ライフサイエンスコーパス: outlier

1 to the areas where they were buried (spatial outliers).

2 We note that 2016 was a statistical outlier.

3 phe ICC value was sensitive to a measurement outlier.

4 l had been publicly identified as a negative outlier.

5 outcomes, but also to learn from successful outliers.

6 ates data by reliably detecting and removing outliers.

7 s, to perform model selection, and to handle outliers.

8 es have revealed increasing numbers of viral outliers.

9 tasets allows visual detection of biases and outliers.

10 ts benefits, including the ability to detect outliers.

11 .49 mm median error, and without large error outliers.

12 detecting clinically significant refractive outliers.

13 aset summary, quality control and helps flag outliers.

14 tecting systematic biases, batch effects and outliers.

15 , a measure least sensitive to postoperative outliers.

16 other regions were sensitive to measurement outliers.

17 many tools exist to interpret biases due to outliers.

18 tion processes to confirm samples flagged as outliers.

19 are more likely to be designated as negative outliers.

20 tstanding stereoinduction displayed by these outliers.

21 than 150% of the MIS average were considered outliers.

22 ode of a distribution and is hence robust to outliers.

23 onserved rare variants compared to 8% of non-outliers.

24 elation coefficients to provide insight into outliers.

25 ametric bootstrapping and for detecting data outliers.

26 r (candidate) traits that associate with the outliers.

27 statistical methodologies to detect splicing outliers.

28 % of all weight measurements were flagged as outliers.

29 other associations exhibited sensitivity to outliers.

30 lity control and the exclusion of population outliers, 835 patients and 1255 control participants fro

31 f inpatient deaths, prolonged length-of-stay outliers, 90-day postdischarge deaths, and 90-day readmi

32 ethylobacterium species, individual-specific outlier abundance of Staphylococcus species (eg, S epide

33 30-day RSMR was much stronger (r= 0.83) and outlier agreement improved substantially (kappa=0.60).

34 The same SNPs outliers also segregated two distinct populations in the

35 One outlier AML responded and exhibited intrinsic drug resis

36 ring modern humans with a HC that is a clear outlier amongst all nonhuman primates investigated here.

37 Finally, outlier analysis identified putative targetable proteins

38 urrent, producing divergent gene expression (outlier analysis), or as functionally important (e.g., k

39 Two subjects were excluded following outlier analysis.

40 target of environmental selection, using an outlier and a genome-wide transcriptome analysis.

41 eal new insights into transcription based on outlier and asymmetrical behaviour in large patient coho

42 ous revascularization increased similarly at outlier and nonoutlier institutions after report of outl

43 Ethyl-Intervention Trial) was a significant outlier and strongly influential trial in the meta-regre

44 response series, and robustly fits data with outliers and cytotoxicity-related signal loss.

45 ber, density distribution, background noise, outliers and degree of overlap, makes it difficult to fi

46 We show robustness against individual outliers and different protocols for the projection of n

47 ile regression has the desired robustness to outliers and dropouts, and it significantly improves eQT

48 vity of findings to removal of high-leverage outliers and in some cases only modest variation in prob

49 or a standard, and thus automatically detect outliers and increase the reliability of quantification.

50 Model comparison by HBI is robust against outliers and is not biased towards overly simplistic mod

51 ultrasound measurements were scrutinized for outliers and leverage points, and those measurements tak

52 R-Egger regression showed that no instrument outliers and no horizontal pleiotropy were likely to bia

53 on, and thus has superior robustness against outliers and other noise.

54 lity control samples can be used to identify outliers and quantify systematic trends to improve downs

55 We show that FARDEEP is less susceptible to outliers and returns a better estimation of coefficients

56 ublished deconvolution methods, is robust to outliers and selection of tuning parameters, and is fast

57 Upon the remove of outliers and the borrowing information among similar sam

58 Both spectral (x-outlier) and analyte (y-outlier) outliers can be detecte

59 major limitations: (i) they are sensitive to outliers, and (ii) they perform only one statistical tes

60 rocedure helps to overcome masking effect in outliers, and a backward step eliminates swamping effect

61 e conducted consistency analysis, identified outliers, and assessed heterogeneity for GWG.

62 performs existing methods in the presence of outliers, and identifies unique sets of genes.

63 cs, like frequent patterns, spatial changes, outliers, and spatiotemporal clusters.

64 first applied DBSCAN algorithm to eliminate outliers, and then used Limma statistical method to dete

65 for Framingham risk score, when excluding TL outliers, and when adjusting for CMV-seropositivity, HCV

66 of the variation in delta(15) N, 45% if one outlier ant species was omitted.

