@article{Carreer2013, abstract = {New metabolomics applications of ultra-high resolution and accuracy mass spectrometry can provide thousands of detectable isotopologues, with the number of potentially detectable isotopologues increasing exponentially with the number of stable isotopes used in newer isotope tracing methods like stable isotope-resolved metabolomics (SIRM) experiments. This huge increase in usable data requires software capable of correcting the large number of isotopologue peaks resulting from SIRM experiments in a timely manner. We describe the design of a new algorithm and software system capable of handling these high volumes of data, while including quality control methods for maintaining data quality. We validate this new algorithm against a previous single isotope correction algorithm in a two-step cross-validation. Next, we demonstrate the algorithm and correct for the effects of natural abundance for both (13)C and (15)N isotopes on a set of raw isotopologue intensities of UDP-N-acetyl-D-glucosamine derived from a (13)C/(15)N-tracing experiment. Finally, we demonstrate the algorithm on a full omics-level dataset.}, author = {Carreer, William J. and Flight, Robert M. and Moseley, Hunter N. B.}, doi = {10.3390/metabo3040853}, journal = {Metabolites}, month = {sep}, pages = {853-866}, title = {A Computational Framework for High-Throughput Isotopic Natural Abundance Correction of Omics-Level Ultra-High Resolution FT-MS Datasets}, url = {http://dx.doi.org/10.3390/metabo3040853}, volume = {3}, year = {2013} } @article{Douglas2008, author = {Douglas, S. E. and Knickle, L. C. and Williams, J. and Flight, R. M. and Reith, M. E.}, doi = {10.1111/j.1095-8649.2008.01861.x}, journal = {Journal of Fish Biology}, month = {jun}, pages = {2391-2406}, title = {A first generation Atlantic halibut Hippoglossus hippoglossus (L.) microarray: application to developmental studies}, url = {https://oadoi.org/10.1111/j.1095-8649.2008.01861.x}, volume = {72}, year = {2008} } @article{Ec2010, author = {Ec, Rouchka and Rouchka, Eric C. and Flight, Robert M. and Rm, Flight and Rinehart, Claire}, doi = {10.1186/1471-2105-11-s4-i1}, journal = {BMC Bioinformatics}, month = {jan}, title = {Proceedings of the ninth annual UT-ORNL-KBRIN Bioinformatics Summit 2010.}, url = {http://dx.doi.org/10.1186/1471-2105-11-s4-i1}, volume = {11}, year = {2010} } @inproceedings{Eteleeb2007, author = {Eteleeb, Abdallah M. and Flight, Robert M. and Harrison, Benjamin J. and Petruska, Jeffrey C. and Rouchka, Eric C.}, doi = {10.1145/2506583.2506589}, journal = {Proceedings of the International Conference on Bioinformatics, Computational Biology and Biomedical Informatics - BCB'13}, month = {jan}, title = {An Island-Based Approach for Differential Expression Analysis}, url = {https://www.researchgate.net/profile/Eric_Rouchka/publication/258763372_An_Island-Based_Approach_for_Differential_Expression_Analysis/links/00b7d539af393a8d36000000.pdf}, year = {2007} } @article{Flight2008, abstract = {The increased need for multiple statistical comparisons under conditions of non-independence in bioinformatics applications, such as DNA microarray data analysis, has led to the development of alternatives to the conventional Bonferroni correction for adjusting P-values. The use of the false discovery rate (FDR), in particular, has grown considerably. However, the calculation of the FDR frequently depends on drawing random samples from a population, and inappropriate sampling will result in a bias in the calculated FDR. In this work, we demonstrate a bias due to incorrect random sampling in the widely used GO::Term Finder package. Both T(2) and permutation tests are used to confirm the bias for a test set of data, which leads to an overestimation of the FDR of about 10. A simple fix to the random sampling method is proposed to remove the bias.}, author = {Flight, Robert M. and Wentzell, Peter D.}, doi = {10.1093/bib/bbn054}, month = {dec}, title = {Potential Bias in GO::TermFinder}, url = {https://academic.oup.com/bib/article-pdf/10/3/289/556336/bbn054.pdf}, year = {2008} } @article{Flight2010, abstract = {In the analysis of data from high-throughput experiments, information regarding the underlying data structure provides the researcher with confidence in the appropriateness of various analysis methods. One extremely simple but powerful data visualization method is the correlation heat map, whereby correlations between experiments/conditions are calculated and represented using color. In this work, the use of correlation maps to shed light on transcription patterns from DNA microarray time course data prior to gene-level analysis is described. Using three different time course studies from the literature, it is shown how the patterns observed at the array level provide insights into the dynamics of the system under study and the experimental design.