Clustering is a powerful and commonly used technique that organizes and elucidates the structure of biological data. Clustering data from gene expression, metabolomics and proteomics experiments has ...proven to be useful at deriving a variety of insights, such as the shared regulation or function of biochemical components within networks. However, experimental measurements of biological processes are subject to substantial noise-stemming from both technical and biological variability-and most clustering algorithms are sensitive to this noise. In this article, we explore several methods of accounting for noise when analyzing biological data sets through clustering. Using a toy data set and two different case studies-gene expression and protein phosphorylation-we demonstrate the sensitivity of clustering algorithms to noise. Several methods of accounting for this noise can be used to establish when clustering results can be trusted. These methods span a range of assumptions about the statistical properties of the noise and can therefore be applied to virtually any biological data source.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
We compared the effect of iterative model reconstruction (IMR), filtered back projection (FBP), and hybrid iterative reconstruction (HIR) on coronary artery calcium (CAC) scoring.
CAC scans of 30 ...consecutive patients (18 men and 12 women, age 70.1 ± 12.2 years) were reconstructed with FBP, HIR, and IMR, and the image noise was measured on all images. Two radiologists independently measured the CAC scores using semiautomated software, and interobserver agreement was evaluated. Statistical analysis included the Spearman correlation coefficient and Bland-Altman analysis.
The mean image noise on FBP, HIR, and IMR images was 48.0 ± 7.9, 29.6 ± 4.8, and 9.3 ± 1.3 Hounsfield units, respectively. The difference among all reconstruction combinations was significant (P < .01). The CAC score on HIR and IMR scans was 4.2% and 8.9% lower, respectively, than the CAC score on FBP images. There was no significant difference in the mean CAC score among the three reconstructions. The interobserver correlation was excellent for all three reconstructions (r
= 0.96 FBP, 0.99 HIR, 0.99 IMR); the best Bland-Altman measure of agreement was with IMR, followed by HIR and FBP.
For CAC scoring, IMR can reduce the image noise and blooming artifacts, and consequently lowers the measured CAC score. IMR can lessen measurement variability and yield stable, reproducible measurements.
AbstractInternational roughness index (IRI) is widely employed for evaluating pavement performance. It is a critical indicator used by state transportation agencies to identify the maintenance ...demands for road sections. However, the determination of IRI is susceptible to measurement variability, especially for network evaluations where the IRI value of a road section is determined only based upon a single test run. Therefore, it is necessary to understand and quantify the influence of measurement variability on pavement evaluation. In this paper, the uncertainty of pavement evaluation due to the run-to-run IRI errors was defined and quantified utilizing raw data from long-term pavement performance (LTPP). Three factors contributing to the uncertainty of pavement evaluation were investigated. They are (1) the performance thresholds, (2) variability of IRI measurement, and (3) distribution of IRI for a road network. Probabilistic relationship was constructed to consider the influence of run-to-run variability of IRI for network-level pavement evaluation. Results indicated that the uncertainty of road sections rated as good were the lowest, whereas those rated as fair were generally high. The variability of IRI measurement significantly affected the pavement evaluation for state routes.
Background
Functional MR urography (fMRU) provides comprehensive functional data that can be subject to variability. To interpret the results of fMRU, it is essential to know the intra- and ...inter-observer variability of the measured parameters.
Objective
To define the range of variability in fMRU, particularly that of the differential renal function based on volume (volumetric differential renal function) and Patlak differential renal function measurements in children.
Materials and methods
We included 15 fMRU studies, 10 of non-duplicated and 5 of unilateral duplex kidneys. We recruited six observers with a range of fMRU experience, including two MRI technologists, one resident, one fellow, one pediatric radiologist and one pediatric urologist. The observers underwent intensive training in using the Children’s Hospital of Philadelphia (CHOP)-fMRU freeware for analysis. They conducted the fMRU analysis on each case twice, at least 1 week apart. Mean and standard deviation were calculated for each set of absolute volume, absolute Patlak, volumetric differential renal function and Patlak differential renal function. We calculated the statistical significance of these deviations using the student’s
t
-test. We also calculated interclass correlations for intra-observer and inter-observer agreement of both volume and Patlak measurements using SPSS software.
