ライフサイエンスコーパス: outlier

1 among them were successfully identified as "outliers".

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

3 phe ICC value was sensitive to a measurement outlier.

4 l had been publicly identified as a negative outlier.

5 model of mesothelial development may be the outlier.

6 tion from ASP norms from all other issues of outliers.

7 esent, although it can be highly affected by outliers.

8 logistic regression to identify statistical outliers.

9 hus favouring algorithms which are robust to outliers.

10 minP and maxP, is that they are sensitive to outliers.

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

12 case of missing and/or corrupted data due to outliers.

13 , a measure least sensitive to postoperative outliers.

14 o identify both abnormalities and biological outliers.

15 ication of a certain fraction of the data as outliers.

16 n noisy data while being highly resilient to outliers.

17 ich makes them just suitable for identifying outliers.

18 n and clustering of biologically interesting outliers.

19 t high outliers and 3.0% were treated at low outliers.

20 below the overall mean) and 11 (12%) as high outliers.

21 lecules with large prediction errors, called outliers.

22 lows it to minimize the effect of expression outliers.

23 sters and between each antigenic cluster and outliers.

24 and the result is particularly sensitive to outliers.

25 sample structures in the presence of subject outliers.

26 other regions were sensitive to measurement outliers.

27 tion processes to confirm samples flagged as outliers.

28 are more likely to be designated as negative outliers.

29 tstanding stereoinduction displayed by these outliers.

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

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

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

33 white) treated at 1,349 hospitals (4.9% high outlier, 0.7% low outlier), 5.6% of patients were treate

34 ), and 24 (63%) hospitals were identified as outliers (12 low performers and 12 high performers).

35 1,349 hospitals (4.9% high outlier, 0.7% low outlier), 5.6% of patients were treated at high outliers

36 r at low outliers (79.9%) compared with high outliers (64.9%) and nonoutliers (68.9%; log-rank test,

37 Five-year overall survival was better at low outliers (79.9%) compared with high outliers (64.9%) and

38 admission ($245 [95% CI, -$231 to $721]), or outliers (-$86 [95% CI, -$1666 to $1495]).

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

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

41 ture selection paradigm for the discovery of outliers, a growing concern is that these could result f

42 30-day RSMR was much stronger (r= 0.83) and outlier agreement improved substantially (kappa=0.60).

43 Moreover, outlier allele frequencies in SW Finland resemble those

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

45 One outlier AML responded and exhibited intrinsic drug resis

46 iers with respect to a tight cluster of non- outliers, among an ordered subset of the experimental sa

47 Outlier analyses revealed a consistent signature of sele

48 Isotopic ratio outlier analysis (IROA) is a (13)C metabolomics profilin

49 to MEK inhibitor treatment, we performed an outlier analysis of a patient who experienced a complete

50 Correspondingly, we used outlier analysis to determine that PGC-1alpha is overexp

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

52 Kappa scores for identifying outlier and nonoutlier clinics between WCM and its compo

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

54 Several outlier and subgroup identification statistics (OASIS) h

55 gdom suggests that E. coli is a phylogenetic outlier and that PHP domain-mediated proofreading is wid

56 lier), 5.6% of patients were treated at high outliers and 3.0% were treated at low outliers.

57 data, there were similar numbers of hospital outliers and correlations between logged OR and standard

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

59 skal-Wallis test is more robust against data outliers and heterogeneous genotype group sizes and dete

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

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

62 t allows identification of performance-based outliers and may represent a rectal cancer surgery quali

63 ot seriously affected by data issues such as outliers and moderately non-linear trends.

64 to make false inferences in the presence of outliers and noise.

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

66 However, study heterogeneity, study bias, outliers and the lack of power of available methods pres

67 re designed for at-a-glance determination of outliers and trends in the datasets, together with relev

68 le, or experimental condition, revealing any outliers and/or systematic issues that could drive false

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

70 distinct clusters; the NDM-1 isolate was an outlier, and the IMP isolates and 6/7 MBL-negative isola

71 inuous and discrete populations with subject outliers, and it can be considered as an extension of th

72 atistics are fast to compute, robust against outliers, and show comparable and often better general p

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

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

75 ng any restrictive assumptions about how the outliers are distributed.