}, author = {Flight, Robert M. and Wentzell, Peter D.}, doi = {10.1089/omi.2009.0096}, month = {feb}, title = {Preliminary Exploration of Time Course DNA Microarray Data with Correlation Maps}, url = {https://oadoi.org/10.1089/omi.2009.0096}, year = {2010} } @misc{Flight2014, author = {Flight, Robert M.}, doi = {10.6084/m9.figshare.963095}, month = {jan}, title = {ccPaper}, url = {http://dx.doi.org/10.6084/M9.FIGSHARE.963095}, year = {2014} } @article{Flight2014_2, abstract = {Assessment of high-throughput –omics data initially focuses on relative or raw levels of a particular feature, such as an expression value for a transcript, protein, or metabolite. At a second level, analyses of annotations including known or predicted functions and associations of each individual feature, attempt to distill biological context. Most currently available comparative- and meta-analyses methods are dependent on the availability of identical features across data sets, and concentrate on determining features that are differentially expressed across experiments, some of which may be considered “biomarkers”. The heterogeneity of measurement platforms and inherent variability of biological systems confounds the search for robust biomarkers indicative of a particular condition. In many instances, however, multiple data sets show involvement of common biological processes or signaling pathways, even though individual features are not commonly measured or differentially expressed between them.We developed a methodology, CATEGORYCOMPARE, for cross-platform and cross-sample comparison of high-throughput data at the annotation level. We assessed the utility of the approach using hypothetical data, as well as determining similarities and differences in the set of processes in two instances: 1) denervated skin vs. denervated muscle, and 2) colon from Crohn’s disease vs. colon from ulcerative colitis. The hypothetical data showed that in many cases comparing annotations gave superior results to comparing only at the gene level. Improved analytical results depended as well on the number of genes included in the annotation term, the amount of noise in relation to the number of genes expressing in unenriched annotation categories, and the specific method in which samples are combined.CATEGORYCOMPARE is available from http://bioconductor.org/packages/release/bioc/html/categoryCompare.html}, author = {Flight, Robert M. and Harrison, Benjamin J. and Mohammad, Fahim and Bunge, Mary B. and Moon, Lawrence D. F. and Petruska, Jeffrey C. and Rouchka, Eric C.}, doi = {10.3389/fgene.2014.00098}, journal = {Frontiers in Genetics}, month = {apr}, title = {categoryCompare, an analytical tool based on feature annotations}, url = {http://dx.doi.org/10.3389/fgene.2014.00098}, volume = {5}, year = {2014} } @misc{Flight2015, author = {Flight, Robert M. and Fondufe-Mittendorf, Yvonne and Moseley, Hunter Nb}, doi = {10.6084/m9.figshare.1267544}, month = {jan}, title = {fmcorrelationbreastcaparp1: Functions for calculating the correlations in PARP1 nucleosome data in breast cancer cell lines}, url = {http://doi.org/10.6084/m9.figshare.1267544.v1}, year = {2015} } @article{Karakach2007, abstract = {DNA microarrays permit the measurement of gene expression across the entire genome of an organism, but the quality of the thousands of measurements is highly variable. For spotted dual-color microarrays the situation is complicated by the use of ratio measurements. Studies have shown that measurement errors can be described by multiplicative and additive terms, with the latter dominating for low-intensity measurements. In this work, a measurement-error model is presented that partitions the variance into general experimental sources and sources associated with the calculation of the ratio from noisy pixel data. The former is described by a proportional (multiplicative) structure, while the latter is estimated using a statistical bootstrap method. The model is validated using simulations and three experimental data sets. Monte-Carlo fits of the model to data from duplicate experiments are excellent, but suggest that the bootstrap estimates, while proportionately correct, may be underestimated. The bootstrap standard error estimates are particularly useful in determining the reliability of individual microarray spots without the need for replicate spotting. This information can be used in screening or weighting the measurements.