ライフサイエンスコーパス: statistical test

1 classified as likely correct, using a simple statistical test.

2 worse outcomes and were analyzed by a global statistical test.

3 etween the 2 treatment groups using a global statistical test.

4 d and statistically compared using McNemar's statistical test.

5 riminant functions and variables within each statistical test.

6 mation to contrast one or more networks in a statistical test.

7 me 9p21 for association using a gene-centric statistical test.

8 cted to PCA to provide an easy to understand statistical test.

9 they are different according to a particular statistical test.

10 H cell-seeded scaffolds, using nonparametric statistical tests.

11 utation-based method for combining different statistical tests.

12 se of normally distributed data, parametric- statistical tests.

13 mean (+/- SD) and compared using appropriate statistical tests.

14 time by TG/DTA with application of different statistical tests.

15 by appropriate non-parametric or parametric statistical tests.

16 on studies with a focus on study designs and statistical tests.

17 r cophylogenetic analyses, performing robust statistical tests.

18 M molecular subgroups by using nonparametric statistical tests.

19 rge-scale experimental data with a number of statistical tests.

20 n intention-to-treat basis using appropriate statistical tests.

21 e evaluated for compartmentalization using 4 statistical tests.

22 3% (95% CI: 0%, 6%) they used inappropriate statistical tests.

23 were compared with the actual outcomes using statistical tests.

24 ished by UV-vis spectrometry and endorsed by statistical tests.

25 lack of scalable software and lack of robust statistical tests.

26 s were categorised into four groups with two statistical tests.

27 sults were further subjected to a battery of statistical tests.

28 e evaluated with univariate and multivariate statistical tests.

29 rge-scale experimental data with a number of statistical tests.

30 new LASSO method has the ability to perform statistical tests.

31 ation, annotation, pathogenic prediction and statistical tests.

32 d approach were evaluated through normalized statistical tests.

33 however, present a challenge to traditional statistical tests.

34 sults may remain unidentified after applying statistical testing.

35 Data were tabulated for statistical testing.

36 ificantly enriched within each cluster using statistical testing.

37 nt number of cases with differences to allow statistical testing.

38 nce index (MLCI) for influence on downstream statistical testing.

39 tically and illogically as a function of the statistical test a researcher plans to use (e.g., t-test

40 We compared a standard statistical test-a score test-with a recently developed

41 ipeline's modularity allows customization of statistical testing, adoption of alternative initial gat

42 on algorithm combined with a two-dimensional statistical test allows the detection of DMRs in large m

43 We use both a formal statistical test and a quantile-quantile plot for visual

44 ion on the effect size of an intervention, a statistical test and measure of confidence with the abil

45 Our method has broad uses for statistical testing and experimental design in research

46 e, Antibody Sequence Analysis Pipeline using Statistical testing and Machine Learning (ASAP-SML), to

47 jor updates in XBSeq2, including alternative statistical testing and parameter estimation method for

48 Using statistical tests and a decoding approach, we found that

49 dom measurement error decreases the power of statistical tests and a review of the roles of sample si

50 We present two-sided statistical tests and correct for multiple comparisons.

51 The method is based on rigorous statistical tests and does not require any presumed kine

52 Furthermore, the statistical tests and linear regression showed that the

53 n AMR associations more reliably than common statistical tests and previous ensemble approaches, iden

54 ions show high levels of sensitivity for the statistical test, and application to a control normal-ti

55 ave uniform transmissibility through a novel statistical test, and find that certain strains appear m

56 using Fisher meta-analysis, resampling-based statistical testing, and machine learning.

57 ciated with SSI were tested using univariate statistical tests, and a hierarchical generalized linear

58 voxel-wise manner, resulting in around 10(5) statistical tests, and considerable emphasis placed on c

59 ue have been small, used potentially invalid statistical tests, and produced inconsistent findings.

