Was the Scanner Calibration Slide used for its intended purpose?

In the article, Scanner calibration revisited, BMC Bioinformatics 2010, 11:361, Dr. Pozhitkov used the Scanner Calibration Slide, a key product of Full Moon BioSystems to generate data in his study of microarray scanner PMT response and proposed a mathematic model for PMT response [1]. In the end, the author concluded that "Full Moon BioSystems calibration slides are inadequate for performing calibration," and recommended "against using these slides." We found these conclusions are seriously flawed and misleading, and his recommendation against using the Scanner Calibration Slide was not properly supported.     

A response to information criterion-based clustering with order-restricted candidate profiles in short time-course microarray experiments

Background  

For gene expression data obtained from a time-course microarray experiment, Liu et al. [1] developed a new algorithm for clustering genes with similar expression profiles over time. Performance of their proposal was compared with three other methods including the order-restricted inference based methodology of Peddada et al. [2, 3]. In this note we point out several inaccuracies in Liu et al. [1] and conclude that the order-restricted inference based methodology of Peddada et al. (programmed in the software ORIOGEN) indeed operates at the desired nominal Type 1 error level, an important feature of a statistical decision rule, while being computationally substantially faster than indicated by Liu et al. [1].     

Feature selection and classification for microarray data analysis: Evolutionary methods for identifying predictive genes

Background  

In the clinical context, samples assayed by microarray are often classified by cell line or tumour type and it is of interest to discover a set of genes that can be used as class predictors. The leukemia dataset of Golubet al.[1] and the NCI60 dataset of Rosset al.[2] present multiclass classification problems where three tumour types and nine cell lines respectively must be identified. We apply an evolutionary algorithm to identify the near-optimal set of predictive genes that classify the data. We also examine the initial gene selection step whereby the most informative genes are selected from the genes assayed.     

Video analysis of the escape flight of Pileated Woodpecker Dryocopus pileatus: does the Ivory-billed Woodpecker Campephilus principalis persist in continental North America?

Background  

The apparent rediscovery of the Ivory-billed Woodpecker Campephilus principalis in Arkansas, USA, previously feared extinct, was supported by video evidence of a single bird in flight (Fitzpatrick et al, Science 2005, 308:1460–1462). Plumage patterns and wingbeat frequency of the putative Ivory-billed Woodpecker were said to be incompatible with the only possible confusion species native to the area, the Pileated Woodpecker Dryocopus pileatus.     

Correlation and prediction of gene expression level from amino acid and dipeptide composition of its protein

Background  

A large number of papers have been published on analysis of microarray data with particular emphasis on normalization of data, detection of differentially expressed genes, clustering of genes and regulatory network. On other hand there are only few studies on relation between expression level and composition of nucleotide/protein sequence, using expression data. There is a need to understand why particular genes/proteins express more in particular conditions. In this study, we analyze 3468 genes of Saccharomyces cerevisiae obtained from Holstege et al., (1998) to understand the relationship between expression level and amino acid composition.     

High quality protein microarray using in situ protein purification

Background  

In the postgenomic era, high throughput protein expression and protein microarray technologies have progressed markedly permitting screening of therapeutic reagents and discovery of novel protein functions. Hexa-histidine is one of the most commonly used fusion tags for protein expression due to its small size and convenient purification via immobilized metal ion affinity chromatography (IMAC). This purification process has been adapted to the protein microarray format, but the quality of in situ His-tagged protein purification on slides has not been systematically evaluated. We established methods to determine the level of purification of such proteins on metal chelate-modified slide surfaces. Optimized in situ purification of His-tagged recombinant proteins has the potential to become the new gold standard for cost-effective generation of high-quality and high-density protein microarrays.     

Envelope structure of Synechococcus sp. WH8113, a nonflagellated swimming cyanobacterium

Background  

Many bacteria swim by rotating helical flagellar filaments [1]. Waterbury et al. [15] discovered an exception, strains of the cyanobacterium Synechococcus that swim without flagella or visible changes in shape. Other species of cyanobacteria glide on surfaces [2,7]. The hypothesis that Synechococcus might swim using traveling surface waves [6,13] prompted this investigation.     

Long branch attraction,taxon sampling,and the earliest angiosperms: <Emphasis Type="Italic">Amborella</Emphasis> or monocots?