}, author = {Karakach, Tobias K. and Flight, Robert M. and Wentzell, Peter D.}, doi = {10.1007/s00216-007-1617-0}, month = {sep}, title = {Bootstrap method for the estimation of measurement uncertainty in spotted dual-color DNA microarrays}, url = {https://www.researchgate.net/profile/Tobias_Karakach/publication/5945736_Bootstrap_method_for_the_estimation_of_measurement_uncertainty_in_spotted_dual-color_DNA_microarrays/links/0a85e5349b990496a3000000.pdf}, year = {2007} } @article{Karakach2010, abstract = {This tutorial presents a basic introduction to DNA microarrays as employed for gene expression analysis, approaching the subject from a chemometrics perspective. The emphasis is on describing the nature of the measurement process, from the platforms used to a few of the standard higher-level data analysis tools employed. Topics include experimental design, detection, image processing, measurement errors, ratio calculation, background correction, normalization, and higher-level data processing. The objective is to present the chemometrician with as clear a picture as possible of an evolving technology so that the strengths and limitations of DNA microarrays are appreciated. Although the focus is primarily on spotted, two-color microarrays, a significant discussion of single-channel, lithographic arrays is also included. ; peer reviewed: yes ; NRC Pub: yes}, author = {Karakach, Tobias K. and Flight, Robert M. and Douglas, Susan E. and Wentzell, Peter D.}, doi = {10.1016/j.chemolab.2010.04.003}, month = {nov}, title = {An introduction to DNA microarrays for gene expression analysis}, url = {https://oadoi.org/10.1016/j.chemolab.2010.04.003}, year = {2010} } @article{Mohammad2011, abstract = {Existing analytical tools enable broad-scale experimentation ("-omics") to provide a great deal of information about intracellular processes. However, extraction of information regarding intercellular interactions, particularly from separate datasets, is generally more limited, principally for lack of specialized analytical tools. In turn, few experiments are designed to examine intercellular interactions. Using the large number of previously identified interactions available in databases may provide a useful platform for analyzing these interactions. However, finding all possible interactions is a computationally intensive task and quickly becomes intractable using a naive approach on networks with hundreds of thousands of nodes and edges. A heuristic algorithm similar to the "Backtracking algorithm" is proposed to find all possible protein interactions across any two gene sets. The algorithm starts with an initial set of genes and incrementally adds a candidate to the interaction network and abandons each candidate x as soon as it is determined that x does not lead to a valid solution. An exclusion vector (EV) is used to accomplish this task and is populated at each step, maintaining a list of those nodes that need to be excluded from interactions in the future and thus restricting the size of the network. The EV also allows location awareness by using Gene Ontology (GO) cell component classifications to discard nodes that are not relevant for the network. This algorithm can be readily applied to pathway analysis and the determination of elements underlying intercellular interactions.}, author = {Mohammad, Fahim and Flight, Robert M. and Harrison, Benjamin J. and Petruska, Jeffrey C. and Rouchka, Eric C.}, doi = {10.1109/bibe.2011.9}, journal = {2011 IEEE 11th International Conference on Bioinformatics and Bioengineering}, month = {oct}, title = {A Heuristic Algorithm for Detecting Intercellular Interactions}, url = {https://www.researchgate.net/profile/Eric_Rouchka/publication/221197809_A_Heuristic_Algorithm_for_Detecting_Intercellular_Interactions/links/00b49539af47b04a98000000.pdf}, year = {2011} } @article{Mohammad2011_2, abstract = {A variety of systems exist in which annotations are available at various levels of granularity to a reference coordinate system, such as roads and landmarks on a map, features within a 2-dimensional or 3-dimensional image, or genetic entities (GEs) mapped to a reference genome. As the number of annotations grows, methods to efficiently locate overlapping entities within a specific interval of interest are needed. In this paper, the efficiency of using interval trees for storing, maintaining, and querying large numbers of intervals with special attention to genetic entities is demonstrated. The results suggest a significant speed -- up when compared to relational database approaches. As such, interval trees serve as a suitable alternative for storing and searching annotations to a reference coordinate system.