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Strictly standardized mean difference

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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
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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
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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
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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
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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,
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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.
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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
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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
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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.
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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
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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
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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
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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
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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.
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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.
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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).
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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
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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).
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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.
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Acion L, Peterson JJ, Temple S, Arndt S (2006). "Probabilistic index: an intuitive non-parametric approach to measuring the size of treatment effects".
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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
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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
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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).
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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
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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).
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based QC criterion is popularly used in HTS assays. However, it has been demonstrated that this QC criterion is most suitable for an
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SSMD can not only rank the size of effects but also classify effects as shown in the following table based on the population value (
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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(
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of a difference between two random values each from one of two groups. It was initially proposed for quality control and
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Zhou HL, Xu M, Huang Q, Gates AT, Zhang XD, Castle JC, Stec E, Ferrer M, Strulovici B, Hazuda DJ, Espeseth AS (2008).
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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
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Optimal High-Throughput Screening: Practical Experimental Design and Data Analysis for Genome-scale RNAi Research
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over the S/N and S/B is that it takes into account the variabilities in both compared groups. As a result, the
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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
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SSMD looks similar to t-statistic and Cohen's d, but they are different with one another as illustrated in.
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Zhang XHD (2010). "Assessing the size of gene or RNAi effects in multifactor high-throughput experiments".
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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".
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Quon K, Kassner PD (2009). "RNA interference screening for the discovery of oncology targets".
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Reiser B, Guttman I (1986). "Statistical inference for of Pr(Y-less-thaqn-X) - normal case".
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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
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when the two groups have different variabilities. Zhang JH et al. proposed the
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Malo N, Hanley JA, Carlile G, Liu J, Pelletier J, Thomas D, Nadon R (2010).
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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
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Downton F (1973). "The estimation of Pr(Y < X) in normal case".
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by their effects and then to select the largest number of potent
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of the paired difference across replicates. The SSMD for this