67 s maximized sensitivity while a most extreme outlier approach maximized specificity.

68 Using a robust outlier approach, we identified 4,452 unique autosomal e

69 We found that conventional statistical outlier approaches were biased toward identifying candid

70 In contrast, when uninformative outliers are expected to occur occasionally, surprising

71 Thus, we show that many DNA methylation outliers are not technical artefacts, but define epigene

72 ancer, CEACAM5 was a persistent longitudinal outlier as early as 26.5 months pre-diagnosis.

73 nds, demonstrating that he is not as much an outlier as he initially seems.

74 ip plots showed the DRC66 sequence is not an outlier as would be expected if dating estimates from mo

75 Outlier association with QOL was then assessed using a l

76 itionally show a correction method for these outliers based on PARAFAC2 model scores, such that full

77 ed square to automatically detect and remove outliers before estimating the cell compositions.

78 istical methods are implemented for treating outliers, benchmarking sampling adequacy, characterizing

79 the presence of mangroves on the latitudinal outlier Bermuda.

80 s inform removal of population-based extreme outliers but an absence of tools limits cleaning of long

81 es identified RVs associated with expression outliers, but varying outlier definitions were employed

82 of theories and techniques aim to detect the outliers by first fitting the majority of the data and t

83 eight, expression-based QC tool that detects outliers by implementing various statistical approaches.

84 spectral (x-outlier) and analyte (y-outlier) outliers can be detected separately or in tandem with SR

85 In practice, the proportion of outliers can be estimated according to the inaccuracy of

86 rther, to the geometry of decision-making in outlier cells, in order to define evolution-resistant ca

87 iting-outcome heterogeneity and detection of outlier clones.

88 We also identify rare 'outlier' clones that deviate from these dynamics, and fu

89 We identified about 1,900 outlier coding genes with excess of wild or domestic anc

90 is highly sensitive to the presence of a few outlier companies, and confirm that nearly all biotech c

91 the presented state is a [Formula: see text] outlier compared with the sampled ranks (its rank is in

92 rtion of hospitals classified as statistical outliers compared.

93 ddressing model mis-specification as well as outliers/contaminations in response variables and covari

94 action analyses, model mis-specification and outliers/contaminations in response variables and covari

95 n a conserved motif of Rad50, resulted in an outlier curative response in a clinical trial.

96 thereafter; and explanations of whether any outliers (data points or entire experiments) were elimin

97 ciated with expression outliers, but varying outlier definitions were employed and no comprehensive o

98 different samples are also often flagged as outliers depending on the outlier measure used.

99 After outlier designation, in-hospital mortality declined at o

100 ne changes in overall model fit and hospital outlier designations.

101 nted in this paper is SRD to detect multiple outliers despite the effects of masking and swamping.

102 Overall, enetLTS had the best outlier detection accuracy with false positive rates < 0

103 With 1% or 2% outliers, Ensemble showed high outlier detection accuracy, but with higher proportions

104 using consecutive adaptation of a well-known outlier detection algorithm, density based clustering of

105 Principal component analysis-based outlier detection analysis found a few loci associated w

106 tuning parameter values thereby simplifying outlier detection and providing improved detection.

107 Based on the total distance, a threshold for outlier detection has been developed by means of a data-

108 idely used in multivariate data analysis for outlier detection in chemometrics and engineering.

109 Sample outlier detection is imperative before calculating a mul

110 Presented, and used by SRD, are several new outlier detection measures.

111 k calling R package l1kdeconv based on a new outlier detection method and an aggregate Gaussian mixtu

112 The accuracy of biomarker selection and outlier detection of these methods needs to be evaluated

113 hreshold is used as a basis for a sequential outlier detection procedure.

114 ric height and weight data that incorporates outlier detection using robust linear regression methodo

115 notype liftOver, quality control, population outlier detection, haplotype pre-phasing, imputation, po

116 application of the sequential procedure for outlier detection.

117 The data were used to identify outliers, determine prediction intervals, and define acc

118 nt (DM) L546A/L754A is considered a dramatic outlier, due to the unprecedented size and near temperat

119 The PCA-X and Hotelling T2 test showed outliers during the months with lowest concentrations of

120 predictors alone are sufficient to identify outliers (e.g., in the 99th percentile of polygenic scor

121 Sensitivity analyses revealed no outlier effects.

122 at models technical excess zeros, identifies outliers efficiently, and evaluates differential express

123 QC, an expression-based QC tool that detects outliers either produced due to variable laboratory cond

124 ion accuracy, but with higher proportions of outliers Ensemble missed many mislabeled samples.