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

77 Outlier association with QOL was then assessed using a l

78 nally, we describe the effectiveness of this outlier attack under different scenarios.

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

80 Hospital performance was categorized as low outlier (better than expected), high outlier (worse than

81 f TCR-pMHC complexes, and for a case with an outlier binding mode, we found that alternative docking

82 SZ cases showed higher outlier burden (i.e., total outlier events per subject)

83 Medicare claims, 26% were also identified as outliers by ACS-NSQIP.

84 trative databases) reduced the number of low outliers by approximately one-third, but results differe

85 ed by ACS-NSQIP, 16% were also identified as outliers by Medicare claims.

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

87 Outlier classification changed postadjustment for 29.3%,

88 iting-outcome heterogeneity and detection of outlier clones.

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

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

91 The cerebellum was a consistent outlier compared to all other regions, and showed over 1

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

93 Risk of death was lower at low outliers compared with high outliers (hazard ratio [HR],

94 Risk of death was higher at high outliers compared with nonoutliers (HR, 1.12; 95% CI, 1.

95 ehavioral contrast makes humans appear to be outliers compared with other primates because of our alm

96 rtion of hospitals classified as statistical outliers compared.

97 nalyses attempting to minimize the effect of outliers, concurrent complications, procedural differenc

98 We describe a methodology to identify outlier conditions by considering the cell-level measure

99 ostnatal care and morbidities, assessment of outliers, covariates, and chart presentation.

100 orted on an insurance claim form or dropping outlier data points from a figure to make a paper sound

101 h across human tumour samples for transcript outlier data points with associated gene copy number var

102 o evaluate replicate reproducibility, detect outlier data points, fit different models, select the be

103 Functional annotation check on detected outliers demonstrate that the methods are able to identi

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

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

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

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

108 Sample outlier detection is imperative before calculating a mul

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

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

111 t to outliers, so no additional denoising or outlier detection step is needed in data preprocessing.

112 nsive offline data manipulation required for outlier detection, derivation and application of algorit

113 his new "on-demand" approach with respect to outlier determinations, kappa statistics, and correlatio

114 ithout making explicit assumptions about the outlier distribution.

115 te distinction and clustering of interesting outlier distributions.

116 st, algorithms which recognise heterogeneous outlier DNA methylation patterns are able to identify ma

117 Without removing any outliers due to ectopic beats, the method is able to det

118 Sensitivity analyses revealed no outlier effects.

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

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

121 es showed higher outlier burden (i.e., total outlier events per subject) than controls for genes with

122 stic tissue represent infrequent stochastic "outlier" events.

123 to represent the mean) was highly skewed by outliers, exceeding the 97(th) percentile at some freque

124 ith high sub-clonal enrichment of AR-GSRs is outlier expression of diverse AR variant species lacking

125 Outlier facilities were larger, treating more patients w

126 would likely result in the hospital being an outlier for performance.

127 We identified facility outliers for 30-day risk-standardized hospitalization, m

128 monstrate that chemosensory proteins are not outliers for adaptive divergence between species.

129 Of hospitals identified as statistical outliers for better or worse performance by Medicare cla

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

131 the tight cluster of low expressions and the outliers for hDEGs.

132 return urine samples for measuring UIC and 2 outliers for UIC.

133 We find several outliers from a mouse ESC RNAi screen that we confirm to

134 linking attacks and a specific attack using outlier gene expression levels that is simple yet accura

135 These outlier genes were enriched for brain expression and for

136 Outlier genes were enriched for CNVs and for rare putati

137 Outlier genes were enriched for proximal rare variants,

138 It identifies outlier genes with effects on the reporter distribution

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

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

141 was lower at low outliers compared with high outliers (hazard ratio [HR], 0.61; 95% CI, 0.50 to 0.75)

142 ed, and we identify a dopamine pathway as an outlier, highlighting the system as a potential cause of

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

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

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

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

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

148 rtality data for the purposes of identifying outlier hospitals.

