Quality assessment of microarrays: Visualization of spatial artifacts and quantitation of regional biases

BACKGROUND: Quality-control is an important issue in the analysis of gene expression microarrays. One type of problem is regional bias, in which one region of a chip shows artifactually high or low intensities (or ratios in a two-channel array) relative to the majority of the chip. Current practice in quality assessment for microarrays does not address regional biases. RESULTS: We present methods implemented in R for visualizing regional biases and other spatial artifacts on spotted microarrays and Affymetrix chips. We also propose a statistical index to quantify regional bias and investigate its typical distribution on spotted and Affymetrix arrays. We demonstrate that notable regional biases occur on both Affymetrix and spotted arrays and that they can make a significant difference in the case of spotted microarray results. Although strong biases are also seen at the level of individual probes on Affymetrix chips, the gene expression measures are less affected, especially when the RMA method is used to summarize intensities for the probe sets. A web application program for visualization and quantitation of regional bias is provided at . CONCLUSION: Researchers should visualize and measure the regional biases and should estimate their impact on gene expression measurements obtained. Here, we (i) introduce pictorial visualizations of the spatial biases; (ii) present for Affymetrix chips a useful resolution of the biases into two components, one related to background, the other to intensity scale factor; (iii) introduce a single parameter to reflect the global bias present across an array. We also examine the pattern distribution of such biases and conclude that algorithms based on smoothing are unlikely to compensate adequately for them

The LeFE Algorithm: Embracing the Complexity of Gene Expression in the Interpretation of Microarray Data

The LeFE algorithm has been developed to address the complex, non-linear regulation of gene expression. Interpretation of microarray data remains a challenge, and most methods fail to consider the complex, nonlinear regulation of gene expression. To address that limitation, we introduce Learner of Functional Enrichment (LeFE), a statistical/machine learning algorithm based on Random Forest, and demonstrate it on several diverse datasets: smoker/never smoker, breast cancer classification, and cancer drug sensitivity. We also compare it with previously published algorithms, including Gene Set Enrichment Analysis. LeFE regularly identifies statistically significant functional themes consistent with known biology.National Cancer Institute's Center for Cancer Researc

Developing Dental Faculty for the Future: ADEA/AAL Institute for Teaching and Learning, 2006–09

This report summarizes the history and curriculum of the American Dental Education Association/Academy for Academic Leadership Institute for Teaching and Learning (ADEA/AAL ITL) Program for Dental School Faculty, describes participant feedback, and reviews how the program serves the faculty development initiatives of the American Dental Education Association. The fifty-hour program (6.5 days), conducted in two phases at collaborating dental schools, enhances core academic competencies of new and transitional faculty, including faculty members whose responsibilities include predoctoral, allied, and postdoctoral dental education. The program's mission is to prepare participants to become more effective teachers and develop other skills that will facilitate confidence, job satisfaction, and professional growth in the academic environment. From 2005 to 2009, 174 individuals graduated from the program, representing forty-three schools of dentistry in the United States and Canada and twenty-nine private practices. A total of forty scholarships have been awarded to participants by the American Academy of Periodontology Foundation, the American Academy of Pediatric Dentistry, and the American Association of Orthodontists. In an online survey completed by 75 percent of ADEA/AAL ITL participants, 99 percent indicated they were positive or highly positive about their learning experience in this faculty development program. Ninety-six percent stated that the program had been important or very important in their effectiveness as a teacher. In 2010, the program will be held at the University of North Carolina at Chapel Hill School of Dentistry, with phase I occurring on August 19-22, 2010, and phase II on October 22-24, 2010. In summary, the ADEA/AAL ITL is addressing an unmet need through a formal professional development program designed to help new and potential faculty members thrive as educators and become future leaders in academic health care

Molecular vibration in cold collision theory

Cold collisions of ground state oxygen molecules with Helium have been investigated in a wide range of cold collision energies (from 1 $\mu$K up to 10 K) treating the oxygen molecule first as a rigid rotor and then introducing the vibrational degree of freedom. The comparison between the two models shows that at low energies the rigid rotor approximation is very accurate and able to describe all the dynamical features of the system. The comparison between the two models has also been extended to cases where the interaction potential He - O$_2$ is made artificially stronger. In this case vibration can perturb rate constants, but fine-tuning the rigid rotor potential can alleviate the discrepancies between the two models.Comment: 11 pages, 3 figure

SpliceMiner: a high-throughput database implementation of the NCBI Evidence Viewer for microarray splice variant analysis

BACKGROUND: There are many fewer genes in the human genome than there are expressed transcripts. Alternative splicing is the reason. Alternatively spliced transcripts are often specific to tissue type, developmental stage, environmental condition, or disease state. Accurate analysis of microarray expression data and design of new arrays for alternative splicing require assessment of probes at the sequence and exon levels. DESCRIPTION: SpliceMiner is a web interface for querying Evidence Viewer Database (EVDB). EVDB is a comprehensive, non-redundant compendium of splice variant data for human genes. We constructed EVDB as a queryable implementation of the NCBI Evidence Viewer (EV). EVDB is based on data obtained from NCBI Entrez Gene and EV. The automated EVDB build process uses only complete coding sequences, which may or may not include partial or complete 5' and 3' UTRs, and filters redundant splice variants. Unlike EV, which supports only one-at-a-time queries, SpliceMiner supports high-throughput batch queries and provides results in an easily parsable format. SpliceMiner maps probes to splice variants, effectively delineating the variants identified by a probe. CONCLUSION: EVDB can be queried by gene symbol, genomic coordinates, or probe sequence via a user-friendly web-based tool we call SpliceMiner (). The EVDB/SpliceMiner combination provides an interface with human splice variant information and, going beyond the very valuable NCBI Evidence Viewer, supports fluent, high-throughput analysis. Integration of EVDB information into microarray analysis and design pipelines has the potential to improve the analysis and bioinformatic interpretation of gene expression data, for both batch and interactive processing. For example, whenever a gene expression value is recognized as important or appears anomalous in a microarray experiment, the interactive mode of SpliceMiner can be used quickly and easily to check for possible splice variant issues