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and the negative reference in that plate has sample size
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When the two groups have normal distributions with equal
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value of a negative control in a plate, then obtain the
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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
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in the positive and negative controls, respectively.
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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:< 3910:0.25 3881:0.25 3878:> 3848:0.25 3842:< 3801:> 3795:> 3792:0.75 3765:< 3759:< 3756:0.75 3743:Weak 3727:0.75 3718:> 3694:0.75 3682:< 3641:> 3638:1.28 3605:< 3602:1.28 3573:1.28 3564:> 3540:1.28 3528:< 3487:> 3451:< 3410:> 3374:< 3333:> 3297:< 3110:> 3080:> 3050:> 3020:> 3007:Poor 2979:< 2940:< 2901:< 2862:< 2818:< 2779:< 2740:< 2701:< 2685:Good 2526:RNAi 2516:The 2509:and 2116:3.48 1741:mean 1703:mean 1695:mean 1408:mean 1371:3.48 869:mean 774:and 746:mean 317:and 289:mean 252:and 224:mean 216:mean 98:mean 18:SSMD 6142:PMC 6132:doi 6128:285 6093:doi 6058:doi 6021:PMC 6013:doi 5966:doi 5929:doi 5888:doi 5836:PMC 5826:doi 5782:doi 5691:doi 5647:PMC 5637:doi 5596:PMC 5588:doi 5544:doi 5500:doi 5456:doi 5406:doi 5361:doi 5312:doi 5258:doi 5210:doi 5175:doi 5140:doi 5113:doi 5076:hdl 5068:doi 5007:doi 4968:doi 4926:doi 4880:doi 4011:is 3869:0.5 3833:0.5 3804:0.5 3771:0.5 3026:0.5 2874:0.5 218:to 120:In 108:in 84:In 6172:: 6150:. 6140:. 6126:. 6122:. 6099:. 6089:11 6087:. 6064:. 6054:10 6052:. 6029:. 6019:. 6009:36 6007:. 6003:. 5980:. 5972:. 5962:24 5960:. 5937:. 5925:25 5923:. 5919:. 5896:. 5884:16 5882:. 5878:. 5858:^ 5844:. 5834:. 5820:. 5816:. 5804:^ 5790:. 5776:. 5772:. 5721:^ 5707:. 5699:. 5687:15 5685:. 5681:. 5669:^ 5655:. 5645:. 5631:. 5627:. 5604:. 5594:. 5582:. 5578:. 5566:^ 5552:. 5540:14 5538:. 5534:. 5522:^ 5508:. 5496:15 5494:. 5490:. 5478:^ 5464:. 5452:15 5450:. 5446:. 5434:^ 5420:. 5412:. 5402:13 5400:. 5377:. 5369:. 5357:12 5355:. 5351:. 5328:. 5320:. 5308:13 5306:. 5302:. 5288:^ 5274:. 5266:. 5254:13 5252:. 5248:. 5230:^ 5216:. 5206:25 5204:. 5181:. 5171:28 5169:. 5146:. 5136:15 5134:. 5109:12 5107:. 5084:. 5074:. 5064:59 5062:. 5023:. 5015:. 5001:. 4997:. 4974:. 4962:. 4948:^ 4934:. 4922:12 4920:. 4916:. 4902:^ 4888:. 4876:89 4874:. 4870:. 4846:^ 4143:, 4104:, 1383:. 710:12 624:, 475:12 369:12 6158:. 6134:: 6107:. 6095:: 6072:. 6060:: 6037:. 6015:: 5988:. 5968:: 5945:. 5931:: 5904:. 5890:: 5852:. 5828:: 5822:1 5798:. 5784:: 5778:4 5757:. 5715:. 5693:: 5663:. 5639:: 5633:4 5612:. 5590:: 5584:6 5560:. 5546:: 5516:. 5502:: 5472:. 5458:: 5428:. 5408:: 5385:. 5363:: 5336:. 5314:: 5282:. 5260:: 5224:. 5212:: 5189:. 5177:: 5154:. 5142:: 5119:. 5115:: 5092:. 5078:: 5070:: 5056:Y 5052:X 5048:X 5044:Y 5031:. 5009:: 5003:4 4982:. 4970:: 4964:2 4942:. 4928:: 4896:. 4882:: 4747:i 4743:s 4737:i 4727:d 4714:1 4708:n 4704:2 4695:) 4690:2 4686:2 4680:n 4674:( 4666:) 4661:2 4657:1 4651:n 4645:( 4636:= 4602:2 4597:i 4593:s 4567:i 4557:d 4522:n 4490:K 4486:/ 4482:) 4479:1 4471:N 4467:n 4463:( 4460:2 4453:N 4443:s 4429:N 4419:X 4407:i 4403:X 4396:= 4356:N 4352:n 4345:K 4322:, 4314:K 4310:/ 4306:) 4303:1 4295:N 4291:n 4287:( 4284:2 4277:N 4273:s 4265:N 4255:X 4243:i 4239:X 4232:= 4198:N 4188:s 4159:N 4155:s 4129:N 4119:X 4090:N 4080:X 4051:N 4047:n 4024:i 4020:X 3987:0 3984:= 3955:0 3922:0 3715:1 3679:1 3650:1 3617:1 3484:2 3448:2 3419:2 3407:3 3386:2 3371:3 3342:3 3330:5 3309:3 3294:5 3265:5 3238:5 3116:3 3086:2 3056:1 2991:3 2976:5 2952:2 2937:3 2913:1 2898:2 2859:1 2830:5 2815:7 2791:3 2776:5 2752:2 2737:3 2713:1 2698:2 2669:7 2639:5 2609:3 2579:2 2491:N 2481:s 2474:, 2469:P 2459:s 2452:, 2447:N 2437:X 2430:, 2425:P 2415:X 2388:, 2378:2 2373:N 2363:s 2356:+ 2351:2 2346:P 2336:s 2320:N 2310:X 2298:P 2288:X 2278:= 2236:. 2228:2 2223:N 2219:s 2215:+ 2210:2 2205:P 2201:s 2193:N 2183:X 2171:P 2161:X 2151:= 2108:N 2104:n 2100:+ 2095:P 2091:n 2084:K 2061:, 2055:) 2050:2 2045:N 2041:s 2037:) 2034:1 2026:N 2022:n 2018:( 2015:+ 2010:2 2005:P 2001:s 1997:) 1994:1 1986:P 1982:n 1978:( 1975:( 1970:K 1967:2 1958:N 1948:X 1936:P 1926:X 1916:= 1879:N 1875:n 1871:, 1866:P 1862:n 1839:2 1834:N 1830:s 1826:, 1821:2 1816:P 1812:s 1786:N 1776:X 1769:, 1764:P 1754:X 1670:. 1663:D 1659:s 1650:D 1639:1 1633:n 1629:2 1620:) 1615:2 1611:2 1605:n 1599:( 1591:) 1586:2 1582:1 1576:n 1570:( 1561:= 1523:. 1516:D 1512:s 1503:D 1496:= 1459:2 1454:D 1450:s 1420:D 1394:n 1363:2 1359:n 1355:+ 1350:1 1346:n 1339:K 1317:2 1313:n 1309:, 1304:1 1300:n 1276:, 1270:) 1265:2 1260:2 1256:s 1252:) 1249:1 1241:2 1237:n 1233:( 1230:+ 1225:2 1220:1 1216:s 1212:) 1209:1 1201:1 1197:n 1193:( 1190:( 1185:K 1182:2 1173:2 1163:X 1151:1 1141:X 1131:= 1089:. 1081:2 1076:2 1072:s 1068:+ 1063:2 1058:1 1054:s 1046:2 1036:X 1024:1 1014:X 1004:= 967:2 962:2 958:s 954:, 949:2 944:1 940:s 914:2 904:X 897:, 892:1 882:X 847:. 840:D 830:D 820:= 792:2 787:D 760:D 732:D 682:. 671:2 662:2 649:1 638:= 610:2 579:. 571:2 566:2 558:+ 553:2 548:1 536:2 523:1 512:= 483:. 467:2 459:2 454:2 446:+ 441:2 436:1 424:2 411:1 400:= 374:. 338:2 333:2 303:2 273:2 268:1 238:1 175:Y 171:X 75:) 69:( 64:) 60:( 56:. 20:)

Index

SSMD
close connection
neutral point of view
talk page
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statistics
effect size
mean
standard deviation
hit selection
high-throughput screening
high-throughput screening
assay
compounds
assays
Z-factor
assays
assay
Z-factor
Z-factor
Z-factor
Z-factor
hit selection
mean
standard deviation
mean
variance
mean
variance
covariance

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