60 Because all parameters required for the statistical test are estimated directly from the data, i

61 The statistical tests are based on the Erlang distribution m

62 Several statistical tests are proposed for a complete dissection

63 genetic epidemiology and argue for retaining statistical testing as an important part of the tool kit

64 was performed using categoric or continuous statistical testing as appropriate, with multivariable r

65 Differences among groups were analyzed using statistical tests as appropriate to the data.

66 Advanced comparative features comprise statistical tests as well as multidimensional scaling, h

67 Here, we present two statistical tests based on the distinctive spatial patte

68 However, we find that statistical tests based on these two models give conflic

69 A statistical test, based on the transformation of the exp

70 mlDNA substantially outperformed traditional statistical testing-based differential expression analys

71 We present a novel non-parametric statistical test between splice graphs to assess the sig

72 on by Buhaug is based on absent or incorrect statistical tests, both in model selection and in the co

73 Statistical testing by eating disorder categories with t

74 tion and evolution, we show that stratifying statistical tests by domain family yields excellent resu

75 Our statistical test can also include tree reconstruction in

76 sis testing problems-that is, those in which statistical tests can be partitioned naturally-controlli

77 hat the tool utilizing networks and binomial statistical tests can identify interesting structural re

78 Statistical testing completed using t test, Chi Square,

79 ves access to the results to 800 millions of statistical tests corresponding to all the pairs of site

80 Newly incorporated statistical tests cover a wide array of univariate analy

81 ous approaches such as DRME model based on a statistical test covering the IP samples only with 2 neg

82 was symmetrical both according to visual and statistical testing (Egger test = 0.32).

83 Based on a novel statistical test employing conjugate Fisher transformati

84 Our methods combine de novo assembly with statistical tests enabling motif discovery without the u

85 on coefficient, the higher is sensitivity of statistical testing, especially of the paired t-test.

86 A variety of statistical tests examined the relationships between the

87 This paper provides a statistical test for DDMs with general, nonconstant boun

88 The presented method conducts a statistical test for differential analysis in regions of

89 ependency DifferentialitY (EDDY), which is a statistical test for differential dependencies of a set

90 one analytics with novel feature extraction, statistical test for differential expression and diagnos

91 ling measurements separately, and performs a statistical test for differential translation efficiency

92 wback is that, because they perform just one statistical test for each individual experiment, they ma

93 to outliers, and (ii) they perform only one statistical test for each individual study, and hence do

94 re for relative abundance profiles, derive a statistical test for equality and propose a protein-leve

95 n favor of ART-123, which met the predefined statistical test for evidence suggestive of efficacy).

96 method based on a deep learning model and a statistical test for identifying differential m6A methyl

97 skal-Wallis test is a popular non-parametric statistical test for identifying expression quantitative

98 A statistical test for interaction between previous aborti

99 CoMEt includes an exact statistical test for mutual exclusivity and techniques t

100 We apply a statistical test for such LOH-influenced disruptions, an

101 information divergency and (iii) a rigorous statistical test for the significance of all the identif

102 ant trend on the BDI (beta = -1.14; P = .08, statistical test for trend), but no significant differen

103 To enable statistical testing for differences in mass signal inten

104 Statistical testing for differences in serum ghrelin lev

105 combined use of small-scale and large-scale statistical testing for genomic island detection.

106 The noninferiority margin was 5 letters, and statistical testing for noninferiority was based on a 1-

107 Statistical testing for substantial differences in ghrel

108 ; if noninferiority was established, 2-sided statistical testing for superiority was conducted.

109 d PubChem compound identifiers, and based on statistical tests for association.

110 prevalence rates, confidence intervals, and statistical tests for differences.

111 eference, counting transcript abundance, and statistical tests for differentially expressed genes.

112 Current statistical tests for exclusivity that incorporate both

113 However, to date, formal statistical tests for gene-gene interaction on untyped S

114 Standard statistical tests for Hardy-Weinberg equilibrium assume

115 Recently, frequentist statistical tests for Hardy-Weinberg equilibrium have be

116 ed to normalized read counts and enabled new statistical tests for identifying developmentally regula

117 We develop several statistical tests for identifying Significantly Mutated

118 shifts using ancestral protein resurrection, statistical tests for positive selection, forward and re

119 ining the best study design, sample size and statistical tests for sequence-based association studies

120 rity since it was realised that the power of statistical tests for the study of evolutionary trends c

121 ogenes are utilized to construct appropriate statistical tests for the transposon insertion tolerance