Results
Intra- and inter-observer variability did not differ significantly, measuring 6% and 4% for relative volume (volumetric differential renal function:
P
> 0.05) and 5% and 3% for relative function (Patlak differential renal function:
P
> 0.05). Absolute values of parameters showed more variability than the relative values. Intra- and inter-observer agreement was well above 0.90 (
P
< 0.001) for all volume measures except for duplex upper pole intra-observer measurements (0.80,
P
< 0.01). Intra- and inter-observer agreement for Patlak values were also above 0.90 (
P
< 0.001) except for duplex upper pole measurements, which were 0.54 (
P
= 0.13) and 0.81 (
P
< 0.01), respectively.
Conclusion
Functional MRU analysis using CHOP-fMRU software is reproducible, with overall intra- and inter-observer variability rates of 5% for volumetric differential renal function and 4% for Patlak differential renal function. There was higher variability in volume and function measurements between upper and lower pole moieties of duplicated kidneys and for absolute volume and function values overall. A range of 45–55% for relative values of volumetric differential renal function and Patlak differential renal function could serve as the normal range.
Human body motion can be captured by body area sensor networks. Accurate sensor placement with respect to anatomical landmarks is one of the main factors determining the accuracy of motion-capture ...systems. Changes in position of the sensors cause increased variability in the motion data, so isolating the characteristic features that represent the most important motion patterns is our concern. As accurate sensor placement is time-consuming and hard to achieve, we propose a signal processing technique that can enable salient data to be isolated. By using functional principal component analysis (f-PCA), we compensate for the variation in data due to changes in the on-body positioning of sensors. More precisely, we investigate the use of f-PCA for filtering and interpreting motion data, whilst accounting for variability in the sensor origin. Data are collected through a marker-based motion capture system from two designed experiments based on human body and robot arm movement. Results show differences between similar actions across different sessions of marker wearing with random changes in position of sensors. After applying the f-PCA filter on the data, we show how uncertainties due to sensor position changes can be compensated for.
Vertebral rotation found in structural scoliosis contributes to trunkal asymmetry which is commonly measured with a simple Scoliometer device on a patient's thorax in the forward flexed position. The ...new generation of mobile 'smartphones' have an integrated accelerometer, making accurate angle measurement possible, which provides a potentially useful clinical tool for assessing rib hump deformity. This study aimed to compare rib hump angle measurements performed using a Smartphone and traditional Scoliometer on a set of plaster torsos representing the range of torsional deformities seen in clinical practice.
Nine observers measured the rib hump found on eight plaster torsos moulded from scoliosis patients with both a Scoliometer and an Apple iPhone on separate occasions. Each observer repeated the measurements at least a week after the original measurements, and were blinded to previous results. Intra-observer reliability and inter-observer reliability were analysed using the method of Bland and Altman and 95% confidence intervals were calculated. The Intra-Class Correlation Coefficients (ICC) were calculated for repeated measurements of each of the eight plaster torso moulds by the nine observers.
Mean absolute difference between pairs of iPhone/Scoliometer measurements was 2.1 degrees, with a small (1 degrees) bias toward higher rib hump angles with the iPhone. 95% confidence intervals for intra-observer variability were +/- 1.8 degrees (Scoliometer) and +/- 3.2 degrees (iPhone). 95% confidence intervals for inter-observer variability were +/- 4.9 degrees (iPhone) and +/- 3.8 degrees (Scoliometer). The measurement errors and confidence intervals found were similar to or better than the range of previously published thoracic rib hump measurement studies.
The iPhone is a clinically equivalent rib hump measurement tool to the Scoliometer in spinal deformity patients. The novel use of plaster torsos as rib hump models avoids the variables of patient fatigue and discomfort, inconsistent positioning and deformity progression using human subjects in a single or multiple measurement sessions.