Background  

Numerous studies, using in aggregate some 28 genes, have achieved a consensus in recognizing three groups of plants, including Amborella, as comprising the basal-most grade of all other angiosperms. A major exception is the recent study by Goremykin et al. (2003; Mol. Biol. Evol. 20:1499–1505), whose analyses of 61 genes from 13 sequenced chloroplast genomes of land plants nearly always found 100% support for monocots as the deepest angiosperms relative to Amborella, Calycanthus, and eudicots. We hypothesized that this conflict reflects a misrooting of angiosperms resulting from inadequate taxon sampling, inappropriate phylogenetic methodology, and rapid evolution in the grass lineage used to represent monocots.     

Washing scaling of GeneChip microarray expression

Background  

Post-hybridization washing is an essential part of microarray experiments. Both the quality of the experimental washing protocol and adequate consideration of washing in intensity calibration ultimately affect the quality of the expression estimates extracted from the microarray intensities.     

Library on a slide for bacterial comparative genomics

Background  

We describe a novel application of microarray technology for comparative genomics of bacteria in which libraries of entire genomes rather than the sequence of a single genome or sets of genes are arrayed on the slide and then probed for the presence or absence of specific genes and/or gene alleles.     

Microarray scanner calibration curves: characteristics and implications

Background

Microarray-based measurement of mRNA abundance assumes a linear relationship between the fluorescence intensity and the dye concentration. In reality, however, the calibration curve can be nonlinear.

Results

By scanning a microarray scanner calibration slide containing known concentrations of fluorescent dyes under 18 PMT gains, we were able to evaluate the differences in calibration characteristics of Cy5 and Cy3. First, the calibration curve for the same dye under the same PMT gain is nonlinear at both the high and low intensity ends. Second, the degree of nonlinearity of the calibration curve depends on the PMT gain. Third, the two PMTs (for Cy5 and Cy3) behave differently even under the same gain. Fourth, the background intensity for the Cy3 channel is higher than that for the Cy5 channel. The impact of such characteristics on the accuracy and reproducibility of measured mRNA abundance and the calculated ratios was demonstrated. Combined with simulation results, we provided explanations to the existence of ratio underestimation, intensity-dependence of ratio bias, and anti-correlation of ratios in dye-swap replicates. We further demonstrated that although Lowess normalization effectively eliminates the intensity-dependence of ratio bias, the systematic deviation from true ratios largely remained. A method of calculating ratios based on concentrations estimated from the calibration curves was proposed for correcting ratio bias.

Conclusion

It is preferable to scan microarray slides at fixed, optimal gain settings under which the linearity between concentration and intensity is maximized. Although normalization methods improve reproducibility of microarray measurements, they appear less effective in improving accuracy.

     

Cancer models,genomic instability and somatic cellular Darwinian evolution

   

The biology of cancer is critically reviewed and evidence adduced that its development can be modelled as a somatic cellular Darwinian evolutionary process. The evidence for involvement of genomic instability (GI) is also reviewed. A variety of quasi-mechanistic models of carcinogenesis are reviewed, all based on this somatic Darwinian evolutionary hypothesis; in particular, the multi-stage model of Armitage and Doll (Br. J. Cancer 1954:8;1-12), the two-mutation model of Moolgavkar, Venzon, and Knudson (MVK) (Math. Biosci. 1979:47;55-77), the generalized MVK model of Little (Biometrics 1995:51;1278-1291) and various generalizations of these incorporating effects of GI (Little and Wright Math. Biosci. 2003:183;111-134; Little et al. J. Theoret. Biol. 2008:254;229-238).     

The joint evolutionary histories of Wolbachia and mitochondria in Hypolimnas bolina

Background  

The interaction between the Blue Moon butterfly, Hypolimnas bolina, and Wolbachia has attracted interest because of the high prevalence of male-killing achieved within the species, the ecological consequences of this high prevalence, the intensity of selection on the host to suppress the infection, and the presence of multiple Wolbachia infections inducing different phenotypes. We examined diversity in the co-inherited marker, mtDNA, and the partitioning of this between individuals of different infection status, as a means to investigate the population biology and evolutionary history of the Wolbachia infections.     