122 s paper generalizes existing null models and statistical tests for this purpose to bipartite graphs,

123 Classical statistical tests for within-sample comparisons fail as

124 models with features identified by different statistical tests further demonstrated the advantage of

125 With the most stringent statistical tests, GeoNet detected 0.2% to 2% of the kno

126 , such as sample size and choice of specific statistical tests, had been specified before any data we

127 Each type of statistical test has its own advantages in characterizin

128 Distance-based statistical tests have been applied to test the associat

129 It is therefore surprising that rigorous statistical tests have failed to find evidence of positi

130 Using rigorous statistical tests, here we characterize the relationship

131 Because of statistical testing hierarchical rules, the 50-mug patch

132 The prespecified statistical testing hierarchy meant that overall surviva

133 t be formally tested due to the prespecified statistical testing hierarchy.

134 is using Cochran-Armitage and Fisher's exact statistical tests identified 1364 statistically signific

135 Statistical tests identified genes that exhibited differ

136 veloped as a two-part process involving: (1) statistical testing in order to determine the number of

137 he intervals are valid for most large-sample statistical tests in any context, and can be used in the

138 offering some guidance to authors reporting statistical tests in journals and present a position sta

139 The BlueSNP R package implements GWAS statistical tests in the R programming language and exec

140 Statistical testing included analysis of variance, t tes

141 Statistical testing included Kruskal-Wallis tests for co

142 Statistical testing included the intraclass correlation

143 Statistical tests included Mann-Whitney U, Pearson corre

144 Statistical tests included t tests and F tests with a ty

145 a dependence kernel is sufficient to render statistical tests independent regardless of the level of

146 Two statistical tests indicate that both modeled and unmodel

147 Results from non-parametric statistical tests indicate that the separation between t

148 tegrated copy number filtering, and to use a statistical test inherently robust for use in platforms

149 The statistical test involves a set of parameters that can b

150 A non-parametric statistical test is applied to each ASM to detect signif

151 in the probability distribution on which the statistical test is based, because of the differences in

152 can be considered to be flat and no further statistical testing is needed.

153 high-dimensional data, variable-by-variable statistical testing is often used to select variables wh

154 Combining P-values from multiple statistical tests is a common exercise in bioinformatics

155 Performing statistical tests is an important step in analyzing geno

156 an be detected using a collection of generic statistical tests known as early warning signals (EWSs).

157 Other statistical tests like student t-test and logistic regre

158 researchers reuse the same dataset, multiple statistical testing may increase false positives.

159 rain lifespan, after correction for multiple statistical testing (miR-203-3p [beta-coefficient = -0.6

160 By one statistical test, missense variants of KLF4 as a group w

161 Here, we introduce the Multivariate Omnibus Statistical Test (MOSTest), with an efficient computatio

162 We present a new statistical test of association between a trait and gene

163 Here, we describe a formal statistical test of colocalization and apply it to type

164 reement between such probe sets, utilizing a statistical test of concordance, Kendall's W coefficient

165 s of aggressive and antisocial behavior; and statistical test of genotype-environment interaction.

166 Parallel mutations were screened using a statistical test of mutation-phenotype association and f

167 A formal statistical test of the treatment-by-biomarker interacti

168 Cue identification is often achieved with statistical testing of candidate cues.

169 However, while statistical testing of differences in mean expression le

170 Sequential statistical testing of noninferiority (margin of 1.075),

171 ingenuity pathway analysis was performed for statistical testing of pathways.

172 A maize germplasm collection was used for statistical testing of the correlation between carotenoi

173 Statistical tests of average responses detected no signi

174 guide the development and interpretation of statistical tests of causality between phenotypes using

175 Maximum likelihood trees and statistical tests of compartmentalization revealed inter

176 Statistical tests of direct cause and effect relationshi

177 rtions of patients with elevated markers and statistical tests of elevations as prognostic factors.

178 We performed statistical tests of phylogeographic structure and appli

179 imony and Bayesian methods demonstrates that statistical tests of positive selection can be misleadin

180 kelihood based estimation further allows for statistical tests of several relevant hypotheses, includ

181 also provide a framework to enable rigorous statistical tests of significance in intervention studie

182 , these articles did not include analyses or statistical tests of the mortality data, and the 2 artic

183 confidence interval was achieved by standard statistical tests of the recovered probability density f

184 upertree of highest likelihood, and performs statistical tests of two or more supertrees.