Almost all relevant data in forestry databases arise from either field measurement or model prediction. In either case, these values have some amount of uncertainty that is often overlooked when ...doing analyses. In this study, the uncertainty associated with both measured and predicted data was quantified for upper-stem diameter at 5.27 m. This uncertainty was propagated through a tree taper model into predictions of individual-tree volume. The effects of uncertainty on individual-tree volume predictions and population estimates of total volume were assessed. Generally, when little or no systematic measurement deviation was present, less uncertainty was associated with field-measured diameters compared to model predictions. However, diameters predicted from a model were preferred when systematic deviations in field measurement exceeded approximately 0.2 cm. Comparisons of results obtained from an alternative taper model showed that more precise estimates of population totals might be obtained without upper-stem diameter information. Upper-stem diameter information increases the prediction accuracy of individual-tree volume, and thus, models using this information may be preferable in applications such as timber sales containing high-value trees. Due to the various factors that influence measurement and modeling uncertainty, foresters are encouraged to make similar evaluations in the context of their specific activities.
Purpose
To compare the use of serum and plasma in multiplex immunoassay analyses of 190 proteins and small molecules, and associated molecular pathways. We also tested whether differences between ...these biofluids can influence the identification of potential biomarkers in a preliminary study comparing bipolar disorder patients with controls.
Experimental design
Using multiplexed immunoassay analyses, we compared the measurement levels and interindividual variation of 190 proteins and small molecules between serum and plasma collected from 21 healthy individuals. We exemplify how this can impact on the outcome of biomarker discovery studies using a case study of 24 patients with bipolar disorder.
Results
Detection of analytes was similar for serum and plasma, although there were marked differences in measurement variability for 29 proteins and cortisol. When considering the disease cohort we identified six proteins that changed significantly in serum and ten in plasma with an overlap of two proteins.
Conclusions and clinical relevance
In spite of the similarities of coverage on a multiplexed platform for serum and plasma, there were important differences in interindividual variability, which can have significant impact on identifications made in biomarker studies.
To compare the measurement variability for coronary artery calcium (CAC) measurements using mineral mass compared with a modified Agatston score (AS) or volume score (VS) with multi-detector CT ...(MDCT) scanning, and to estimate the potential impact of these methods on the design of CAC progression studies.
We studied 162 consecutive subjects (83 women, 79 men, mean age 51
±
11 years) from a general Caucasian community-based cohort (Framingham Heart Study) with duplicate runs of prospective electrocardiographically-triggered MDCT scanning. Each scan was independently evaluated for the presence of CAC by four experienced observers who determined a “modified” AS, VS and mineral mass.
Of the 162 subjects, CAC was detected in both scans in 69 (42%) and no CAC was detected in either scan in 72 (45%). Calcium scores were low in the 21/162 subjects (12%) for whom CAC was present in one but not the other scan (modified AS <20 in 20/21 subjects, mean AS 4.6
±
1.9). For all three quantification algorithms, the inter- and intraobserver correlation were excellent (
r
>
0.96). However, the mean interscan variability was significantly different between mineral mass, modified AS, and VS (coefficient of variation 26
±
19%, 41
±
28% and 34
±
25%, respectively;
p
<
0.04), with significantly smaller mean differences in pair-wise comparisons for mineral mass compared with modified AS (
p
<
0.002) or with VS (
p
<
0.03). The amount of CAC but not heart rate was an independent predictor of interscan variability (
r
=
−0.638, −0.614 and −0.577 for AS, VS, and mineral mass, respectively; all
p
<
0.0001). The decreased interscan variability of mineral mass would allow a sample size reduction of 5.5% compared with modified AS for observational studies of CAC progression and for randomized clinical trials.
There is significantly reduced interscan variability of CAC measurements with mineral mass compared with the modified AS or VS. However, the measurement variability of all quantification methods is predicted by the amount of CAC and is inversely correlated to the extent of partial volume artifacts. Moreover, the improvement of measurement reproducibility leads to a modest reduction in sample size for observational epidemiological studies or randomized clinical trials to assess the progression of CAC.
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