125 With 1% or 2% outliers, Ensemble showed high outlier detection accurac

126 Outliers, especially in high-dimensional space, can be d

127 stic tissue represent infrequent stochastic "outlier" events.

128 ss to identify regulators or genes that have outlier expression in large patient cohorts.

129 ecific expression accompanied by an elevated outlier expression.

130 Outlier facilities were larger, treating more patients w

131 lysis of LC-MS data was used to identify key outlier features in the spectra.

132 Among 86 hospitals, 31 were reported as outliers for excess mortality.

133 Of the hospitals designated high outliers for mortality and readmissions by the Centers f

134 is framework will be useful to better detect outlier-free genetic and epigenetic signatures in variou

135 irst millennium BC, with the exception of an outlier from the third millennium BC, who had primarily

136 ile that matches ancient DNA from 11 genetic outliers from sites in Iran and Turkmenistan in cultural

137 algorithm with the artificial generation of outliers from the authentic samples.

138 ns allows for the identification of relevant outliers from the body size - fundamental frequency (f(0

139 allow for the identification of interesting outliers from the body size-f(0) regression [3].

140 s distance removed 131 (7.1%) and 137 (7.4%) outliers from the structure and function regressions, re

141 that many epivariations are associated with outlier gene expression.

142 Outlier genes were enriched for proximal rare variants,

143 More than 600 outlier genes were significantly enriched for Gene Ontol

144 Samples with bacterial outliers had significantly depressed alpha-diversity (me

145 er, the binocular 10-2 sensitivities of 24-2 outliers had the strongest association with the composit

146 of underexpression and 28% of overexpression outliers have nearby conserved rare variants compared to

147 stitutions, 108 428 (21%) were treated at an outlier hospital after public report.

148 omes were compared among patients treated at outlier hospitals before and after public report of outl

149 Overall agreement in the designation of outlier hospitals between in-hospital and 30-day RSMRs w

150 the hierarchical model was used to identify outlier hospitals where the odds of delayed fixation wer

151 When used to identify outlier hospitals with high or low mortality, the agreem

152 rtality data for the purposes of identifying outlier hospitals.

153 The accuracy of variable selection, outlier identification, and prediction of three methods

154 For outlier identification, enetLTS is the recommended metho

155 Outliers identification considered the longitudinal natu

156 emble on a subset of data after removing the outliers identified by enetLTS improved the variable sel

157 ariable selection on a subset after removing outliers identified by enetLTS.

158 Here, we announce Detecting Relative Outlier Impacts from Molecular Dynamic Simulation (DROID

159 in theory for an individual to be a low-risk outlier in all conditions simultaneously.

160 spitals that were recognized as negative PCI outliers in 2 states (Massachusetts and New York) from 2

161 We begin by detecting outliers in a single exposure-outcome MR analysis, hypot

162 Outliers in agreement with other scales are oxygen and f

163 d 49 physicians (35.8%) were persistent high outliers in all 3 years.

164 Due to feature redundancy or outliers in samples, using all available data for traini

165 n contemporaries in Africa, Neandertals were outliers in terms of behavioral complexity.

166 Outliers in the cell data distribution are particularly

167 used to illustrate the behavior of possible outliers in the regression model and their corresponding

168 l approach to taking against the presence of outliers in the sample while also mitigating small sampl

169 The Brassicaceae are also outliers in the sense that they have lost the common sym

170 maps in the presence of motion artifacts and outliers in the video recordings.

171 es of models together decreases the error on outliers, indicating that the combination of several app

172 Studies of outliers-individuals remaining uninfected despite viral

173 lihood of in-hospital mortality decreased at outlier institutions (RR, 0.83; 95% CI, 0.81-0.85) after

174 went PCI, in-hospital mortality decreased at outlier institutions after public recognition of outlier

175 signation, in-hospital mortality declined at outlier institutions to a greater extent than was observ

176 When the proportion of outliers is > 5%, Ensemble can be used for variable sele

177 When the proportion of outliers is <=5%, Ensemble can be used for variable sele

178 ients suggests that identifying RNA splicing outliers is particularly useful for determining causal M

179 fects between groups with high variation and outliers, is pointed out.

180 owed for the identification of proteins with outlier levels of missingness that differentiate between

181 g genetic markers, our study identified four outlier loci clearly associated with resistance.