185 ssociations can be identified using a simple statistical test on all paired combinations of genetic v

186 is a bioinformatics technique that performs statistical testing on biologically meaningful sets of g

187 Existing meta-analysis methods perform statistical tests on sets of publications associated wit

188 data for one or more species; (ii) performs statistical tests on the integrated datasets; and (iii)

189 d pain response at 12 weeks) were to undergo statistical testing only if the primary end point analys

190 analysis has more power than the equivalent statistical test performed on a single large experiment.

191 The large number of statistical tests performed also makes sufficient type o

192 ntrol alpha error due to the large number of statistical tests performed.

193 Ideally, a statistical testing procedure should incorporate the inh

194 counting for spatial correlations within the statistical testing procedure.

195 We develop four frequentist statistical test procedures for X-linked markers that ta

196 ee indices of dynamic interaction reliant on statistical testing procedures are susceptible to Type I

197 It utilizes a wide gamut of statistical tests, procedures, and methodologies that be

198 Statistical tests produced regression R2 values of 88%,

199 The non-parametric nature of our statistical test provides fast and efficient analyses, a

200 In contrast to available statistical tests, RareIBD generates accurate p values e

201 Various statistical tests rejected a neutral equilibrium model o

202 ikely recur, with the sample size n used for statistical tests representing biological replicates, in

203 l power resulting from the massive number of statistical tests required to detect such interactions.

204 Performing a statistical test requires a null hypothesis.

205 n in preliminary data processing and optimal statistical testing significantly enhances the functiona

206 ne toxicity were analysed using a gene based statistical test (SKAT-O test).

207 Our statistical testing strategy showed no significant evide

208 The necessary parameters for statistical tests (such as the expected frequency of rep

209 Statistical test suggested simulated results were not si

210 s to pass all 15 tests of the NIST SP 800-22 statistical test suite.

211 n dynamic displays alongside user-controlled statistical tests, supporting rapid statistical validati

212 Statistical test (t-student) was applied to the coeffici

213 This assessment uses a novel statistical test that extends the widely used Hypergeome

214 cts on deglaciation are overcome using a new statistical test that focuses on maxima in orbital forci

215 It supports any statistical test that is based on contingency tables, an

216 terion specifies a single, information-based statistical test that is free from ad hoc parameters and

217 noprecipitation-sequencing (ChIP-seq) with a statistical test that simultaneously scores peak height

218 ropose a combination of machine learning and statistical testing that takes correlation structures wi

219 stant seasonality, thus confirming by formal statistical testing that the magnitude of the seasonalit

220 Effect sizes were calculated from statistical tests that could be converted to standardize

221 dies, having >1 outcome variable, conducting statistical tests that produce >1 P value, taking multip

222 We propose a distance-based statistical test, the generalized RV (GRV) test, to asse

223 For a variety of magnitude cutoffs and three statistical tests, the global catalog, with local cluste

224 s in a bayesian analysis may provide a novel statistical test to assess the consistency of species ab

225 Using this analysis method, we formulated a statistical test to compare the ACO hypothesis with meas

226 ly, we use a recently devised non-parametric statistical test to demonstrate that PPI networks of man

227 Y (Evaluation of Differential DependencY), a statistical test to detect differential statistical depe

228 In this article, we propose a new statistical test to detect differentially methylated loc

229 We present a statistical test to detect that a presented state of a r

230 At the core of smCounter2 is a statistical test to determine whether the allele frequen

231 al disorders, and develop a simulation-based statistical test to identify gene-specific enrichment of

232 ch other and one is selected as best without statistical testing to determine whether the improvement

233 Here, we propose a suite of statistical tests to address these open needs: a paramet

234 ase of supernovae so we can perform rigorous statistical tests to check whether these 'standardisable

235 ng profiles across single cells and performs statistical tests to compare percent spliced-in (PSI) va

