:
5378:
5329:
5275:
5182:
5147:
5085:
5024:
4975:
4144:
1856:
1706:
1698:
1294:
600:
219:
101:
5103:
Church JD, Harris B (1970). "The estimation of reliability from stress-strength relationships".
1412:
5396:
Quon K, Kassner PD (2009). "RNA interference screening for the discovery of oncology targets".
4587:
1444:
6151:
6100:
6065:
6030:
5973:
5938:
5897:
5845:
5791:
5748:
5700:
5656:
5605:
5553:
5509:
5465:
5413:
5370:
5321:
5267:
5217:
5016:
4935:
4889:
4813:
4767:
4617:
4535:
4511:
4213:
4008:
3976:
3176:
3168:
3164:
3159:
3155:
3151:
1727:
1715:
750:
293:
228:
129:
5165:
Reiser B, Guttman I (1986). "Statistical inference for of Pr(Y-less-thaqn-X) - normal case".
6141:
6131:
6092:
6057:
6020:
6012:
5965:
5928:
5887:
5835:
5825:
5781:
5690:
5646:
5636:
5595:
5587:
5543:
5499:
5455:
5405:
5360:
5311:
5257:
5209:
5174:
5139:
5112:
5075:
5067:
5006:
4967:
4925:
4879:
4380:
which is usually common in HTS experiments, a robust version of SSMD can be obtained using
3185:
584:{\displaystyle \beta ={\frac {\mu _{1}-\mu _{2}}{\sqrt {\sigma _{1}^{2}+\sigma _{2}^{2}}}}.}
197:
4149:
4041:
4014:
4808:
4327:{\displaystyle {\text{SSMD}}={\frac {X_{i}-{\bar {X}}_{N}}{s_{N}{\sqrt {2(n_{N}-1)/K}}}},}
6146:
6119:
6025:
6000:
5840:
5813:
5651:
5624:
5600:
5575:
4517:
1719:
1389:
727:
48:
It may require cleanup to comply with
Knowledge (XXG)'s content policies, particularly
5814:"Genome-wide screens for effective siRNAs through assessing the size of siRNA effects"
6169:
4979:
4798:
178:
105:
5933:
5916:
5712:
5425:
5333:
5279:
5028:
5985:
5382:
5116:
5080:
2498:{\displaystyle {\tilde {X}}_{P},{\tilde {X}}_{N},{\tilde {s}}_{P},{\tilde {s}}_{N}}
5641:
3158:
and a negative reference group with no specific inhibition/activation effects. A
124:(HTS), quality control (QC) is critical. An important QC characteristic in a HTS
4884:
4783:
93:
5786:
5769:
5011:
4994:
161:
has been broadly used as a QC metric in HTS assays. The absolute sign in the
149:
when the two groups have different variabilities. Zhang JH et al. proposed the
6061:
6001:"Hit selection with false discovery rate control in genome-scale RNAi screens"
5576:"Statistical methods for analysis of high-throughput RNA interference screens"
5409:
353:
85:
5892:
5875:
5695:
5678:
5548:
5531:
5504:
5487:
5460:
5443:
5365:
5348:
5316:
5299:
5262:
5245:
4930:
6136:
5677:
Malo N, Hanley JA, Carlile G, Liu J, Pelletier J, Thomas D, Nadon R (2010).
6155:
6104:
6069:
6034:
5977:
5942:
5901:
5849:
5830:
5795:
5704:
5660:
5609:
5557:
5513:
5469:
5417:
5374:
5325:
5271:
5221:
5020:
4939:
4893:
4971:
165:
makes it inconvenient to derive its statistical inference mathematically.
6016:
4831:
4793:
4582:
2530:
2517:
1801:
1439:
1105:
929:
595:
318:
253:
162:
158:
154:
150:
137:
136:. Signal-to-noise ratio (S/N), signal-to-background ratio (S/B), and the
5770:"Genome-scale RNAi screen for host factors required for HIV replication"
6096:
5591:
5186:
5151:
5089:
4510:
In a confirmatory or primary screen with replicates, for the i-th test
2252:
1108:, the uniformly minimal variance unbiased estimate (UMVUE) of SSMD is,
687:{\displaystyle \beta ={\frac {\mu _{1}-\mu _{2}}{{\sqrt {2}}\sigma }}.}
5213:
4539:
4105:
2506:
5969:
5178:
5143:
5071:
386:
Then, the SSMD for the comparison of these two groups is defined as
17:
5130:
Downton F (1973). "The estimation of Pr(Y < X) in normal case".
4771:
4377:
3172:
3135:
2521:
1723:
1711:
146:
141:
133:
125:
3167:
by their effects and then to select the largest number of potent
4803:
4543:
4066:
2525:
1740:
1702:
1694:
1407:
868:
745:
288:
223:
215:
97:
5569:
5567:
4616:
of the paired difference across replicates. The SSMD for this
26:
1726:) is represented by the magnitude of difference between the
5917:"Determination of sample size in genome-scale RNAi screens"
1528:{\displaystyle {\hat {\beta }}={\frac {\bar {D}}{s_{D}}}.}
4038:
and the negative reference in that plate has sample size
1104:
When the two groups have normal distributions with equal
4542:
value of a negative control in a plate, then obtain the
2524:
with very or extremely strong positive controls. In an
852:{\displaystyle \beta ={\frac {\mu _{D}}{\sigma _{D}}}.}
41:
A major contributor to this article appears to have a
4629:
4590:
4551:
4520:
4389:
4343:
4225:
4182:
4152:
4113:
4074:
4044:
4017:
3979:
3941:
3905:
3867:
3828:
3790:
3751:
3713:
3674:
3636:
3597:
3559:
3520:
3482:
3443:
3405:
3366:
3328:
3289:
3257:
3227:
3188:
3105:
3075:
3045:
3015:
2971:
2932:
2893:
2854:
2810:
2771:
2732:
2693:
2658:
2628:
2598:
2568:
2513:
in the positive and negative controls, respectively.
2409:
2264:
2137:
2082:
1902:
1859:
1809:
1748:
1547:
1482:
1447:
1415:
1392:
1337:
1297:
1117:
990:
937:
876:
815:
780:
753:
730:
703:
633:
603:
507:
395:
362:
326:
296:
261:
231:
200:
5532:"Error rates and power in genome-scale RNAi screens"
5525:
5523:
5481:
5479:
5293:
5291:
5289:
4861:
4859:
4857:
4855:
4853:
4851:
4849:
4847:
1714:plate. For hit selection, the size of effects of a
4755:
4608:
4573:
4526:
4499:
4368:
4326:
4204:
4165:
4135:
4096:
4057:
4030:
3991:
3959:
3926:
3885:
3852:
3808:
3775:
3731:
3698:
3654:
3621:
3577:
3544:
3500:
3467:
3423:
3390:
3346:
3313:
3269:
3242:
3194:
3120:
3090:
3060:
3030:
2995:
2956:
2917:
2878:
2834:
2795:
2756:
2717:
2673:
2643:
2613:
2583:
2497:
2392:
2240:
2120:
2065:
1885:
1845:
1792:
1674:
1527:
1465:
1430:
1398:
1375:
1323:
1280:
1093:
973:
920:
851:
798:
766:
736:
716:
686:
616:
583:
487:
378:
344:
309:
279:
244:
206:
5807:
5805:
140:have been adopted to evaluate the quality of HTS
5738:
5736:
5734:
5732:
5730:
5728:
5726:
5724:
5722:
5869:
5867:
5865:
5863:
5861:
5859:
5437:
5435:
5239:
5237:
5235:
5233:
5231:
5060:Journal of the American Statistical Association
3150:In an HTS assay, one primary goal is to select
1689:Application in high-throughput screening assays
4953:
4951:
4949:
4907:
4905:
4903:
2255:in the controls, the SSMD can be estimated as
1793:{\displaystyle {\bar {X}}_{P},{\bar {X}}_{N}}
921:{\displaystyle {\bar {X}}_{1},{\bar {X}}_{2}}
194:As a statistical parameter, SSMD (denoted as
8:
90:strictly standardized mean difference (SSMD)
5672:
5670:
1331:are the sample sizes in the two groups and
4993:Zhang JH, Chung TDY, Oldenburg KR (1999).
