Detection and correction of probe-level artefacts on microarrays

ABSTRACT: BACKGROUND: A recent large-scale analysis of Gene Expression Omnibus (GEO) data found frequent evidence for spatial defects in a substantial fraction of Affymetrix microarrays in the GEO. Nevertheless, in contrast to quality assessment, artefact detection is not widely used in standard gene expression analysis pipelines. Furthermore, although approaches have been proposed to detect diverse types of spatial noise on arrays, the correction of these artefacts is mostly left to either summarization methods or the corresponding arrays are completely discarded. RESULTS: We show that state-of-the-art robust summarization procedures are vulnerable to artefacts on arrays and cannot appropriately correct for these. To address this problem, we present a simple approach to detect artefacts with high recall and precision, which we further improve by taking into account the spatial layout of arrays. Finally, we propose two correction methods for these artefacts that either substitute values of defective probes using probeset information or filter corrupted probes. We show that our approach can identify and correct defective probe measurements appropriately and outperforms existing tools. CONCLUSIONS: While summarization is insufficient to correct for defective probes, this problem can be addressed in a straightforward way by the methods we present for identification and correction of defective probes. As these methods output CEL files with corrected probe values that serve as input to standard normalization and summarization procedures, they can be easily integrated into existing microarray analysis pipelines as an additional pre-processing step. An R package is freely available from http://www.bio.ifi.lmu.de/artefact-correction.     

Software and methods for oligonucleotide and cDNA array data analysis

Two HTML-based programs were developed to analyze and filter gene-expression data: 'Bullfrog' for Affymetrix oligonucleotide arrays and 'Spot' for custom cDNA arrays. The programs provide intuitive data-filtering tools through an easy-to-use interface. A background subtraction and normalization program for cDNA arrays was also built that provides an informative summary report with data-quality assessments. These programs are freeware to aid in the analysis of gene-expression results and facilitate the search for genes responsible for interesting biological processes and phenotypes.     

Striptease on glass: validation of an improved stripping procedure for in situ microarrays

Microarrays have rapidly become an indispensable tool for gene analysis. Microarray experiments can be cost prohibitive, however, largely due to the price of the arrays themselves. Whilst different methods for stripping filter arrays on membranes have been established, only very few protocols are published for thermal and chemical stripping of microarrays on glass. Most of these protocols for stripping microarrays on glass were developed in combination with specific surface chemistry and different coatings for covalently immobilizing presynthesized DNA in a deposition process. We have developed a method for stripping commercial in situ microarrays using a multi-step procedure. We present a method that uses mild chemical degradation complemented by enzymatic treatment. We took advantage of the differences in biochemical properties of covalently linked DNA oligonucleotides on in situ synthesized microarrays and the antisense cRNA hybridization probes. The success of stripping protocols for microarrays on glass was critically dependent on the type of arrays, the nature of sample used for hybridization, as well as hybridization and washing conditions. The protocol employs alkali hydrolysis of the cRNA, several enzymatic degradation steps using RNAses and Proteinase K, combined with appropriate washing steps. Stripped arrays were rehybridized using the same protocols as for new microarrays. The stripping method was validated with microarrays from different suppliers and rehybridization of stripped in situ arrays yielded comparable results to hybridizations done on unused, new arrays with no significant loss in precision or accuracy. We show that stripping of commercial in situ arrays is feasible and that reuse of stripped arrays gave similar results compared to unused ones. This was true even for biological samples that show only slight differences in their expression profiles. Our analyses indicate that the stripping procedure does not significantly influence data quality derived from post-primary hybridizations. The method is robust, easy to perform, inexpensive, and results after reuse are of comparable accuracy to new arrays.     

Model-based analysis of oligonucleotide arrays: model validation, design issues and standard error application

Background

A model-based analysis of oligonucleotide expression arrays we developed previously uses a probe-sensitivity index to capture the response characteristic of a specific probe pair and calculates model-based expression indexes (MBEI). MBEI has standard error attached to it as a measure of accuracy. Here we investigate the stability of the probe-sensitivity index across different tissue types, the reproducibility of results in replicate experiments, and the use of MBEI in perfect match (PM)-only arrays.