149 a (SZ) cases and 713 controls for expression outliers (i.e., extreme tails of the distribution of tra

150 Of outliers identified by ACS-NSQIP, 16% were also identifi

151 In addition, the number and degree of outliers identified suggest a high degree of variability

152 e proposed algorithm assesses each potential outlier in relation to the cluster of potential outliers

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

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

155 of which 6-19% occurred simultaneously with outliers in other vital signs.

156 Dissimilarity metrics revealed outliers in performance, and a nested ANOVA model reveal

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

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

159 instability of signal acquisition and (iii) outliers in the lower limit and margin events in the upp

160 that can handle both normal errors and large outliers in the optimization process.

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

162 bandgap QD samples result from large bandgap outliers in the size distribution.

163 acid residues in HCV E2 could explain these outliers in the tested cases of AR5A and HC84.26.

164 As the first selected outliers indeed had experimental problems, including hyd

165 quintile of the birth weight distribution, 'outlier' individuals are significantly more common among

166 Such 'outlier' individuals differ substantially from the rest

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

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

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

170 for missing data imputation and detection of outliers is that the uncorrupted data matrix is low rank

171 We identify PCAT-1, a prostate cancer outlier lncRNA, which regulates cell response to genotox

172 We identified 15 outlier loci among candidate SNPs, mostly related to fli

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

174 Markers at outlier loci delineated a geographic region associated w

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

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

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

178 Up to 51% of outlier loci overlapped between transect pairs and up to

179 At outlier loci, allele frequencies in SW Finland shifted i

180 ation as well as the genomic distribution of outlier loci.

181 istory of secondary contacts in interpreting outlier loci.

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

183 a protein concentration predictor from which outliers may be extracted in a systematic manner.

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

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

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

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

188 the other sites, strongly influenced by five outlier microsatellite loci located in conserved interge

189 o well-established methods in selecting good outlier models from a large set of models of mostly low

190 econstruction accuracy and is more robust to outlier noises than many existing state reconstruction a

191 date divisions and one phylotype that was an outlier of candidate division OP3.

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

193 sign days contained at least one statistical outlier, of which 6-19% occurred simultaneously with out

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

195 ct zones, and the potential selection-driven outliers on next-generation molecular markers.

196 Statistical outliers on the basis of high and low utilization were i

197 ll low and it remains to be seen if they are outliers or if macrocycles will open up novel oral drugg

198 sed to discover transcriptomic features with outliers or multiple modes in expression that are indica

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

200 lassified as low or as high excess mortality outliers; others changed classification depending on the

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

202 uality assessment in surgery focused on true outlier performance rather than process or clinical outc

203 Seventeen (19%) systems were labeled as low outliers (performance significantly below the overall me

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

205 Outlier physician practices in health care can represent

206 To study outlier physician practices in Mohs micrographic surgery

207 ate efforts to achieve the goal of modifying outlier physicians' behavior.

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

209 Prior analyses were driven by an outlier population and unbalanced treatment groups in po

210 Careful analysis of such outlier populations is most likely to shed light on the

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

212 loss using quantile regression and extracts outlier proteins whose measured concentrations are lower

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

214 ns projecting to the posterior striatum were outliers, receiving relatively few inputs from the ventr

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

216 identifying shifts in variation, discovering outlier regions and locating and extracting interesting

217 The first approach, outlier rejecting regression, allows explicit specificat

218 t the same time provides a robust method for outlier rejection, selecting for removal any replicate p

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

220 Few outliers remained.

221 of complexity in physiological signals with outliers remains a major barrier for translating this no

222 re performed for clusters identification and outliers removal.