3545:{\displaystyle -1.645<\beta \leq -1.28}
3175:. The other strategy is to test whether a
6145:
6135:
6024:
5932:
5891:
5839:
5829:
5785:
5694:
5650:
5640:
5599:
5547:
5503:
5459:
5364:
5315:
5261:
5079:
5010:
4929:
4883:
4745:
4735:
4724:
4723:
4720:
4700:
4676:
4647:
4638:
4630:
4628:
4600:
4595:
4589:
4565:
4554:
4553:
4550:
4519:
4484:
4469:
4457:
4451:
4440:
4439:
4427:
4416:
4415:
4405:
4398:
4390:
4388:
4354:
4342:
4308:
4293:
4281:
4275:
4263:
4252:
4251:
4241:
4234:
4226:
4224:
4196:
4185:
4184:
4181:
4157:
4151:
4127:
4116:
4115:
4112:
4088:
4077:
4076:
4073:
4049:
4043:
4022:
4016:
3978:
3940:
3904:
3866:
3827:
3789:
3750:
3712:
3673:
3635:
3596:
3558:
3519:
3481:
3442:
3404:
3365:
3327:
3288:
3256:
3226:
3187:
3104:
3074:
3044:
3014:
2970:
2931:
2892:
2853:
2809:
2770:
2731:
2692:
2657:
2627:
2597:
2567:
2489:
2478:
2477:
2467:
2456:
2455:
2445:
2434:
2433:
2423:
2412:
2411:
2408:
2376:
2371:
2360:
2359:
2349:
2344:
2333:
2332:
2329:
2318:
2307:
2306:
2296:
2285:
2284:
2280:
2266:
2265:
2263:
2226:
2221:
2208:
2203:
2191:
2180:
2179:
2169:
2158:
2157:
2153:
2139:
2138:
2136:
2121:{\displaystyle K\approx n_{P}+n_{N}-3.48}
2106:
2093:
2081:
2048:
2043:
2024:
2008:
2003:
1984:
1964:
1956:
1945:
1944:
1934:
1923:
1922:
1918:
1904:
1903:
1901:
1877:
1864:
1858:
1837:
1832:
1819:
1814:
1808:
1784:
1773:
1772:
1762:
1751:
1750:
1747:
1661:
1647:
1645:
1625:
1601:
1572:
1563:
1549:
1548:
1546:
1514:
1500:
1498:
1484:
1483:
1481:
1457:
1452:
1446:
1417:
1416:
1414:
1391:
1376:{\displaystyle K\approx n_{1}+n_{2}-3.48}
1361:
1348:
1336:
1315:
1302:
1296:
1263:
1258:
1239:
1223:
1218:
1199:
1179:
1171:
1160:
1159:
1149:
1138:
1137:
1133:
1119:
1118:
1116:
1079:
1074:
1061:
1056:
1044:
1033:
1032:
1022:
1011:
1010:
1006:
992:
991:
989:
965:
960:
947:
942:
936:
912:
901:
900:
890:
879:
878:
875:
838:
828:
822:
814:
790:
785:
779:
758:
752:
729:
708:
702:
668:
660:
647:
640:
632:
608:
602:
594:If the two independent groups have equal
569:
564:
551:
546:
534:
521:
514:
506:
473:
457:
452:
439:
434:
422:
409:
402:
394:
367:
361:
336:
331:
325:
301:
295:
271:
266:
260:
236:
230:
199:
72:Learn how and when to remove this message
4960:Statistics in Biopharmaceutical Research
3853:{\displaystyle -0.5\leq \beta <-0.25}
3578:{\displaystyle 1.645>\beta \geq 1.28}
3204:
2539:
128:is how much the positive controls, test
5530:Zhang XHD, Marine SD, Ferrer M (2009).
4843:
3776:{\displaystyle -0.75<\beta <-0.5}
3468:{\displaystyle -2<\beta \leq -1.645}
1710:control and a negative reference in an
3886:{\displaystyle 0.5\geq \beta >0.25}
3699:{\displaystyle -1<\beta \leq -0.75}
3622:{\displaystyle -1.28<\beta \leq -1}
5398:Expert Opinion on Therapeutic Targets
3927:{\displaystyle -0.25\leq \beta <0}
3809:{\displaystyle 0.75>\beta >0.5}
3501:{\displaystyle 2>\beta \geq 1.645}
2879:{\displaystyle -1<\beta \leq -0.5}
7:
3960:{\displaystyle 0.25\geq \beta >0}
3732:{\displaystyle 1>\beta \geq 0.75}
3655:{\displaystyle 1.28>\beta \geq 1}
4369:{\displaystyle K\approx n_{N}-2.48}
3391:{\displaystyle -3<\beta \leq -2}
3314:{\displaystyle -5<\beta \leq -3}
2996:{\displaystyle -5<\beta \leq -3}
2957:{\displaystyle -3<\beta \leq -2}
2918:{\displaystyle -2<\beta \leq -1}
2835:{\displaystyle -7<\beta \leq -5}
2796:{\displaystyle -5<\beta \leq -3}
2757:{\displaystyle -3<\beta \leq -2}
2718:{\displaystyle -2<\beta \leq -1}
1846:{\displaystyle s_{P}^{2},s_{N}^{2}}
974:{\displaystyle s_{1}^{2},s_{2}^{2}}
498:If the two groups are independent,
4670:
4641:
1705:of log fold change divided by the
1595:
1566:
981:. The MM estimate of SSMD is then
25:
5880:Journal of Biomolecular Screening
5683:Journal of Biomolecular Screening
5536:Journal of Biomolecular Screening
5492:Journal of Biomolecular Screening
5448:Journal of Biomolecular Screening
5353:Journal of Biomolecular Screening
5304:Journal of Biomolecular Screening
5250:Journal of Biomolecular Screening
4999:Journal of Biomolecular Screening
4918:Journal of Biomolecular Screening
3424:{\displaystyle 3>\beta \geq 2}
3347:{\displaystyle 5>\beta \geq 3}
3171:that is practical for validation
4376:. When there are outliers in an
4205:{\displaystyle {\tilde {s}}_{N}}
4136:{\displaystyle {\tilde {X}}_{N}}
52:. Please discuss further on the
31:
6124:Journal of Biological Chemistry
799:{\displaystyle \sigma _{D}^{2}}
345:{\displaystyle \sigma _{2}^{2}}
280:{\displaystyle \sigma _{1}^{2}}
5747:. Cambridge University Press.
5117:10.1080/00401706.1970.10488633
4729:
4694:
4673:
4665:
4644:
4574:{\displaystyle {\bar {d}}_{i}}
4559:
4481:
4462:
4445:
4421:
4305:
4286:
4257:
4190:
4121:
4097:{\displaystyle {\bar {X}}_{N}}
4082:
3031:{\displaystyle \beta >-0.5}
2483:
2461:
2439:
2417:
2365:
2338:
2312:
2290:
2271:
2185:
2163:
2144:
2054:
2036:
2017:
1996:
1977:
1974:
1950:
1928:
1909:
1778:
1756:
1652:
1619:
1598:
1590:
1569:
1554:
1538:The UMVUE estimate of SSMD is
1505:
1489:
1422:
1269:
1251:
1232:
1211:
1192:
1189:
1165:
1143:
1124:
1038:
1016:
997:
906:
884:
181:in high-throughput screening.