Results

Probe-sensitivity indexes are stable across tissue types. The target gene's presence in many arrays of an array set allows the probe-sensitivity index to be estimated accurately. We extended the model to obtain expression values for PM-only arrays, and found that the 20-probe PM-only model is comparable to the 10-probe PM/MM difference model, in terms of the expression correlations with the original 20-probe PM/MM difference model. MBEI method is able to extend the reliable detection limit of expression to a lower mRNA concentration. The standard errors of MBEI can be used to construct confidence intervals of fold changes, and the lower confidence bound of fold change is a better ranking statistic for filtering genes. We can assign reliability indexes for genes in a specific cluster of interest in hierarchical clustering by resampling clustering trees. A software dChip implementing many of these analysis methods is made available.

Conclusions

The model-based approach reduces the variability of low expression estimates, and provides a natural method of calculating expression values for PM-only arrays. The standard errors attached to expression values can be used to assess the reliability of downstream analysis.     

Chemiluminescent detection of sequential DNA hybridizations to high-density, filter-arrayed cDNA libraries: a subtraction method for novel gene discovery.

A chemiluminescent approach for sequential DNA hybridizations to high-density filter arrays of cDNAs, using a biotin-based random priming method followed by a streptavidin/alkaline phosphatase/CDP-Star detection protocol, is presented. The method has been applied to the Brugia malayi genome project, wherein cDNA libraries, cosmid and bacterial artificial chromosome (BAC) libraries have been gridded at high density onto nylon filters for subsequent analysis by hybridization. Individual probes and pools of rRNA probes, ribosomal protein probes and expressed sequence tag probes show correct specificity and high signal-to-noise ratios even after ten rounds of hybridization, detection, stripping of the probes from the membranes and rehybridization with additional probe sets. This approach provides a subtraction method that leads to a reduction in redundant DNA sequencing, thus increasing the rate of novel gene discovery. The method is also applicable for detecting target sequences, which are present in one or only a few copies per cell; it has proven useful for physical mapping of BAC and cosmid high-density filter arrays, wherein multiple probes have been hybridized at one time (multiplexed) and subsequently "deplexed" into individual components for specific probe localizations.     

MOF： An R Function to Detect Outlier Microarray

We developed an R function named ＂microarray outlier filter＂ （MOF） to assist in the identification of faUed arrays. In sorting a group of similar arrays by the likelihood of failure, two statistical indices were employed： the correlation coefficient and the percentage of outlier spots. MOF can be used to monitor the quality of microarray data for both trouble shooting, and to eliminate bad datasets from downstream analysis. The function is freely avaliable at http：//www.wriwindber.org/ applications/mof/.     

Optimization and application of median filter corrections to relieve diverse spatial patterns in microtiter plate data

The standard (STD) 5 × 5 hybrid median filter (HMF) was previously described as a nonparametric local backestimator of spatially arrayed microtiter plate (MTP) data. As such, the HMF is a useful tool for mitigating global and sporadic systematic error in MTP data arrays. Presented here is the first known HMF correction of a primary screen suffering from systematic error best described as gradient vectors. Application of the STD 5 × 5 HMF to the primary screen raw data reduced background signal deviation, thereby improving the assay dynamic range and hit confirmation rate. While this HMF can correct gradient vectors, it does not properly correct periodic patterns that may present in other screening campaigns. To address this issue, 1 × 7 median and a row/column 5 × 5 hybrid median filter kernels (1 × 7 MF and RC 5 × 5 HMF) were designed ad hoc, to better fit periodic error patterns. The correction data show periodic error in simulated MTP data arrays is reduced by these alternative filter designs and that multiple corrective filters can be combined in serial operations for progressive reduction of complex error patterns in a MTP data array.     

Median filter algorithm for estimating the threshold of detection on custom protein arrays

We constructed protein arrays according to a titration design to estimate the assay sensitivities over varying concentrations of flu vaccine and human immunoglobulin G (IgG). After imaging, we considered the problem of appropriately distinguishing background noise from foreground signal. We applied the median filter smoothing technique and estimated the differences of the observed signal compared to the smoothed signal. If the absolute value of the difference was large, the feature was easily detectable, indicating that the spot did not blend with its surrounding neighbors. After estimating the residuals, we applied thresholding algorithms to estimate the limits of detection for each assay. At sufficiently large smoothing spans, our median filter approach performed as well or better than visual inspection and two other competing analysis methods. This suggests that a median filter approach has utility in high-throughput arrays where visual inspection is impractical.     