}, author = {Mohammad, Fahim and Flight, Robert M. and Harrison, Benjamin J. and Petruska, Jeffrey C. and Rouchka, Eric C.}, doi = {10.1109/bibe.2011.49}, journal = {2011 IEEE 11th International Conference on Bioinformatics and Bioengineering}, month = {oct}, title = {Interval Trees for Detection of Overlapping Genetic Entities}, url = {https://www.researchgate.net/profile/Eric_Rouchka/publication/221197298_Interval_Trees_for_Detection_of_Overlapping_Genetic_Entities/links/0deec539af4a4a2589000000.pdf}, year = {2011} } @article{Mohammad2012, abstract = {Abstract Background High-throughput molecular biology techniques yield vast amounts of data, often by detecting small portions of ribonucleotides corresponding to specific identifiers. Existing bioinformatic methodologies categorize and compare these elements using inferred descriptive annotation given this sequence information irrespective of the fact that it may not be representative of the identifier as a whole. Results All annotations, no matter the granularity, can be aligned to genomic sequences and therefore annotated by genomic intervals. We have developed AbsIDconvert, a methodology for converting between genomic identifiers by first mapping them onto a common universal coordinate system using an interval tree which is subsequently queried for overlapping identifiers. AbsIDconvert has many potential uses, including gene identifier conversion, identification of features within a genomic region, and cross-species comparisons. The utility is demonstrated in three case studies: 1) comparative genomic study mapping plasmodium gene sequences to corresponding human and mosquito transcriptional regions; 2) cross-species study of Incyte clone sequences; and 3) analysis of human Ensembl transcripts mapped by Affymetrix®; and Agilent microarray probes. AbsIDconvert currently supports ID conversion of 53 species for a given list of input identifiers, genomic sequence, or genome intervals. Conclusion AbsIDconvert provides an efficient and reliable mechanism for conversion between identifier domains of interest. The flexibility of this tool allows for custom definition identifier domains contingent upon the availability and determination of a genomic mapping interval. As the genomes and the sequences for genetic elements are further refined, this tool will become increasingly useful and accurate. AbsIDconvert is freely available as a web application or downloadable as a virtual machine at:http://bioinformatics.louisville.edu/abid/. }, author = {Mohammad, Fahim and Flight, Robert M. and Harrison, Benjamin J. and Petruska, Jeffrey C. and Rouchka, Eric C.}, doi = {10.1186/1471-2105-13-229}, journal = {BMC Bioinformatics}, month = {jan}, title = {AbsIDconvert: An absolute approach for converting genetic identifiers at different granularities}, url = {http://dx.doi.org/10.1186/1471-2105-13-229}, volume = {13}, year = {2012} } @article{Murray2009, abstract = {An experimental microdiet prepared using an internal gelation method was used to partially replace the traditional live feed (Artemia) for larval Atlantic halibut, Hippoglossus hippoglossus L. Three trials were conducted with microdiet introduced at 20, 32, and 43 days post first feeding and larvae were sampled at approximately 2, 13, 23, and 33 days after microdiet introduction in each trial. The success of feeding was assessed by morphometrics and histological analysis of gut contents. Microdiet particles were readily consumed after a period of adaptation and provided an adequate source of nutrients with no significant increase in mortality in the microdiet-fed group compared to the control group. However, growth was limited and there was an increased incidence of malpigmentation of the eye and skin. Subtle changes in underlying digestive and developmental physiology were revealed by microarray analysis of RNA from control and experimental fish given microdiet from day 20 post first feeding. Fifty-eight genes were differentially expressed over the four sampling times in the course of the trial and the 28 genes with annotated functions fell into five major categories: metabolism and biosynthesis, cell division and proliferation, protein trafficking, cell structure, and stress. Interestingly, several of these genes were involved in pigmentation and eye development, in agreement with the phenotypic abnormalities seen in the larvae ; peer reviewed: yes ; NRC Pub: yes}, author = {Murray, H. M. and Lall, S. P. and Rajaselvam, R. and Boutilier, L. A. and La, Boutilier and Flight, R. M. and Blanchard, B. and Colombo, S. and Mohindra, V. and Yúfera, M. and Douglas, S. E.