OutlierD: an R package for outlier detection using quantile regression on mass spectrometry data

Cho, Hyungjun; Kim, Yang Jin; Jung, Hee Jung; Lee, Sang Won; Lee, Jae Won

doi:10.1093/bioinformatics/btn012

Cited by 32 publications

(33 citation statements)

References 5 publications

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“…M is the difference between the duplicate samples and A is the average of the duplicate samples [30, 31]. Samples that fell outside the lower 25% and upper 25% quantiles of this MA-plot were rejected (Additional file 4).…”

Section: Methodsmentioning

confidence: 99%

Serological markers to measure recent changes in malaria at population level in Cambodia

Kerkhof

Sluydts

Willen

et al. 2016

Malar J

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BackgroundSerological markers for exposure to different Plasmodium species have recently been used in multiplex immunoassays based on the Luminex technology. However, interpretation of the assay results requires consideration of the half-life of specific antibodies against these markers. Therefore, the aim of the present study was to document the half-life of malaria specific serological makers, as well as assessing the sensitivity of these markers to pick up recent changes in malaria exposure.MethodsA recently developed multiplex immunoassay was used to measure the intensity of antibody (Ab) responses against 19 different Plasmodium specific antigens, covering different human malaria parasites and two vector saliva antigens. Therefore, 8439 blood samples from five cross-sectional surveys in Ratanakiri, Cambodia, were analysed. These involve a random selection from two selected surveys, and an additional set of blood samples of individuals that were randomly re-sampled three, four or five times. A generalized estimating equation model and linear regression models were fitted on log transformed antibody intensity data.ResultsResults showed that most (17/21) Ab-responses are higher in PCR positive than PCR negative individuals. Furthermore, these antibody-responses follow the same upward trend within each age group. Estimation of the half-lives showed differences between serological markers that reflect short- (seasonal) and long-term (year round) transmission trends. Ab levels declined significantly together with a decrease of PCR prevalence in a group of malaria endemic villages.ConclusionFor Plasmodium falciparum, antibodies against LSA3.RE, GLURP and Pf.GLURP.R2 are most likely to be a reflexion of recent (range from 6 to 8 months) exposure in the Mekong Subregion. PvEBP is the only Plasmodium vivax Ag responding reasonably well, in spite of an estimated Ab half-life of more than 1 year. The use of Ab intensity data rather dichotomizing the continuous Ab-titre data (positive vs negative) will lead to an improved approach for serological surveillance.Electronic supplementary materialThe online version of this article (doi:10.1186/s12936-016-1576-z) contains supplementary material, which is available to authorized users.

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Section: Methodsmentioning

confidence: 99%

Serological markers to measure recent changes in malaria at population level in Cambodia

Kerkhof

Sluydts

Willen

et al. 2016

Malar J

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“…Cho et al [4] proposed a more elaborate approach for detecting outliers with low false positive and negative rates in MS data to solve the problem when the number of technical replicates is two. The algorithm was developed by utilizing quantile regression for duplicate MS experiments.…”

Section: Resultsmentioning

confidence: 99%

“…Cho et al [4] proposed the construction of lower and upper fences using quantile regression in an MA plot with M and A values in vertical and horizontal axes, respectively, where M j is the difference between replicated samples for j and A j is the average, i.e.

M_{j} = y_{1 j} - y_{2 j} = \underset{2}{log} (x_{1 j} / x_{2 j})

and

A_{j} = (y_{1 j} + y_{2 j}) / 2 = (1 / 2) \underset{2}{log} (x_{1 j} x_{2 j})

to detect the outliers accounting for the heterogeneity of variability.…”

Section: Resultsmentioning

confidence: 99%

Outlier Detection using Projection Quantile Regression for Mass Spectrometry Data with Low Replication

Pak

Choi

et al. 2012

BMC Res Notes

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BackgroundMass spectrometry (MS) data are often generated from various biological or chemical experiments and there may exist outlying observations, which are extreme due to technical reasons. The determination of outlying observations is important in the analysis of replicated MS data because elaborate pre-processing is essential for successful analysis with reliable results and manual outlier detection as one of pre-processing steps is time-consuming. The heterogeneity of variability and low replication are often obstacles to successful analysis, including outlier detection. Existing approaches, which assume constant variability, can generate many false positives (outliers) and/or false negatives (non-outliers). Thus, a more powerful and accurate approach is needed to account for the heterogeneity of variability and low replication.FindingsWe proposed an outlier detection algorithm using projection and quantile regression in MS data from multiple experiments. The performance of the algorithm and program was demonstrated by using both simulated and real-life data. The projection approach with linear, nonlinear, or nonparametric quantile regression was appropriate in heterogeneous high-throughput data with low replication.ConclusionVarious quantile regression approaches combined with projection were proposed for detecting outliers. The choice among linear, nonlinear, and nonparametric regressions is dependent on the degree of heterogeneity of the data. The proposed approach was illustrated with MS data with two or more replicates.