182 Markers at outlier loci delineated a geographic region associated w

183 rs of differentiation; and (iii) identifying outlier loci hypothesized to underlie adaptive divergenc

184 Clustering analyses based on these outlier loci indicated that recruits at the southern end

185 Scan and Sambetaada) were used to search for outlier loci indicating signatures of selection.

186 that were potentially under selection using outlier loci methods, and mapped their main gradients of

187 ution and show that the degree of deviation (outlier magnitude) relates to specific attention-deficit

188 Use of rank-based outliers maximized sensitivity while a most extreme outl

189 Potential outliers may severely undermine the correct classificati

190 o often flagged as outliers depending on the outlier measure used.

191 ol that can simultaneously evaluate multiple outlier measures across windows of tuning parameter valu

192 The outlier measures Hotelling's t-squared, Q-residuals, and

193 ps, we identified 809 segregating expression outliers (median z score of 2.97), averaging 13.3 genes

194 to determine the pathogenic significance of outlier microbes in the lungs of immunocompromised child

195 t where surprise was indicative of a one-off outlier (oddball).

196 Pseudotrichonympha pearti is the outlier of the trio, more distantly related to P. leei a

197 f such data often suffers from detecting the outliers of the samples, which subsequently affects the

198 separate mutants of interest from phenotypic outliers of the wild-type population.

199 tinuous (per IQR increase) variable or after outliers of total vitamin K intake (defined as a value t

200 ifty percent of hospitals were a statistical outlier on at least 1 measure.

201 he presented state is an [Formula: see text]-outlier on the walk is significant at [Formula: see text

202 ur research ranks the impact of the negative outliers on CHD and then quantifies the impact of the po

203 Secondly, we identified the genomic outliers or "rebel genes" within each clade.

204 genetic data are not robust with respect to outliers or influential observations.

205 Here we identify gene expression outliers, or individuals showing extreme expression leve

206 as possible causes of disease by parsing for outlier organisms.

207 Both spectral (x-outlier) and analyte (y-outlier) outliers can be detected separately or in tande

208 00-106 mum) eyes and only after exclusion of outliers (P = .01).

209 e to a deteriorating patient and the care of outlier patients as error-prone processes.

210 We aimed to investigate 3 outlier patients who ultimately achieved independent fun

211 The dilemma of managing the outlier physician is especially complex.

212 Outlier physician practices in health care can represent

213 To study outlier physician practices in Mohs micrographic surgery

214 Characteristics of outlier physicians, defined as those whose mean number o

215 Outliers possibly requiring secondary intervention were

216 ive ALCL pathogenesis, we applied the cancer outlier profile analysis algorithm to a gene expression

217 f scaling between energy and size, and their outliers provide new avenues for physiological and ecolo

218 is crucial for controlling the appearance of outliers; rare cells with unusually high levels of sasA

219 ments and their components, including index, outlier, readmission, physician services, and postdischa

220 stics, 57 hospitals (26%) were identified as outliers, reflecting significant practice variation unex

221 er novel genes more often overlap with F(ST) outlier regions.

222 The likelihood of PCI at outlier (relative risk [RR], 1.13; 95% confidence interv

223 ly expressed gene detection before and after outlier removal as well as with and without batch effect

224 adversarial nets (GAN) is proposed, named as outlier removal auxiliary classifier generative adversar

225 Outlier removal can significantly improve the performanc

226 hat includes both pre-GWAS analysis, such as outlier removal, data transformation and calculation of

227 After outlier removal, the LMS (Lambda-Mu-Sigma) function with

228 re performed for clusters identification and outliers removal.

229 e elucidating the molecular underpinnings of outlier responses and informing strategies to extend suc

230 While rare outlier responses to anticancer therapies exist, barrier

231 ith low oxygen tolerating bacteria, two high outliers resulted in this difference being non-significa

232 tionale for the evolution of the BCO-related outlier RPE65 retinol isomerase, an enzyme that does not

233 We developed Outlier-RV Enrichment (ORE) to identify biologically-mea

234 Both rPCA methods detected the same two outlier samples but cPCA failed to detect any.

235 A) methods, PcaHubert and PcaGrid, to detect outlier samples in multiple simulated and real biologica

236 om genes with high expression and identified outlier samples with a 2-fold greater PCR duplication ra

237 ical RNA-seq data sets with positive control outlier samples.

238 s an accurate and objective method to detect outlier samples.

239 If the genome contains outlier sequences extraordinarily sensitive to environme

240 s, together with a dispersed set of diverse 'outlier' sequences.