Split-Plot Microarray Experiments

This article focuses on microarray experiments with two or more factors in which treatment combinations of the factors corresponding to the samples paired together onto arrays are not completely random. A main effect of one (or more) factor(s) is confounded with arrays (the experimental blocks). This is called a split-plot microarray experiment. We utilise an analysis of variance (ANOVA) model to assess differentially expressed genes for between-array and within-array comparisons that are generic under a split-plot microarray experiment. Instead of standard t- or F-test statistics that rely on mean square errors of the ANOVA model, we use a robust method, referred to as 'a pooled percentile estimator', to identify genes that are differentially expressed across different treatment conditions. We illustrate the design and analysis of split-plot microarray experiments based on a case application described by Jin et al. A brief discussion of power and sample size for split-plot microarray experiments is also presented.     

Between-group analysis of microarray data

MOTIVATION: Most supervised classification methods are limited by the requirement for more cases than variables. In microarray data the number of variables (genes) far exceeds the number of cases (arrays), and thus filtering and pre-selection of genes is required. We describe the application of Between Group Analysis (BGA) to the analysis of microarray data. A feature of BGA is that it can be used when the number of variables (genes) exceeds the number of cases (arrays). BGA is based on carrying out an ordination of groups of samples, using a standard method such as Correspondence Analysis (COA), rather than an ordination of the individual microarray samples. As such, it can be viewed as a method of carrying out COA with grouped data. RESULTS: We illustrate the power of the method using two cancer data sets. In both cases, we can quickly and accurately classify test samples from any number of specified a priori groups and identify the genes which characterize these groups. We obtained very high rates of correct classification, as determined by jack-knife or validation experiments with training and test sets. The results are comparable to those from other methods in terms of accuracy but the power and flexibility of BGA make it an especially attractive method for the analysis of microarray cancer data.     

A filter assay for binding of labeled ligands to membrane-bound receptors

A filter assay was developed for the specific binding of labeled ligands to the acetylcholine receptor in an unpurified suspension of membrane fragments from Torpedo californica. Binding to the filter membrane and the standard deviation of replicates were studied, and it was possible to reduce relative standard deviation to about 3% by accounting for the variable weight of the particles dispensed, stopping the loss of particles to the filter apparatus, regulating the transmembrane pressure during filtration, controlling the time the filter remains subject to suction after all the liquid has passed through the filter, and correcting for variable counting efficiency. A method for dispensing equal aliquots of suspended particulates is also described.     

The linear electrode array: a useful tool with many applications.

In this review we describe the basic principles of operation of linear electrode arrays for the detection of surface EMG signals, together with their most relevant current applications. A linear array of electrodes is a system which detects surface EMG signals in a number of points located along a line. A spatial filter is usually placed in each point for signal detection, so that the recording of EMG signals with linear arrays corresponds to the sampling in one spatial direction of a spatially filtered version of the potential distribution over the skin. Linear arrays provide indications on motor unit (MU) anatomical properties, such as the locations of the innervation zones and tendons, and the fiber length. Such systems allow the investigation of the properties of the volume conductor and its effect on surface detected signals. Moreover, linear arrays allow to estimate muscle fiber conduction velocity with a very low standard deviation of estimation (of the order of 0.1-0.2 m/s), thus providing reliable indications on muscle fiber membrane properties and their changes in time (for example with fatigue or during treatment). Conduction velocity can be estimated from a signal epoch (global estimate) or at the single MU level. In the latter case, MU action potentials are identified from the interference EMG signals and conduction velocity is estimated for each detected potential. In this way it is possible, in certain conditions, to investigate single MU control and conduction properties with a completely non-invasive approach. Linear arrays provide valuable information on the neuromuscular system properties and appear to be promising tools for applied studies and clinical research.     

The Design of Simple Bacterial Microarrays: Development towards Immobilizing Single Living Bacteria on Predefined Micro-Sized Spots on Patterned Surfaces

In this paper we demonstrate a procedure for preparing bacterial arrays that is fast, easy, and applicable in a standard molecular biology laboratory. Microcontact printing is used to deposit chemicals promoting bacterial adherence in predefined positions on glass surfaces coated with polymers known for their resistance to bacterial adhesion. Highly ordered arrays of immobilized bacteria were obtained using microcontact printed islands of polydopamine (PD) on glass surfaces coated with the antiadhesive polymer polyethylene glycol (PEG). On such PEG-coated glass surfaces, bacteria were attached to 97 to 100% of the PD islands, 21 to 62% of which were occupied by a single bacterium. A viability test revealed that 99% of the bacteria were alive following immobilization onto patterned surfaces. Time series imaging of bacteria on such arrays revealed that the attached bacteria both divided and expressed green fluorescent protein, both of which indicates that this method of patterning of bacteria is a suitable method for single-cell analysis.     