1:
5934:10.1093/bioinformatics/btp082
3243:{\displaystyle \beta \leq -5}
3214:Thresholds for positive SSMD
2674:{\displaystyle \beta \leq -7}
2644:{\displaystyle \beta \leq -5}
2614:{\displaystyle \beta \leq -3}
2584:{\displaystyle \beta \leq -2}
1473:, the MM estimate of SSMD is
379:{\displaystyle \sigma _{12}.}
214:) is defined as the ratio of
5915:Zhang XHD, Heyse JF (2009).
5642:10.1371/journal.pone.0006892
3270:{\displaystyle \beta \geq 5}
3211:Thresholds for negative SSMD
3121:{\displaystyle \beta >-3}
3091:{\displaystyle \beta >-2}
3061:{\displaystyle \beta >-1}
2555:D: Extremely Strong Control
717:{\displaystyle \sigma _{12}}
4885:10.1016/j.ygeno.2006.12.014
1886:{\displaystyle n_{P},n_{N}}
1324:{\displaystyle n_{1},n_{2}}
617:{\displaystyle \sigma ^{2}}
6197:
5787:10.1016/j.chom.2008.10.004
5012:10.1177/108705719900400206
2511:median absolute deviations
1431:{\displaystyle {\bar {D}}}
356:between the two groups is
6062:10.2217/14622416.10.3.345
5410:10.1517/14728220903179338
4789:high-throughput screening
4609:{\displaystyle s_{i}^{2}}
4175:median absolute deviation
1466:{\displaystyle s_{D}^{2}}
122:high-throughput screening
110:high-throughput screening
5893:10.1177/1087057111405851
5696:10.1177/1087057110377497
5549:10.1177/1087057109331475
5505:10.1177/1087057110381919
5461:10.1177/1087057110381783
5366:10.1177/1087057107300646
5317:10.1177/1087057108317145
5263:10.1177/1087057108317062
4931:10.1177/1087057107300645
3992:{\displaystyle \beta =0}
767:{\displaystyle \mu _{D}}
310:{\displaystyle \mu _{2}}
245:{\displaystyle \mu _{1}}
6137:10.1074/jbc.M109.057182
5774:Cell Host & Microbe
5081:2027/mdp.39015094992651
153:. The advantage of the
6181:Descriptive statistics
6005:Nucleic Acids Research
5831:10.1186/1756-0500-1-33
5202:Statistics in Medicine
4757:
4610:
4575:
4528:
4501:
4370:
4328:
4206:
4167:
4137:
4098:
4059:
4032:
3993:
3961:
3928:
3887:
3854:
3810:
3777:
3733:
3700:
3656:
3623:
3579:
3546:
3502:
3469:
3425:
3392:
3348:
3315:
3271:
3244:
3196:
3195:{\displaystyle \beta }
3122:
3092:
3062:
3032:
2997:
2958:
2919:
2880:
2836:
2797:
2758:
2719:
2675:
2645:
2615:
2585:
2552:C: Very Strong Control
2499:
2394:
2242:
2122:
2067:
1887:
1847:
1794:
1676:
1529:
1467:
1432:
1400:
1377:
1325:
1282:
1095:
975:
922:
863:Statistical estimation
853:
800:
768:
738:
718:
688:
618:
585:
489:
380:
346:
311:
287:and another group has
281:
246:
208:
207:{\displaystyle \beta }
4972:10.1198/sbr.2009.0074
4758:
4611:
4576:
4529:
4502:
4371:
4329:
4207:
4168:
4166:{\displaystyle s_{N}}
4138:
4099:
4060:
4058:{\displaystyle n_{N}}
4033:
4031:{\displaystyle X_{i}}
3994:
3962:
3929:
3888:
3855:
3811:
3778:
3734:
3701:
3657:
3624:
3580:
3547:
3503:
3470:
3426:
3393:
3349:
3316:
3272:
3245:
3197:
3123:
3093:
3063:
3033:
2998:
2959:
2920:
2881:
2837:
2798:
2759:
2720:
2676:
2646:
2616:
2586:
2500:
2395:
2251:If there are clearly
2243:
2123:
2068:
1888:
1848:
1795:
1693:SSMD is the ratio of
1677:
1530:
1468:
1433:
1401:
1378:
1326:
1283:
1096:
976:
923:
854:
801:
769:
739:
719:
689:
619:
586:
490:
381:
347:
312:
282:
247:
209:
190:Statistical parameter
50:neutral point of view
5958:Nature Biotechnology
4819:Dual-flashlight plot
4627:
4588:
4549:
4518:
4387:
4341:
4223:
4212:, the SSMD for this
4180:
4150:
4111:
4072:
4042:
4015:
3977:
3939:
3903:
3865:
3826:
3788:
3749:
3711:
3672:
3634:
3595:
3557:
3518:
3480:
3441:
3403:
3364:
3326:
3287:
3255:
3225:
3186:
3103:
3073:
3043:
3013:
2969:
2930:
2891:
2852:
2808:
2769:
2730:
2691:
2656:
2626:
2596:
2566:
2407:
2262:
2135:
2080:
1900:
1857:
1807:
1746:
1545:
1480:
1445:
1413:
1390:
1335:
1295:
1115:
988:
935:
874:
813:
778:
751:
728:
701:
631:
601:
505:
393:
360:
324:
294:
259:
229:
198:
4605:
2546:A: Moderate Control
2381:
2354:
2231:
2213:
2053:
2013:
1853:, and sample sizes
1842:
1824:
1462:
1268:
1228:
1084:
1066:
970:
952:
795:
574:
556:
462:
444:
341:
276:
6097:10.2217/PGS.09.136
6017:10.1093/nar/gkn435
5874:Zhang XHD (2011).
5818:BMC Research Notes
5812:Zhang XHD (2010).
5743:Zhang XHD (2011).
5592:10.1038/nmeth.1351
5442:Zhang XHD (2010).
5244:Zhang XHD (2008).
4912:Zhang XHD (2007).
4866:Zhang XHD (2007).
4753:
4606:
4591:
4571:
4524:
4497:
4366:
4324:
4202:
4163:
4145:standard deviation
4133:
4094:
4055:
4028:
3989:
3957:
3924:
3883:
3850:
3806:
3773:
3729:
3696:
3652:
3619:
3575:
3542:
3498:
3465:
3421:
3388:
3344:
3311:
3267:
3240:
3192:
3118:
3088:
3058:
3028:
2993:
2954:
2915:
2876:
2832:
2793:
2754:
2715:
2671:
2641:
2611:
2581:
2495:
2390:
2358:
2331:
2238:
2217:
2199:
2118:
2063:
2039:
1999:
1883:
1843:
1828:
1810:
1790:
1707:standard deviation
1699:standard deviation
1672:
1525:
1463:
1448:
1428:
1396:
1373:
1321:
1278:
1254:
1214:
1091:
1070:
1052:
971:
956:
938:
918:
849:
796:
781:
764:
734:
714:
684:
614:
581:
560:
542:
485:
448:
430:
376:
342:
327:
307:
277:
262:
242:
220:standard deviation
204:
102:standard deviation
5754:978-0-521-73444-8
4830:Zhang XHD (2011)
4814:Contrast variable
4751:
4732:
4718:
4717:
4698:
4692:
4663:
4633:
4562:
4527:{\displaystyle n}
4495:
4492:
4448:
4424:
4393:
4319:
4316:
4260:
4229:
4193:
4124:
4085:
4002:
4001:
3131:
3130:
2549:B: Strong Control
2486:
2464:
2442:
2420:
2385:
2382:
2368:
2341:
2315:
2293:
2274:
2233:
2232:
2188:
2166:
2147:
2058:
2057:
1972:
1953:
1931:
1912:
1781:
1759:
1667:
1655:
1643:
1642:
1623:
1617:
1588:
1557:
1520:
1508:
1492:
1425:
1399:{\displaystyle n}
1273:
1272:
1187:
1168:
1146:
1127:
1086:
1085:
1041:
1019:
1000:
909:
887:
844:
737:{\displaystyle D}
679:
673:
576:
575:
480:
479:
82:
81:
74:
45:with its subject.