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“…The reporter ion peak intensities of identical peptides were summed, and those values were log 2 transformed. Outliers were removed as described previously (23). Ratios generated during the optimization experiment were set relative to 1ϫ, and means were normalized to their respective replicates (24).…”

Section: Methodsmentioning

confidence: 99%

cysTMTRAQ—An Integrative Method for Unbiased Thiol-based Redox Proteomics

Parker

Balmant

Zhu

et al. 2015

Molecular & Cellular Proteomics

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Protein redox regulation plays important roles in many biological processes. Protein cysteine thiols are sensitive to redox changes and may function as redox switches, which turn signaling and metabolic pathways on or off to ensure speedy responses to environmental stimuli or stresses. Here we report a novel integrative proteomics method called cysTMTRAQ that combines two types of isobaric tags, cysteine tandem mass tags and isobaric tag for relative and absolute quantification, in one experiment. The method not only enables simultaneous analysis of cysteine redox changes and total protein level changes, but also allows the determination of bona fide redox modified cysteines in proteins through the correction of protein turnover. Changes in the redox states of protein cysteine thiols serve as regulatory switches in diverse biological processes (1). The redox cycle is regulated by well-known factors such as the ferredoxin-thioredoxin and glutathione-glutaredoxin systems, which reduce oxidized cysteines. Other oxidoreductases and oxidants such as reactive oxygen species act primarily to oxidize cysteine thiol groups (2, 3). In order to map and quantify cysteine redox modifications on the proteome scale, several approaches and methods have been developed, mostly using thiol-specific reagents and isotope tags. Twodimensional gel electrophoresis technology combined with fluorescent dye labeling (e.g. monobromobimane (4, 5) and cyanine dyes (6, 7)) and gel-free technology with isotope tagging (e.g. isotope-coded affinity tagging (6 -8), cysTMT 1 (9), and iTRAQ labeling of enriched cysteine-containing peptides (10 -14)) are often used to identify potential redox-sensitive cysteine residues and quantify redox changes.In addition to the well-known capabilities and limitations associated with two-dimensional gel electrophoresis-based and gel-free approaches (15), each method has its strengths and weaknesses in redox proteomics. For example, the twodimensional gel electrophoresis methods allow the inspection of spot patterns related to redox and protein-level changes. However, spot-volume-based quantification becomes problematic, as each spot often contains more than one protein species from complex samples. In addition, the limited number of fluorescent reagents compromises multiplexing capability, and the use of cyanine dyes does not allow mapping of the modified cysteines (6, 7). Other thiol labeling approaches such as the use of N-ethylmaleimide, biotin-N-[6-(Biotinamido)hexyl]-3-(2-pyridyldithio) propionamide (16), and isotopecoded affinity tags allow specific enrichment of cysteinecontaining peptides, mapping of cysteine modification sites, and duplex experiments in the case of isotope-coded affinity tags (6, 7). To enable multiplexing, 4-or 8-plex iTRAQ tags were recently used to label cysteine-containing peptides isolated from thiol-affinity chromatography (10,11,14,16). Another multiplexing technology, cysTMT, was developed to specifically label cysteines with free thiol groups of proteins from six different sampl...

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OutlierD: an R package for outlier detection using quantile regression on mass spectrometry data

Abstract: An R package, OutlierD, is available at the Bioconductor project at http://www.bioconductor.org

Cited by 32 publications

References 5 publications

Serological markers to measure recent changes in malaria at population level in Cambodia

Serological markers to measure recent changes in malaria at population level in Cambodia

Outlier Detection using Projection Quantile Regression for Mass Spectrometry Data with Low Replication

cysTMTRAQ—An Integrative Method for Unbiased Thiol-based Redox Proteomics

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