Surface-induced lamellar orientation of multilayer membrane arrays. Theoretical analysis and a new method with application to purple membrane fragments.

The orientation of membrane fragments into a lamellar array by a flat surface is analyzed. This analysis includes processes such as centrifugation and drying and physical effects due to membrane fragment steric interactions, finite size, elasticity, and thermal fluctuations. Several model calculations of optimal orientational order in multilayer membrane arrays are presented. The predictions of a smectic A model agree quantitatively with the measured spatial dependence of the fluctuations in layer orientation in a multilamellar arrays. A new technique, based in part on this analysis, for the preparation of well-oriented multilamellar arrays of natural and artificial membranes, isopotential spin-dry centrifugation, is described. The method involves the use of specially designed inserts for the buckets of a standard vacuum ultracentrifuge. The membrane fragments to be oriented are sedimented from solution or suspension onto a substrate of a convenient material which forms a gravitational isopotential surface at high g. Sedimentation is accompanied by removal of the suspending medium at high g to produce oriented films with a selected degree of solvation. In addition, a method is described whereby small solute molecules can be maintained in constant concentration with the membrane fragments during this process. Initial application of the method to the orientation of purple membrane fragments is described. The degree of orientation obtained in this system is evaluated using freeze-fracture and scanning electron microscopy, optical birefringence, linear dichroism, and microscopy.     

Partition resampling and extrapolation averaging: approximation methods for quantifying gene expression in large numbers of short oligonucleotide arrays

MOTIVATION: Studies of gene expression using high-density short oligonucleotide arrays have become a standard in a variety of biological contexts. Of the expression measures that have been proposed to quantify expression in these arrays, multi-chip-based measures have been shown to perform well. As gene expression studies increase in size, however, utilizing multi-chip expression measures is more challenging in terms of computing memory requirements and time. RESULTS: A strategic alternative to exact multi-chip quantification on a full large chip set is to approximate expression values based on subsets of chips. This paper introduces an extrapolation method, Extrapolation Averaging (EA), and a resampling method, Partition Resampling (PR), to approximate expression in large studies. An examination of properties indicates that subset-based methods can perform well compared with exact expression quantification. The focus is on short oligonucleotide chips, but the same ideas apply equally well to any array type for which expression is quantified using an entire set of arrays, rather than for only a single array at a time. AVAILABILITY: Software implementing Partition Resampling and Extrapolation Averaging is under development as an R package for the BioConductor project.     

Correction for inner filter effects in turbid samples: fluorescence assays of mitochondrial NADH

Fluorescentdeterminations of NADH in porcine heart mitochondria were subject tosignificant errors caused by alterations in inner filter effects duringnumerous metabolic perturbations. These inner filter effects wereprimarily associated with changes in mitochondrial volume andaccompanying light scattering. The observed effects were detected in astandard commercial fluorometer with emission orthogonal to theexcitation light path and, to a lesser extent, in a light path geometrydetecting only the surface fluorescence. A method was developed todetect and correct for inner filter effects on mitochondrial NADHfluorescence measurements that were independent of the optical pathgeometry using an internal fluorescent standard and linearleast-squares spectral analysis. A simple linear correction with theinner fluorescence reference was found to adequately correct for innerfilter effects. This approach may be useful for other fluorescenceprobes in isolated mitochondria or other light-scattering media.

     

A field-adapted HPLC method for determination of amodiaquine and its metabolite in whole blood dried on filter paper

A reversed-phase high performance liquid chromatographic method was developed and validated for the quantitative determination of amodiaquine (AQ) and its metabolite desethylamodiaquine (DAQ) in whole blood collected on filter paper. The structure analogue 4-(4-dimethylamino-1-methylbutylamino)-7-chloroquinoline was used as internal standard. Upon collection, blood was added to 10% phosphoric acid in a 1:1 ratio and then spotted onto filter paper. The samples were alkalinized (pH approximately 9.2) with potassium hydroxide at the time of assay and the compounds were extracted together with internal standard into di-isopropyl ether and then re-extracted into an aqueous phase with 0.1M phosphate buffer at pH 4. The chromatographic analysis was performed using an Agilent Technologies ChemStation LC System. The absorbance of the compounds was monitored at 333 nm. Mean extraction recoveries of AQ and DAQ were 49 and 48%, respectively. Intra-day and inter-day coefficients of variation were <10.5%. The limit of quantification was 50 nM for both compounds (sample size 100 microl). Both AQ and DAQ that were previously reported to be unstable have been stored on filter paper for at least 19 weeks. The method was applied on samples from healthy volunteers.