16:(Redirected from
6188:
6160:
6159:
6149:
6139:
6115:
6109:
6108:
6085:Pharmacogenomics
6080:
6074:
6073:
6050:Pharmacogenomics
6045:
6039:
6038:
6028:
5996:
5990:
5989:
5953:
5947:
5946:
5936:
5912:
5906:
5905:
5895:
5871:
5854:
5853:
5843:
5833:
5809:
5800:
5799:
5789:
5765:
5759:
5758:
5740:
5717:
5716:
5698:
5674:
5665:
5664:
5654:
5644:
5620:
5614:
5613:
5603:
5571:
5562:
5561:
5551:
5527:
5518:
5517:
5507:
5483:
5474:
5473:
5463:
5439:
5430:
5429:
5393:
5387:
5386:
5368:
5344:
5338:
5337:
5319:
5295:
5284:
5283:
5265:
5241:
5226:
5225:
5214:10.1002/sim.2256
5197:
5191:
5190:
5162:
5156:
5155:
5127:
5121:
5120:
5100:
5094:
5093:
5083:
5046: <
5039:
5033:
5032:
5014:
4990:
4984:
4983:
4955:
4944:
4943:
4933:
4909:
4898:
4897:
4887:
4863:
4762:
4760:
4759:
4754:
4752:
4750:
4749:
4740:
4739:
4734:
4733:
4725:
4721:
4719:
4716:
4702:
4701:
4699:
4697:
4693:
4688:
4677:
4668:
4664:
4659:
4648:
4639:
4634:
4631:
4620:is estimated as
4615:
4613:
4612:
4607:
4604:
4599:
4580:
4578:
4577:
4572:
4570:
4569:
4564:
4563:
4555:
4533:
4531:
4530:
4525:
4506:
4504:
4503:
4498:
4496:
4494:
4493:
4488:
4474:
4473:
4458:
4456:
4455:
4450:
4449:
4441:
4433:
4432:
4431:
4426:
4425:
4417:
4410:
4409:
4399:
4394:
4391:
4375:
4373:
4372:
4367:
4359:
4358:
4333:
4331:
4330:
4325:
4320:
4318:
4317:
4312:
4298:
4297:
4282:
4280:
4279:
4269:
4268:
4267:
4262:
4261:
4253:
4246:
4245:
4235:
4230:
4227:
4216:is estimated as
4211:
4209:
4208:
4203:
4201:
4200:
4195:
4194:
4186:
4172:
4170:
4169:
4164:
4162:
4161:
4142:
4140:
4139:
4134:
4132:
4131:
4126:
4125:
4117:
4103:
4101:
4100:
4095:
4093:
4092:
4087:
4086:
4078:
4064:
4062:
4061:
4056:
4054:
4053:
4037:
4035:
4034:
4029:
4027:
4026:
3998:
3996:
3995:
3990:
3966:
3964:
3963:
3958:
3933:
3931:
3930:
3925:
3892:
3890:
3889:
3884:
3859:
3857:
3856:
3851:
3815:
3813:
3812:
3807:
3782:
3780:
3779:
3774:
3738:
3736:
3735:
3730:
3705:
3703:
3702:
3697:
3661:
3659:
3658:
3653:
3628:
3626:
3625:
3620:
3584:
3582:
3581:
3576:
3551:
3549:
3548:
3543:
3507:
3505:
3504:
3499:
3474:
3472:
3471:
3466:
3430:
3428:
3427:
3422:
3397:
3395:
3394:
3389:
3353:
3351:
3350:
3345:
3320:
3318:
3317:
3312:
3276:
3274:
3273:
3268:
3249:
3247:
3246:
3241:
3219:Extremely strong
3205:
3201:
3199:
3198:
3193:
3127:
3125:
3124:
3119:
3097:
3095:
3094:
3089:
3067:
3065:
3064:
3059:
3037:
3035:
3034:
3029:
3002:
3000:
2999:
2994:
2963:
2961:
2960:
2955:
2924:
2922:
2921:
2916:
2885:
2883:
2882:
2877:
2841:
2839:
2838:
2833:
2802:
2800:
2799:
2794:
2763:
2761:
2760:
2755:
2724:
2722:
2721:
2716:
2680:
2678:
2677:
2672:
2650:
2648:
2647:
2642:
2620:
2618:
2617:
2612:
2590:
2588:
2587:
2582:
2540:
2504:
2502:
2501:
2496:
2494:
2493:
2488:
2487:
2479:
2472:
2471:
2466:
2465:
2457:
2450:
2449:
2444:
2443:
2435:
2428:
2427:
2422:
2421:
2413:
2399:
2397:
2396:
2391:
2386:
2384:
2383:
2380:
2375:
2370:
2369:
2361:
2353:
2348:
2343:
2342:
2334:
2330:
2324:
2323:
2322:
2317:
2316:
2308:
2301:
2300:
2295:
2294:
2286:
2281:
2276:
2275:
2267:
2247:
2245:
2244:
2239:
2234:
2230:
2225:
2212:
2207:
2198:
2197:
2196:
2195:
2190:
2189:
2181:
2174:
2173:
2168:
2167:
2159:
2154:
2149:
2148:
2140:
2127:
2125:
2124:
2119:
2111:
2110:
2098:
2097:
2072:
2070:
2069:
2064:
2059:
2052:
2047:
2029:
2028:
2012:
2007:
1989:
1988:
1973:
1965:
1963:
1962:
1961:
1960:
1955:
1954:
1946:
1939:
1938:
1933:
1932:
1924:
1919:
1914:
1913:
1905:
1892:
1890:
1889:
1884:
1882:
1881:
1869:
1868:
1852:
1850:
1849:
1844:
1841:
1836:
1823:
1818:
1799:
1797:
1796:
1791:
1789:
1788:
1783:
1782:
1774:
1767:
1766:
1761:
1760:
1752:
1681:
1679:
1678:
1673:
1668:
1666:
1665:
1656:
1648:
1646:
1644:
1641:
1627:
1626:
1624:
1622:
1618:
1613:
1602:
1593:
1589:
1584:
1573:
1564:
1559:
1558:
1550:
1534:
1532:
1531:
1526:
1521:
1519:
1518:
1509:
1501:
1499:
1494:
1493:
1485:
1472:
1470:
1469:
1464:
1461:
1456:
1437:
1435:
1434:
1429:
1427:
1426:
1418:
1405:
1403:
1402:
1397:
1382:
1380:
1379:
1374:
1366:
1365:
1353:
1352:
1330:
1328:
1327:
1322:
1320:
1319:
1307:
1306:
1287:
1285:
1284:
1279:
1274:
1267:
1262:
1244:
1243:
1227:
1222:
1204:
1203:
1188:
1180:
1178:
1177:
1176:
1175:
1170:
1169:
1161:
1154:
1153:
1148:
1147:
1139:
1134:
1129:
1128:
1120:
1100:
1098:
1097:
1092:
1087:
1083:
1078:
1065:
1060:
1051:
1050:
1049:
1048:
1043:
1042:
1034:
1027:
1026:
1021:
1020:
1012:
1007:
1002:
1001:
993:
980:
978:
977:
972:
969:
964:
951:
946:
927:
925:
924:
919:
917:
916:
911:
910:
902:
895:
894:
889:
888:
880:
858:
856:
855:
850:
845:
843:
842:
833:
832:
823:
805:
803:
802:
797:
794:
789:
773:
771:
770:
765:
763:
762:
744:with population
743:
741:
740:
735:
723:
721:
720:
715:
713:
712:
693:
691:
690:
685:
680:
678:
674:
669:
666:
665:
664:
652:
651:
641:
623:
621:
620:
615:
613:
612:
590:
588:
587:
582:
577:
573:
568:
555:
550:
541:
540:
539:
538:
526:
525:
515:
494:
492:
491:
486:
481:
478:
477:
461:
456:
443:
438:
429:
428:
427:
426:
414:
413:
403:
385:
383:
382:
377:
372:
371:
351:
349:
348:
343:
340:
335:
316:
314:
313:
308:
306:
305:
286:
284:
283:
278:
275:
270:
251:
249:
248:
243:
241:
240:
213:
211:
210:
205:
173: >
92:is a measure of
77:
70:
66:
63:
57:
43:close connection
35:
34:
27:
21:
6196:
6195:
6191:
6190:
6189:
6187:
6186:
6185:
6166:
6165:
6164:
6163:
6130:(10): 7619–32.