Predicting functional sites with an automated algorithm suitable for heterogeneous datasets

Background  

In a previous report (La et al., Proteins, 2005), we have demonstrated that the identification of phylogenetic motifs, protein sequence fragments conserving the overall familial phylogeny, represent a promising approach for sequence/function annotation. Across a structurally and functionally heterogeneous dataset, phylogenetic motifs have been demonstrated to correspond to a wide variety of functional site archetypes, including those defined by surface loops, active site clefts, and less exposed regions. However, in our original demonstration of the technique, phylogenetic motif identification is dependent upon a manually determined similarity threshold, prohibiting large-scale application of the technique.     

Information criterion-based clustering with order-restricted candidate profiles in short time-course microarray experiments

Background  

Time-course microarray experiments produce vector gene expression profiles across a series of time points. Clustering genes based on these profiles is important in discovering functional related and co-regulated genes. Early developed clustering algorithms do not take advantage of the ordering in a time-course study, explicit use of which should allow more sensitive detection of genes that display a consistent pattern over time. Peddada et al. [1] proposed a clustering algorithm that can incorporate the temporal ordering using order-restricted statistical inference. This algorithm is, however, very time-consuming and hence inapplicable to most microarray experiments that contain a large number of genes. Its computational burden also imposes difficulty to assess the clustering reliability, which is a very important measure when clustering noisy microarray data.     

sdef: an R package to synthesize lists of significant features in related experiments

Background  

In microarray studies researchers are often interested in the comparison of relevant quantities between two or more similar experiments, involving different treatments, tissues, or species. Typically each experiment reports measures of significance (e.g. p-values) or other measures that rank its features (e.g genes). Our objective is to find a list of features that are significant in all experiments, to be further investigated. In this paper we present an R package called sdef, that allows the user to quantify the evidence of communality between the experiments using previously proposed statistical methods based on the ranked lists of p-values. sdef implements two approaches that address this objective: the first is a permutation test of the maximal ratio of observed to expected common features under the hypothesis of independence between the experiments. The second approach, set in a Bayesian framework, is more flexible as it takes into account the uncertainty on the number of genes differentially expressed in each experiment.     

Detecting differential expression in microarray data: comparison of optimal procedures

Background  

Many procedures for finding differentially expressed genes in microarray data are based on classical or modified t-statistics. Due to multiple testing considerations, the false discovery rate (FDR) is the key tool for assessing the significance of these test statistics. Two recent papers have generalized two aspects: Storey et al. (2005) have introduced a likelihood ratio test statistic for two-sample situations that has desirable theoretical properties (optimal discovery procedure, ODP), but uses standard FDR assessment; Ploner et al. (2006) have introduced a multivariate local FDR that allows incorporation of standard error information, but uses the standard t-statistic (fdr2d). The relationship and relative performance of these methods in two-sample comparisons is currently unknown.     

Development and evaluation of an off‐the‐slide genotyping technique for identifying Giardia cysts and Cryptosporidium oocysts directly from US EPA Method 1623 slides

Aims

This study developed and systematically evaluated performance and limit of detection of an off‐the‐slide genotyping procedure for both Cryptosporidium oocysts and Giardia cysts.

Methods and Results

Slide standards containing flow‐sorted (oo)cysts were used to evaluate the off‐the‐slide genotyping procedure by microscopy and PCR. Results show approximately 20% of cysts and oocysts are lost during staining. Although transfer efficiency from the slide to the PCR tube could not be determined by microscopy, it was observed that the transfer process aided in the physical lysis of the (oo)cysts likely releasing DNA. PCR detection rates for a single event on a slide were 44% for Giardia and 27% for Cryptosporidium, and a minimum of five cysts and 20 oocysts are required to achieve a 90% PCR detection rate. A Poisson distribution analysis estimated the relative PCR target densities and limits of detection, it showed that 18 Cryptosporidium and five Giardia replicates are required for a 95% probability of detecting a single (oo)cyst on a slide.

Conclusions

This study successfully developed and evaluated recovery rates and limits of detection of an off‐the‐slide genotyping procedure for both Cryptosporidium and Giardia (oo)cysts from the same slide.

Significance and Impact of the Study

This off‐the‐slide genotyping technique is a simple and low cost tool that expands the applications of US EPA Method 1623 results by identifying the genotypes and assemblages of the enumerated Cryptosporidium and Giardia. This additional information will be useful for microbial risk assessment models and watershed management decisions.