236 It is therefore important to use robust statistical tests to decipher the correct theoretical mo

237 We designed statistical tests to detect AEI in a comprehensive set o

238 ncreasing need to develop and apply powerful statistical tests to detect association between multiple

239 ents, which has made it difficult to develop statistical tests to either confirm or deny putative tra

240 nt scenarios, (ii) using a sequence of three statistical tests to eliminate background regions and to

241 This algorithm employs straightforward statistical tests to evaluate the significance of differ

242 umor genome data could complement gene-based statistical tests to identify likely new cancer genes; b

243 The method uses correlation analysis and statistical tests to identify network modules by three c

244 nologies have motivated development of novel statistical tests to identify rare genetic variation tha

245 es used weights and complex design-corrected statistical tests to infer generalizability to the US po

246 s introduced to select and apply appropriate statistical tests to loadings plot data, which are then

247 atlas comparison was performed via per-voxel statistical tests to localize shape differences (signifi

248 We apply the GP growth model and develop statistical tests to quantify the differential effects o

249 ematically combine information from multiple statistical tests to rigorously evaluate a single overar

250 get associations using one of three separate statistical tests, to link microRNA targets to functiona

251 ion test (SKAT) is probably the most popular statistical test used in rare-variant association studie

252 Statistical tests used in the analysis were all two-side

253 Statistical tests used the factorial design and included

254 We performed statistical testing using FBAT-CNV.

255 Two-sided statistical tests using conditional logistic regression

256 dels to build between-tumor and within-tumor statistical tests, using organoids analogously to large

257 A global statistical test was used to analyze the 9 scales of the

258 dings for each hypothesis were obtained when statistical testing was completed for that hypothesis; t

259 Consequently, formal statistical testing was not done for subsequent major se

260 Statistical testing was performed by using linear regres

261 Nonparametric statistical testing was performed on all comparisons.

262 Statistical testing was performed with Wilcoxon's rank s

263 Due to our stringent statistical test, we expect many of the associations in

264 Using the same statistical test, we found 1495 genes whose expression w

265 Using statistical tests, we identified a small number of cases

266 All statistical tests were 2 sided.

267 Statistical tests were 2-sided.

268 vitamin E, vitamin C, and carotenoid intake; statistical tests were 2-sided.

269 All statistical tests were 2-sided.

270 Statistical tests were applied for data analysis.

271 Standard quality control and statistical tests were applied to the 1000 Genomes imput

272 Machine learning feature selection and statistical tests were combined to identify candidate bi

273 Both chromosome-wide and genome-wide statistical tests were conducted to identify imprinted q

274 Statistical tests were performed on EEG and NIRS signals

275 Statistical tests were performed to confirm the quality

276 Appropriate statistical tests were performed to evaluate measured qu

277 Statistical tests were performed using Wilcoxon signed-r

278 The statistical tests were two sided, with a type-I error se

279 All statistical tests were two sided.

280 ffects models were used for analyses and all statistical tests were two-sided.

281 All statistical tests were two-sided.

282 ere estimated using logistic regression, and statistical tests were two-sided.

283 Non-parametric statistical tests were used for between-group comparison

284 Statistical tests were used to assess changes in the cli

285 Statistical tests were used to assess correlations betwe

286 Appropriate statistical tests were used to assess differences in (18

287 Statistical tests were used to evaluate linearity.

288 Statistical tests were used to identify molecular specie

289 Non-parametrical statistical tests were used.

290 Standard two-sided statistical tests were utilized.

291 quence of Bell's theorem is the existence of statistical tests which can detect the presence of entan

292 Kolomogov-Smirnov statistical tests, which compare the distributions of en

293 n the flipped analysis and by non-parametric statistical testing (whole brain corrected P-value < 0.0

294 Using simulations, we illustrate how the statistical test with optimal power depends on the relat

295 analysed the primary endpoint with one-sided statistical testing with calculation of upper 95% confid

296 Using statistical testing with seizure surrogate data and a un

297 ze over 900 different genomes, using updated statistical tests with false discovery rate corrections

298 Statistical tests with multiple testing corrections demo

299 M2, and ERN1) by applying between population statistical tests (XP-EHH and XP-CLR).

300 The global statistical test yielded t1865.8 = -0.75 (2-sided P = .4