SpliceCenter: A suite of web-based bioinformatic applications for evaluating the impact of alternative splicing on RT-PCR, RNAi, microarray, and peptide-based studies

<p>Abstract</p> <p>Background</p> <p>Over 60% of protein-coding genes in vertebrates express mRNAs that undergo alternative splicing. The resulting collection of transcript isoforms poses significant challenges for contemporary biological assays. For example, RT-PCR validation of gene expression microarray results may be unsuccessful if the two technologies target different splice variants. Effective use of sequence-based technologies requires knowledge of the specific splice variant(s) that are targeted. In addition, the critical roles of alternative splice forms in biological function and in disease suggest that assay results may be more informative if analyzed in the context of the targeted splice variant.</p> <p>Results</p> <p>A number of contemporary technologies are used for analyzing transcripts or proteins. To enable investigation of the impact of splice variation on the interpretation of data derived from those technologies, we have developed SpliceCenter. SpliceCenter is a suite of user-friendly, web-based applications that includes programs for analysis of RT-PCR primer/probe sets, effectors of RNAi, microarrays, and protein-targeting technologies. Both interactive and high-throughput implementations of the tools are provided. The interactive versions of SpliceCenter tools provide visualizations of a gene's alternative transcripts and probe target positions, enabling the user to identify which splice variants are or are not targeted. The high-throughput batch versions accept user query files and provide results in tabular form. When, for example, we used SpliceCenter's batch siRNA-Check to process the Cancer Genome Anatomy Project's large-scale shRNA library, we found that only 59% of the 50,766 shRNAs in the library target all known splice variants of the target gene, 32% target some but not all, and 9% do not target any currently annotated transcript.</p> <p>Conclusion</p> <p>SpliceCenter <url>http://discover.nci.nih.gov/splicecenter</url> provides unique, user-friendly applications for assessing the impact of transcript variation on the design and interpretation of RT-PCR, RNAi, gene expression microarrays, antibody-based detection, and mass spectrometry proteomics. The tools are intended for use by bench biologists as well as bioinformaticists.</p

CellMiner: a relational database and query tool for the NCI-60 cancer cell lines

<p>Abstract</p> <p>Background</p> <p>Advances in the high-throughput omic technologies have made it possible to profile cells in a large number of ways at the DNA, RNA, protein, chromosomal, functional, and pharmacological levels. A persistent problem is that some classes of molecular data are labeled with gene identifiers, others with transcript or protein identifiers, and still others with chromosomal locations. What has lagged behind is the ability to integrate the resulting data to uncover complex relationships and patterns. Those issues are reflected in full form by molecular profile data on the panel of 60 diverse human cancer cell lines (the NCI-60) used since 1990 by the U.S. National Cancer Institute to screen compounds for anticancer activity. To our knowledge, CellMiner is the first online database resource for integration of the diverse molecular types of NCI-60 and related meta data.</p> <p>Description</p> <p>CellMiner enables scientists to perform advanced querying of molecular information on NCI-60 (and additional types) through a single web interface. CellMiner is a freely available tool that organizes and stores raw and normalized data that represent multiple types of molecular characterizations at the DNA, RNA, protein, and pharmacological levels. Annotations for each project, along with associated metadata on the samples and datasets, are stored in a MySQL database and linked to the molecular profile data. Data can be queried and downloaded along with comprehensive information on experimental and analytic methods for each data set. A Data Intersection tool allows selection of a list of genes (proteins) in common between two or more data sets and outputs the data for those genes (proteins) in the respective sets. In addition to its role as an integrative resource for the NCI-60, the CellMiner package also serves as a shell for incorporation of molecular profile data on other cell or tissue sample types.</p> <p>Conclusion</p> <p>CellMiner is a relational database tool for storing, querying, integrating, and downloading molecular profile data on the NCI-60 and other cancer cell types. More broadly, it provides a template to use in providing such functionality for other molecular profile data generated by academic institutions, public projects, or the private sector. CellMiner is available online at <url>http://discover.nci.nih.gov/cellminer/</url>.</p

Graphene under hydrostatic pressure

In-situ high pressure Raman spectroscopy is used to study monolayer, bilayer and few-layer graphene samples supported on silicon in a diamond anvil cell to 3.5 GPa. The results show that monolayer graphene adheres to the silicon substrate under compressive stress. A clear trend in this behaviour as a function of graphene sample thickness is observed. We also study unsupported graphene samples in a diamond anvil cell to 8 GPa, and show that the properties of graphene under compression are intrinsically similar to graphite. Our results demonstrate the differing effects of uniaxial and biaxial strain on the electronic bandstructure.Comment: Accepted in Physical Review B with minor change