6117:
6116:
6112:
6082:
6081:
6077:
6047:
6046:
6042:
6011:(14): 4667–79.
5998:
5997:
5993:
5970:10.1038/nbt1186
5955:
5954:
5950:
5914:
5913:
5909:
5873:
5872:
5857:
5811:
5810:
5803:
5767:
5766:
5762:
5755:
5742:
5741:
5720:
5689:(8): 990–1000.
5676:
5675:
5668:
5622:
5621:
5617:
5573:
5572:
5565:
5529:
5528:
5521:
5485:
5484:
5477:
5441:
5440:
5433:
5395:
5394:
5390:
5346:
5345:
5341:
5297:
5296:
5287:
5243:
5242:
5229:
5199:
5198:
5194:
5179:10.2307/1269081
5164:
5163:
5159:
5144:10.2307/1266860
5129:
5128:
5124:
5102:
5101:
5097:
5072:10.2307/2283110
5066:(307): 906–24.
5041:
5040:
5036:
4992:
4991:
4987:
4957:
4956:
4947:
4911:
4910:
4901:
4865:
4864:
4845:
4840:
4827:
4825:Further reading
4780:
4741:
4722:
4706:
4678:
4669:
4649:
4640:
4625:
4624:
4586:
4585:
4552:
4547:
4546:
4516:
4515:
4465:
4438:
4434:
4414:
4401:
4400:
4385:
4384:
4350:
4339:
4338:
4289:
4271:
4270:
4250:
4237:
4236:
4221:
4220:
4183:
4178:
4177:
4153:
4148:
4147:
4114:
4109:
4108:
4075:
4070:
4069:
4045:
4040:
4039:
4018:
4013:
4012:
3975:
3974:
3937:
3936:
3901:
3900:
3863:
3862:
3824:
3823:
3786:
3785:
3747:
3746:
3709:
3708:
3670:
3669:
3632:
3631:
3593:
3592:
3589:Fairly moderate
3555:
3554:
3516:
3515:
3478:
3477:
3439:
3438:
3401:
3400:
3362:
3361:
3324:
3323:
3285:
3284:
3253:
3252:
3223:
3222:
3184:
3183:
3148:
3101:
3100:
3071:
3070:
3041:
3040:
3011:
3010:
2967:
2966:
2928:
2927:
2889:
2888:
2850:
2849:
2806:
2805:
2767:
2766:
2728:
2727:
2689:
2688:
2654:
2653:
2624:
2623:
2594:
2593:
2564:
2563:
2476:
2454:
2432:
2410:
2405:
2404:
2325:
2305:
2283:
2282:
2260:
2259:
2178:
2156:
2155:
2133:
2132:
2102:
2089:
2078:
2077:
2020:
1980:
1943:
1921:
1920:
1898:
1897:
1873:
1860:
1855:
1854:
1805:
1804:
1771:
1749:
1744:
1743:
1736:
1734:Quality control
1691:
1657:
1631:
1603:
1594:
1574:
1565:
1543:
1542:
1510:
1478:
1477:
1443:
1442:
1411:
1410:
1388:
1387:
1357:
1344:
1333:
1332:
1311:
1298:
1293:
1292:
1235:
1195:
1158:
1136:
1135:
1113:
1112:
1031:
1009:
1008:
986:
985:
933:
932:
928:, and sample
899:
877:
872:
871:
865:
834:
824:
811:
810:
776:
775:
754:
749:
748:
726:
725:
704:
699:
698:
667:
656:
643:
642:
629:
628:
604:
599:
598:
530:
517:
516:
503:
502:
469:
418:
405:
404:
391:
390:
363:
358:
357:
322:
321:
297:
292:
291:
257:
256:
232:
227:
226:
196:
195:
192:
187:
118:
100:divided by the
78:
67:
61:
58:
47:
36:
32:
23:
22:
15:
12:
11:
5:
6194:
6192:
6184:
6183:
6178:
6168:
6167:
6162:
6161:
6110:
6091:(2): 199–213.
6075:
6040:
5991:
5948:
5921:Bioinformatics
5907:
5855:
5801:
5780:(5): 495–504.
5760:
5753:
5718:
5666:
5615:
5580:Nature Methods
5563:
5519:
5498:(9): 1123–31.
5475:
5454:(9): 1116–22.
5431:
5404:(9): 1027–35.
5388:
5339:
5285:
5227:
5208:(4): 591–602.
5192:
5157:
5122:
5095:
5034:
4985:
4945:
4899:
4842:
4841:
4839:
4836:
4835:
4834:
4826:
4823:
4822:
4821:
4816:
4811:
4806:
4801:
4796:
4791:
4786:
4779:
4776:
4764:
4763:
4748:
4744:
4738:
4731:
4728:
4715:
4712:
4709:
4705:
4696:
4691:
4687:
4684:
4681:
4675:
4672:
4667:
4662:
4658:
4655:
4652:
4646:
4643:
4637:
4603:
4598:
4594:
4568:
4561:
4558:
4523:
4508:
4507:
4491:
4487:
4483:
4480:
4477:
4472:
4468:
4464:
4461:
4454:
4447:
4444:
4437:
4430:
4423:
4420:
4413:
4408:
4404:
4397:
4365:
4362:
4357:
4353:
4349:
4346:
4335:
4334:
4323:
4315:
4311:
4307:
4304:
4301:
4296:
4292:
4288:
4285:
4278:
4274:
4266:
4259:
4256:
4249:
4244:
4240:
4233:
4199:
4192:
4189:
4160:
4156:
4130:
4123:
4120:
4091:
4084:
4081:
4052:
4048:
4025:
4021:
4000:
3999:
3988:
3985:
3982:
3972:
3968:
3967:
3956:
3953:
3950:
3947:
3944:
3934:
3923:
3920:
3917:
3914:
3911:
3908:
3898:
3897:Extremely weak
3894:
3893:
3882:
3879:
3876:
3873:
3870:
3860:
3849:
3846:
3843:
3840:
3837:
3834:
3831:
3821:
3817:
3816:
3805:
3802:
3799:
3796:
3793:
3783:
3772:
3769:
3766:
3763:
3760:
3757:
3754:
3744:
3740:
3739:
3728:
3725:
3722:
3719:
3716:
3706:
3695:
3692:
3689:
3686:
3683:
3680:
3677:
3667:
3663:
3662:
3651:
3648:
3645:
3642:
3639:
3629:
3618:
3615:
3612:
3609:
3606:
3603:
3600:
3590:
3586:
3585:
3574:
3571:
3568:
3565:
3562:
3552:
3541:
3538:
3535:
3532:
3529:
3526:
3523:
3513:
3509:
3508:
3497:
3494:
3491:
3488:
3485:
3475:
3464:
3461:
3458:
3455:
3452:
3449:
3446:
3436:
3432:
3431:
3420:
3417:
3414:
3411:
3408:
3398:
3387:
3384:
3381:
3378:
3375:
3372:
3369:
3359:
3355:
3354:
3343:
3340:
3337:
3334:
3331:
3321:
3310:
3307:
3304:
3301:
3298:
3295:
3292:
3282:
3278:
3277:
3266:
3263:
3260:
3250:
3239:
3236:
3233:
3230:
3220:
3216:
3215:
3212:
3209:
3208:Effect subtype
3191:
3147:
3144:
3129:
3128:
3117:
3114:
3111:
3108:
3098:
3087:
3084:
3081:
3078:
3068:
3057:
3054:
3051:
3048:
3038:
3027:
3024:
3021:
3018:
3008:
3004:
3003:
2992:
2989:
2986:
2983:
2980:
2977:
2974:
2964:
2953:
2950:
2947:
2944:
2941:
2938:
2935:
2925:
2914:
2911:
2908:
2905:
2902:
2899:
2896:
2886:
2875:
2872:
2869:
2866:
2863:
2860:
2857:
2847:
2843:
2842:
2831:
2828:
2825:
2822:
2819:
2816:
2813:
2803:
2792:
2789:
2786:
2783:
2780:
2777:
2774:
2764:
2753:
2750:
2747:
2744:
2741:
2738:
2735:
2725:
2714:
2711:
2708:
2705:
2702:
2699:
2696:
2686:
2682:
2681:
2670:
2667:
2664:
2661:
2651:
2640:
2637:
2634:
2631:
2621:
2610:
2607:
2604:
2601:
2591:
2580:
2577:
2574:
2571:
2561:
2557:
2556:
2553:
2550:
2547:
2544:
2492:
2485:
2482:
2475:
2470:
2463:
2460:
2453:
2448:
2441:
2438:
2431:
2426:
2419:
2416:
2401:
2400:
2389:
2379:
2374:
2367:
2364:
2357:
2352:
2347:
2340:
2337:
2328:
2321:
2314:
2311:
2304:
2299:
2292:
2289:
2279:
2273:
2270:
2249:
2248:
2237:
2229:
2224:
2220:
2216:
2211:
2206:
2202:
2194:
2187:
2184:
2177:
2172:
2165:
2162:
2152:
2146:
2143:
2117:
2114:
2109:
2105:
2101:
2096:
2092:
2088:
2085:
2074:
2073:
2062:
2056:
2051:
2046:
2042:
2038:
2035:
2032:
2027:
2023:
2019:
2016:
2011:
2006:
2002:
1998:
1995:
1992:
1987:
1983:
1979:
1976:
1971:
1968:
1959:
1952:
1949:
1942:
1937:
1930:
1927:
1917:
1911:
1908:
1880:
1876:
1872:
1867:
1863:
1840:
1835:
1831:
1827:
1822:
1817:
1813:
1787:
1780:
1777:
1770:
1765:
1758:
1755:
1735:
1732:
1720:small molecule
1690:
1687:
1683:
1682:
1671:
1664:
1660:
1654:
1651:
1640:
1637:
1634:
1630:
1621:
1616:
1612:
1609:
1606:
1600:
1597:
1592:
1587:
1583:
1580:
1577:
1571:
1568:
1562:
1556:
1553:
1536:
1535:
1524:
1517:
1513:
1507:
1504:
1497:
1491:
1488:
1460:
1455:
1451:
1424:
1421:
1395:
1372:
1369:
1364:
1360:
1356:
1351:
1347:
1343:
1340:
1318:
1314:
1310:
1305:
1301:
1289:
1288:
1277:
1271:
1266:
1261:
1257:
1253:
1250:
1247:
1242:
1238:
1234:
1231:
1226:
1221:
1217:
1213:
1210:
1207:
1202:
1198:
1194:
1191:
1186:
1183:
1174:
1167:
1164:
1157:
1152:
1145:
1142:
1132:
1126:
1123:
1102:
1101:
1090:
1082:
1077:
1073:
1069:
1064:
1059:
1055:
1047:
1040:
1037:
1030:
1025:
1018:
1015:
1005:
999:
996:
968:
963:
959:
955:
950:
945:
941:
915:
908:
905:
898:
893:
886:
883:
864:
861:
860:
859:
848:
841:
837:
831:
827:
821:
818:
793:
788:
784:
761:
757:
733:
711:
707:
695:
694:
683:
677:
672:
663:
659:
655:
650:
646:
639:
636:
611:
607:
592:
591:
580:
572:
567:
563:
559:
554:
549:
545:
537:
533:
529:
524:
520:
513:
510:
496:
495:
484:
476:
472:
468:
465:
460:
455:
451:
447:
442:
437:
433:
425:
421:
417:
412:
408:
401:
398:
375:
370:
366:
339:
334:
330:
304:
300:
274:
269:
265:
239:
235:
203:
191:
188:
186:
183:
117:
114:
80:
79:
39:
37:
30:
24:
14:
13:
10:
9:
6:
4:
3:
2:
6193:
6182:
6179:
6177:
6174:
6173:
6171:
6157:
6153:
6148:
6143:
6138:
6133:
6129:
6125:
6121:
6114:
6111:
6106:
6102:
6098:
6094:
6090:
6086:
6079:
6076:
6071:
6067:
6063:
6059:
6056:(3): 345–58.
6055:
6051:
6044:
6041:
6036:
6032:
6027:
6022:
6018:
6014:
6010:
6006:
6002:
5995:
5992:
5987:
5983:
5979:
5975:
5971:
5967:
5964:(2): 167–75.
5963:
5959:
5952:
5949:
5944:
5940:
5935:
5930:
5927:(7): 841–44.
5926:
5922:
5918:
5911:
5908:
5903:
5899:
5894:
5889:
5886:(7): 775–85.
5885:
5881:
5877:
5870:
5868:
5866:
5864:
5862:
5860:
5856:
5851:
5847:
5842:
5837:
5832:
5827:
5823:
5819:
5815:
5808:
5806:
5802:
5797:
5793:
5788:
5783:
5779:
5775:
5771:
5764:
5761:
5756:
5750:
5746:
5739:
5737:
5735:
5733:
5731:
5729:
5727:
5725:
5723:
5719:
5714:
5710:
5706:
5702:
5697:
5692:
5688:
5684:
5680:
5673:
5671:
5667:
5662:
5658:
5653:
5648:
5643:
5638:
5634:
5630:
5626:
5619:
5616:
5611:
5607:
5602:
5597:
5593:
5589:
5586:(8): 569–75.
5585:
5581:
5577:
5570:
5568:
5564:
5559:
5555:
5550:
5545:
5542:(3): 230–38.
5541:
5537:
5533:
5526:
5524:
5520:
5515:
5511:
5506:
5501:
5497:
5493:
5489:
5482:
5480:
5476:
5471:
5467:
5462:
5457:
5453:
5449:
5445:
5438:
5436:
5432:
5427:
5423:
5419:
5415:
5411:
5407:
5403:
5399:
5392:
5389:
5384:
5380:
5376:
5372:
5367:
5362:
5359:(4): 645–55.
5358:
5354:
5350:
5343:
5340:
5335:
5331:
5327:
5323:
5318:
5313:
5310:(5): 378–89.
5309:
5305:
5301:
5294:
5292:
5290:
5286:
5281:
5277:
5273:
5269:
5264:
5259:
5256:(5): 363–77.
5255:
5251:
5247:
5240:
5238:
5236:
5234:
5232:
5228:
5223:
5219:
5215:
5211:
5207:
5203:
5196:
5193:
5188:
5184:
5180:
5176:
5172:
5168:
5167:Technometrics
5161:
5158:
5153:
5149:
5145:
5141:
5137:
5133:
5132:Technometrics
5126:
5123:
5118:
5114:
5110:
5106:
5105:Technometrics
5099:
5096:
5091:
5087:
5082:
5077:
5073:
5069:
5065:
5061:
5058:are normal".
5057:
5053:
5049:
5045:
5038:
5035:
5030:
5026:
5022:
5018:
5013:
5008:
5004:
5000:
4996:
4989:
4986:
4981:
4977:
4973:
4969:
4966:(2): 292–99.