241 ) using MR-PRESSO estimates corrected for an outlier SNP (rs550057) from the highly pleiotropic gene

242 Finally, we identified eleven colocalized outlier SNPs associated with seed mass and precipitation

243 The divergence among microhabitats for these outlier SNPs is larger than that among populations, exce

244 ished LeafCutter in the context of detecting outlier splicing events.

245 A novel algorithm using outlier statistics on RNA-sequencing junction expression

246 Agreement in outlier status between the models before and after inclu

247 ier institutions after public recognition of outlier status in comparison with prior (RR, 0.72; 9% CI

248 Persistent high outlier status was associated with performing Mohs surge

249 hospitals before and after public report of outlier status.

250 and nonoutlier institutions after report of outlier status.

251 (interaction P=0.50) after public report of outlier status.

252 he physician characteristics associated with outlier status.

253 ion were not associated with persistent high outlier status.

254 ta-analyses, highlighting overly influential outlier studies with the potential to inflate genetic si

255 as only for the discounting domain, after an outlier study was excluded.

256 The sensitivity of global mean trends to outliers suggests that more informative indices are need

257 Using these variance estimates in a dosage outlier test (ANEVA-DOT) applied to AE data from 70 Mend

258 Based on outlier tests, we found high incidence of signatures of

259 , greater precision, and substantially fewer outliers than did single-time-point methods.

260 d Ensemble were less accurate in identifying outliers than enetLTS.

261 The assay using the SP142 antibody is an outlier that detected significantly less PD-L1 expressio

262 ixed-methods framework for studying positive outliers that can be applied across diverse health and d

263 ion data are frequently contaminated by many outliers that decrease the estimation accuracy.

264 Investigating therapeutic "outliers" that show exceptional responses to anti-cancer

265 ing parameter dependent and sensitive to the outlier themselves, i.e., the measures are susceptible t

266 low- and high-risk groups were analyzed for outliers to identify the threshold 8-OHdG value that wou

267 erlapping, or found to represent significant outliers to the approximation model are removed from the

268 The only outliers to the Bronsted correlation are the reactions w

269 (trQTLs) than SRE SNPs in general and includ outlier trQTLs for cross-population composite likelihood

270 We also discovered that outlier values of SkewIT highlight potential bacterial m

271 order to examine statistical differences and outlier values.

272 led 18 markedly elevated biochemicals (>5 sd outliers versus n = 25 controls) suggesting additional H

273 her analysis, with 4 having been rejected as outliers (via Cook distance calculations).

274 A single outlier was closely related to HAdV-D8 strains isolated

275 sample size was large and the proportion of outliers was <=5%, the positive selection rate of Ensemb

276 The mean real-life screening PPV of PERFORMS outliers was 0.14% and was significantly lower than the

277 However, when the proportion of outliers was 10% or 15%, Ensemble missed some variables

278 The mean real-life CDR of PERFORMS outliers was 7.2 per 1000 women screened and was signifi

279 Detection of outliers was based on Cook distance of the regression of

280 still performed well when the proportion of outliers was relatively large.

281 MR-Egger, MR pleiotropy residual sum and outlier, weighted median, and Phenoscanner-based sensiti

282 Notable outliers were 1 patient at 16 days and 1 patient at 21 d

283 The real-life CDR, recall rate, and PPV of outliers were compared against other readers (nonoutlier

284 Outliers were defined as patients for whom the differenc

285 Outliers were defined by O:E z-scores.

286 Statistical outliers were determined based on abundance within each

287 nd validation sets, key diastereoselectivity outliers were identified.

288 ere calculated as a compound spherocylinder, outliers were observed for 233 eyes (2.59%).

289 nents of the refractive error independently, outliers were observed in 82 eyes (0.91%) based on the s

290 less bias on average and significantly fewer outliers when estimating kidney TIA, compared with popul

291 ed to reveal the structural origins of these outliers, which was consistent with the presence of seve

292 ng differentially expressed genes (DEGs) and outliers, which will inevitably introduce some bias.

293 ion increased over time, as evinced by three outliers who can be modeled as descendants of recent mig

294 After removing 2 outliers whose EEDLW were incompatible with other data,

295 ow rigorously that the presented state is an outlier with respect to the values, by establishing a [F

296 e exons (exon 12, EPAS1), exhibiting extreme outliers with a high probability of directional selectio

297 using machine learning methods to highlight outliers with respect to such models as proteins associa

298 city in all the tests using positive control outliers with varying degrees of divergence.

299 Among the 90 samples, the SP142 assay was an outlier, with a significantly lower mean score of PD-L1

300 We identify participants who are outliers within this distribution and show that the degr

301 Removing outliers without batch effect modeling performed the bes