223 The analysis was performed with outliers removed to assess their impact.

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

225 While rare outlier responses to anticancer therapies exist, barrier

226 Targeted cancer therapies often induce "outlier" responses in molecularly defined patient subset

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

228 Outliers resulting from differential direct targeting we

229 m Mann-Whitney statistics and multi-platform outlier robust T-statistics, and a parametric method, mu

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

231 es multiple QC measures designed to identify outlier samples and batch effects; and (iv) provides a v

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

233 n localization responses are real (or due to outliers, sampling bias, or other factors), and (2) whet

234 ariates; transform data; remove or winsorize outliers; select covariates for analysis; and create res

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

236 en meta-analysis was performed excluding the outliers, significant pooled ORs were found for all pati

237 Using random effects models, outlier sites were identified based on 95% confidence in

238 3%, 16.1%, and 26.5% of low-, non-, and high-outlier sites, respectively.

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

240 1,364 outlier SNPs were mapped on the annotated D. pulex genom

241 ryotic Orthologous Groups that we found from outlier SNPs, 294 were involved in three metabolic and f

242 yet effective; it is intrinsically robust to outliers, so it is particularly suitable for diagnostic/

243 It is robust to outliers, so no additional denoising or outlier detectio

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

245 The association between outlier status and overall risk of death at 5 years was

246 each data source, classification of hospital outlier status as better or worse performance than expec

247 reement between the data sources on hospital outlier status classification was uniformly poor (weight

248 Hospital statistical outlier status for better or worse performance than expe

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

250 Hospital RAMP outlier status is a rectal cancer surgery composite metr

251 1.9% of hospitals and worse in 22.8% and the outlier status of 28.3% of hospitals changed.

252 diagnosis of sepsis or respiratory failure, outlier status under the broader definition improved in

253 Persistent high outlier status was associated with performing Mohs surge

254 hospitals before and after public report of outlier status.

255 ion were not associated with persistent high outlier status.

256 and nonoutlier institutions after report of outlier status.

257 measures were significantly associated with outlier status.

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

259 he physician characteristics associated with outlier status.

260 his only explained a small proportion of the outlier subjects, highlighting the underlying presence o

261 However, an outlier subset of tumor-associated ncRNAs, typically of

262 ed without need for thresholding or dropping outlier swimmers from study.

263 ptive trait phenotyping was coupled with FST outlier tests and sliding window analysis to assess the

264 ironmental selection, via multiple stringent outlier tests, and correlations with temperature.

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

266 rk is robust against bias, less sensitive to outliers than other methods, and more sensitive to small

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

268 ach population, precluding identification of outliers that affect the distribution of the reporter in

269 g of ligand binding and identify interesting outliers that do not behave as expected.

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

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

272 utylphthalocyanine [Mn((t)BuPc)], that is an outlier to the reactivity-selectivity paradigm.

273 ormatically perturbed datasets) and by using outliers to model multiple resistance mechanisms.

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

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

276 rdized mean difference after exclusion of an outlier trial, -0.33 [CI, -0.56 to -0.09]; SOE, low), an

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

278 h outlier (worse than expected), or non-RAMP outlier using standard observed-to-expected methodology.

279 he features of interest and detection of the outliers using a sparsity promoting l 1 penality.

280 order to examine statistical differences and outlier values.

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

282 6a, although for all HMAbs, except AR4A, an outlier was observed.

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

284 When outliers were accounted for, we generated >80% genome co

285 The number and distribution of statistical outliers were calculated for all measures.

286 ystematically varied, key enantioselectivity outliers were identified and analyzed.

287 When adjusting for risk, performance outliers were identified at the surgeon and institutiona

288 nd validation sets, key diastereoselectivity outliers were identified.

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

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

291 - 0.54 D) in the T7-T9 subgroup (excluding 1 outlier whose corneal astigmatism doubled after surgery)

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

293 hDEGs by sequentially testing for potential outliers with respect to a tight cluster of non- outlier

294 Previous work showed that in such a setting, outliers with respect to the model are reliable candidat

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

296 The star-nosed mole was an outlier, with more than twice the number of trigeminal n

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

298 lier in relation to the cluster of potential outliers without making explicit assumptions about the o

299 as low outlier (better than expected), high outlier (worse than expected), or non-RAMP outlier using

300 Many of these outliers would have been missed by other analysis method