4965:
4961:
4954:
4952:
4950:
4946:
4941:
4937:
4932:
4927:
4924:(5): 645–55.
4923:
4919:
4915:
4908:
4906:
4904:
4900:
4895:
4891:
4886:
4881:
4878:(4): 552–61.
4877:
4873:
4869:
4862:
4860:
4858:
4856:
4854:
4852:
4850:
4848:
4844:
4837:
4833:
4829:
4828:
4824:
4820:
4817:
4815:
4812:
4810:
4809:c-probability
4807:
4805:
4802:
4800:
4799:Hit selection
4797:
4795:
4792:
4790:
4787:
4785:
4782:
4781:
4777:
4775:
4773:
4769:
4746:
4742:
4736:
4726:
4713:
4710:
4707:
4703:
4689:
4685:
4682:
4679:
4660:
4656:
4653:
4650:
4635:
4623:
4622:
4621:
4619:
4601:
4596:
4592:
4584:
4566:
4556:
4545:
4541:
4537:
4521:
4513:
4489:
4485:
4478:
4475:
4470:
4466:
4459:
4452:
4442:
4435:
4428:
4418:
4411:
4406:
4402:
4395:
4383:
4382:
4381:
4379:
4363:
4360:
4355:
4351:
4347:
4344:
4321:
4313:
4309:
4302:
4299:
4294:
4290:
4283:
4276:
4272:
4264:
4254:
4247:
4242:
4238:
4231:
4219:
4218:
4217:
4215:
4197:
4187:
4176:
4158:
4154:
4146:
4128:
4118:
4107:
4089:
4079:
4068:
4050:
4046:
4023:
4019:
4010:
4005:
3986:
3983:
3980:
3973:
3970:
3969:
3954:
3951:
3948:
3945:
3942:
3935:
3921:
3918:
3915:
3912:
3909:
3906:
3899:
3896:
3895:
3880:
3877:
3874:
3871:
3868:
3861:
3847:
3844:
3841:
3838:
3835:
3832:
3829:
3822:
3819:
3818:
3803:
3800:
3797:
3794:
3791:
3784:
3770:
3767:
3764:
3761:
3758:
3755:
3752:
3745:
3742:
3741:
3726:
3723:
3720:
3717:
3714:
3707:
3693:
3690:
3687:
3684:
3681:
3678:
3675:
3668:
3665:
3664:
3649:
3646:
3643:
3640:
3637:
3630:
3616:
3613:
3610:
3607:
3604:
3601:
3598:
3591:
3588:
3587:
3572:
3569:
3566:
3563:
3560:
3553:
3539:
3536:
3533:
3530:
3527:
3524:
3521:
3514:
3511:
3510:
3495:
3492:
3489:
3486:
3483:
3476:
3462:
3459:
3456:
3453:
3450:
3447:
3444:
3437:
3435:Fairly strong
3434:
3433:
3418:
3415:
3412:
3409:
3406:
3399:
3385:
3382:
3379:
3376:
3373:
3370:
3367:
3360:
3357:
3356:
3341:
3338:
3335:
3332:
3329:
3322:
3308:
3305:
3302:
3299:
3296:
3293:
3290:
3283:
3280:
3279:
3264:
3261:
3258:
3251:
3237:
3234:
3231:
3228:
3221:
3218:
3217:
3213:
3210:
3207:
3206:
3203:
3189:
3180:
3178:
3174:
3170:
3166:
3161:
3157:
3153:
3146:Hit selection
3145:
3143:
3139:
3137:
3115:
3112:
3109:
3106:
3099:
3085:
3082:
3079:
3076:
3069:
3055:
3052:
3049:
3046:
3039:
3025:
3022:
3019:
3016:
3009:
3006:
3005:
2990:
2987:
2984:
2981:
2978:
2975:
2972:
2965:
2951:
2948:
2945:
2942:
2939:
2936:
2933:
2926:
2912:
2909:
2906:
2903:
2900:
2897:
2894:
2887:
2873:
2870:
2867:
2864:
2861:
2858:
2855:
2848:
2845:
2844:
2829:
2826:
2823:
2820:
2817:
2814:
2811:
2804:
2790:
2787:
2784:
2781:
2778:
2775:
2772:
2765:
2751:
2748:
2745:
2742:
2739:
2736:
2733:
2726:
2712:
2709:
2706:
2703:
2700:
2697:
2694:
2687:
2684:
2683:
2668:
2665:
2662:
2659:
2652:
2638:
2635:
2632:
2629:
2622:
2608:
2605:
2602:
2599:
2592:
2578:
2575:
2572:
2569:
2562:
2559:
2558:
2554:
2551:
2548:
2545:
2542:
2541:
2538:
2534:
2532:
2527:
2523:
2519:
2514:
2512:
2508:
2490:
2480:
2473:
2468:
2458:
2451:
2446:
2436:
2429:
2424:
2414:
2387:
2377:
2372:
2362:
2355:
2350:
2345:
2335:
2326:
2319:
2309:
2302:
2297:
2287:
2277:
2268:
2258:
2257:
2256:
2254:
2235:
2227:
2222:
2218:
2214:
2209:
2204:
2200:
2192:
2182:
2175:
2170:
2160:
2150:
2141:
2131:
2130:
2129:
2115:
2112:
2107:
2103:
2099:
2094:
2090:
2086:
2083:
2060:
2049:
2044:
2040:
2033:
2030:
2025:
2021:
2014:
2009:
2004:
2000:
1993:
1990:
1985:
1981:
1969:
1966:
1957:
1947:
1940:
1935:
1925:
1915:
1906:
1896:
1895:
1894:
1878:
1874:
1870:
1865:
1861:
1838:
1833:
1829:
1825:
1820:
1815:
1811:
1803:
1785:
1775:
1768:
1763:
1753:
1742:
1733:
1731:
1729:
1725:
1721:
1717:
1713:
1708:
1704:
1700:
1696:
1688:
1686:
1669:
1662:
1658:
1649:
1638:
1635:
1632:
1628:
1614:
1610:
1607:
1604:
1585:
1581:
1578:
1575:
1560:
1551:
1541:
1540:
1539:
1522:
1515:
1511:
1502:
1495:
1486:
1476:
1475:
1474:
1458:
1453:
1449:
1441:
1419:
1409:
1393:
1384:
1370:
1367:
1362:
1358:
1354:
1349:
1345:
1341:
1338:
1316:
1312:
1308:
1303:
1299:
1275:
1264:
1259:
1255:
1248:
1245:
1240:
1236:
1229:
1224:
1219:
1215:
1208:
1205:
1200:
1196:
1184:
1181:
1172:
1162:
1155:
1150:
1140:
1130:
1121:
1111:
1110:
1109:
1107:
1088:
1080:
1075:
1071:
1067:
1062:
1057:
1053:
1045:
1035:
1028:
1023:
1013:
1003:
994:
984:
983:
982:
966:
961:
957:
953:
948:
943:
939:
931:
913:
903:
896:
891:
881:
870:
862:
846:
839:
835:
829:
825:
819:
816:
809:
808:
807:
791:
786:
782:
759:
755:
747:
731:
709:
705:
681:
675:
670:
661:
657:
653:
648:
644:
637:
634:
627:
626:
625:
609:
605:
597:
578:
570:
565:
561:
557:
552:
547:
543:
535:
531:
527:
522:
518:
511:
508:
501:
500:
499:
482:
474:
470:
466:
463:
458:
453:
449:
445:
440:
435:
431:
423:
419:
415:
410:
406:
399:
396:
389:
388:
387:
373:
368:
364:
355:
337:
332:
328:
320:
302:
298:
290:
272:
267:
263:
255:
237:
233:
225:
221:
217:
201:
189:
184:
182:
180:
179:hit selection
176:
172:
166:
164:
160:
156:
152:
148:
143:
139:
135:
131:
127:
123:
115:
113:
111:
107:
106:hit selection
103:
99:
95:
91:
87:
76:
73:
65:
55:
51:
46:
44:
38:
29:
28:
19:
6127:
6123:
6113:
6088:
6084:
6078:
6053:
6049:
6043:
6008:
6004:
5994:
5961:
5957:
5951:
5924:
5920:
5910:
5883:
5879:
5821:
5817:
5777:
5773:
5763:
5744:
5686:
5682:
5635:(9): e6892.
5632:
5628:
5618:
5583:
5579:
5539:
5535:
5495:
5491:
5451:
5447:
5401:
5397:
5391:
5356:
5352:
5342:
5307:
5303:
5253:
5249:
5205:
5201:
5195:
5173:(3): 253–7.
5170:
5166:
5160:
5138:(3): 551–8.
5135:
5131:
5125:
5108:
5104:
5098:
5063:
5059:
5055:
5051:
5047:
5043:
5037:
5005:(2): 67–73.
5002:
4998:
4988:
4963:
4959:
4921:
4917:
4875:
4871:
4765:
4509:
4336:
4006:
4003:
3181:
3149:
3140:
3132:
2543:Quality Type
2535:
2515:
2402:
2250:
2075:
1737:
1692:
1684:
1537:
1385:
1290:
1103:
866:
696:
593:
497:
193:
174:
170:
167:
119:
96:. It is the
89:
83:
68:
59:
40:
6176:Effect size
4784:Effect size
3666:Fairly weak
3281:Very strong
3202:) of SSMD.
1438:and sample
94:effect size
6170:Categories
4838:References
1800:, sample
806:, SSMD is
354:covariance
116:Background
86:statistics
5111:: 49–54.
4980:119825625
4768:compounds
4730:¯
4711:−
4683:−
4671:Γ
4654:−
4642:Γ
4560:¯
4476:−
4446:~
4422:~
4412:−
4361:−
4348:≈
4300:−
4258:¯
4248:−
4191:~
4122:~
4083:¯
4065:, sample
3981:β
3971:No effect
3949:β
3946:≥
3916:β
3913:≤
3907:−
3875:β
3872:≥
3845:−
3839:β
3836:≤
3830:−
3820:Very weak
3798:β
3768:−
3762:β
3753:−
3724:≥
3721:β
3691:−
3688:≤
3685:β
3676:−
3647:≥
3644:β
3614:−
3611:≤
3608:β
3599:−
3570:≥
3567:β
3537:−
3534:≤
3531:β
3522:−
3493:≥
3490:β
3460:−
3457:≤
3454:β
3445:−
3416:≥
3413:β
3383:−
3380:≤
3377:β
3368:−
3339:≥
3336:β
3306:−
3303:≤
3300:β
3291:−
3262:≥
3259:β
3235:−
3232:≤
3229:β
3190:β
3169:compounds
3165:compounds
3152:compounds
3113:−
3107:β
3083:−
3077:β
3053:−
3047:β
3023:−
3017:β
2988:−
2985:≤
2982:β
2973:−
2949:−
2946:≤
2943:β
2934:−
2910:−
2907:≤
2904:β
2895:−
2871:−
2868:≤
2865:β
2856:−
2827:−
2824:≤
2821:β
2812:−
2788:−
2785:≤
2782:β
2773:−
2749:−
2746:≤
2743:β
2734:−
2710:−
2707:≤
2704:β
2695:−
2666:−
2663:≤
2660:β
2636:−
2633:≤
2630:β
2606:−
2603:≤
2600:β
2576:−
2573:≤
2570:β
2560:Excellent
2484:~
2462:~
2440:~
2418:~
2366:~
2339:~
2313:~
2303:−
2291:~
2272:^
2269:β
2186:¯
2176:−
2164:¯
2145:^
2142:β
2113:−
2087:≈
2031:−
1991:−
1951:¯
1941:−
1929:¯
1910:^
1907:β
1802:variances
1779:¯
1757:¯
1718:(i.e., a
1653:¯
1636:−
1608:−
1596:Γ
1579:−
1567:Γ
1555:^
1552:β
1506:¯
1490:^
1487:β
1423:¯
1406:, sample
1368:−
1342:≈
1246:−
1206:−
1166:¯
1156:−
1144:¯
1125:^
1122:β
1039:¯
1029:−
1017:¯
998:^
995:β
930:variances
907:¯
885:¯
836:σ
826:μ
817:β
783:σ
756:μ
706:σ
676:σ
658:μ
654:−
645:μ
635:β
606:σ
596:variances
562:σ
544:σ
532:μ
528:−
519:μ
509:β
471:σ
464:−
450:σ
432:σ
420:μ
416:−
407:μ
397:β
365:σ
329:σ
299:μ
264:σ
234:μ
202:β
130:compounds
62:July 2011
54:talk page
6156:20032460
6105:20136359
6070:20397965
6035:18628291
5978:16465162
5943:19223447
5902:21515799
5850:18710486
5796:18976975
5713:41358896
5705:20817887
5661:19727391
5629:PLOS ONE
5610:19644458
5558:19211781
5514:20852024
5470:20855561
5426:10714162
5418:19650760
5375:17435171
5334:22679273
5326:18480473
5280:12688742
5272:18567841
5222:16143965
5029:36577200
5021:10838414
4940:17517904
4894:17276655
4872:Genomics
4794:Z-factor
4778:See also
4618:compound
4583:variance
4538:and the
4536:compound
4512:compound
4214:compound
4009:compound
3512:Moderate
3177:compound
3160:compound
3156:compound
2846:Inferior
2531:Z-factor
2518:Z-factor
2505:are the
2253:outliers
1728:compound
1716:compound
1440:variance
1106:variance
319:variance
254:variance
163:Z-factor
159:Z-factor
155:Z-factor
151:Z-factor
138:Z-factor
6147:2844209
6026:2504311
5986:6158255
5841:2526086
5652:2731218
5601:2789971
5383:7542230
5187:1269081
5152:1266860
5090:2283110
5050:) when
2507:medians
1697:to the
185:Concept
6154:
6144:
6103:
6068:
6033:
6023:
5984:
5976:
5941:
5900:
5848:
5838:
5824:: 33.
5794:
5751:
5711:
5703:
5659:
5649:
5608:
5598:
5556:
5512:
5468:
5424:
5416:
5381:
5373:
5332:
5324:
5278:
5270:
5220:
5185:
5150:
5088:
5027:
5019:
4978:
4938:
4892:
4770:in an
4540:median
4436:1.4826
4337:where
4106:median
3358:Strong
3173:assays
2403:where
2327:1.4826
2076:where
1722:or an
1291:where
352:. The
142:assays
134:assays
88:, the
5982:S2CID
5709:S2CID
5422:S2CID
5379:S2CID
5330:S2CID
5276:S2CID
5183:JSTOR
5148:JSTOR
5086:JSTOR
5025:S2CID
4976:S2CID
4772:assay
4514:with
4392:SSMD*
4378:assay
3561:1.645
3525:1.645
3496:1.645
3463:1.645
3136:assay
2522:assay
1724:siRNA
1712:assay
147:assay
126:assay
6152:PMID
6101:PMID
6066:PMID
6031:PMID
5974:PMID
5939:PMID
5898:PMID
5846:PMID
5792:PMID
5749:ISBN
5701:PMID
5657:PMID
5606:PMID
5554:PMID
5510:PMID
5466:PMID
5414:PMID
5371:PMID
5322:PMID
5268:PMID
5218:PMID
5054:and
5017:PMID
4936:PMID
4890:PMID
4804:SMCV
4632:SSMD
4581:and
4544:mean
4364:2.48
4228:SSMD
4173:and
4067:mean
3952:>
3943:0.25
3919:<
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