}, doi = {10.1007/s10126-009-9211-4}, journal = {Marine Biotechnology}, month = {jul}, pages = {214-229}, title = {Effect of Early Introduction of Microencapsulated Diet to Larval Atlantic Halibut, Hippoglossus hippoglossus L. Assessed by Microarray Analysis}, url = {http://nparc.cisti-icist.nrc-cnrc.gc.ca/eng/view/accepted/?id=5749a3a4-4101-4e6a-8d9d-2a7ac2087974}, volume = {12}, year = {2009} } @article{Murray2010, abstract = {Aquaculture feeds for carnivorous finfish species have been dependent upon the use of fish meal as the major source of dietary protein; however, the increasing demands upon the finite quantity of this high-quality protein source requires that feeds become increasingly comprised of alternative plant and/or animal protein. Soybean meal has been has been used to partially replace fish meal in the diets of several fish but it is known to cause enteritis in Atlantic salmon, Salmo salar. We have compared two groups of juvenile (207.2 ± 6.6 g) Atlantic halibut, Hippoglossus hippoglossus, L., fed diets containing fish meal (FM; control) or 30% soybean meal (SBM; experimental) as a protein source for 3 weeks. No detectable difference in feed intake or palatability was evident with the SBM diet relative to the FM diet. Histological examination of the distal intestine was performed to examine leukocyte infiltration of the lamina propria and other changes in morphology commonly observed with soybean-induced enteritis of salmonids. No significant difference was found between fish fed the FM and SBM diets. Global gene expression profiling performed using a high-density oligonucleotide microarray containing 9260 unique features, printed in quadruplicate, from Atlantic halibut revealed subtle underlying changes in the expression of several immune genes and genes involved in muscle formation, lipid transport, xenobiotic detoxification, digestion and intermediary metabolism. These results indicate that SBM can be used successfully as a replacement for animal protein in diet for juvenile Atlantic halibut, although long-term effects on the immune system may ensue. Crown Copyright © 2009. ; peer reviewed: yes ; NRC Pub: yes}, author = {Murray, Harry M. and Lall, Santosh P. and Rajaselvam, Rajesh and Boutilier, Lee Anne and Blanchard, Brian and Flight, Robert M. and Colombo, Stefanie and Mohindra, Vindhya and Douglas, Susan E.}, doi = {10.1016/j.aquaculture.2009.11.001}, journal = {Aquaculture}, month = {jan}, pages = {282-293}, title = {A nutrigenomic analysis of intestinal response to partial soybean meal replacement in diets for juvenile Atlantic halibut, Hippoglossus hippoglossus, L.}, url = {http://nparc.cisti-icist.nrc-cnrc.gc.ca/eng/view/accepted/?id=db3d7473-0ce7-4a5e-bcbd-fc8707f83620}, volume = {298}, year = {2010} } @article{Nalabothula2015, abstract = {Poly (ADP-ribose) polymerase-1 (PARP1) is a nuclear enzyme involved in DNA repair, chromatin remodeling and gene expression. PARP1 interactions with chromatin architectural multi-protein complexes (i.e. nucleosomes) alter chromatin structure resulting in changes in gene expression. Chromatin structure impacts gene regulatory processes including transcription, splicing, DNA repair, replication and recombination. It is important to delineate whether PARP1 randomly associates with nucleosomes or is present at specific nucleosome regions throughout the cell genome. We performed genome-wide association studies in breast cancer cell lines to address these questions. Our studies show that PARP1 associates with epigenetic regulatory elements genome-wide, such as active histone marks, CTCF and DNase hypersensitive sites. Additionally, the binding of PARP1 to chromatin genome-wide is mutually exclusive with DNA methylation pattern suggesting a functional interplay between PARP1 and DNA methylation. Indeed, inhibition of PARylation results in genome-wide changes in DNA methylation patterns. Our results suggest that PARP1 controls the fidelity of gene transcription and marks actively transcribed gene regions by selectively binding to transcriptionally active chromatin. These studies provide a platform for developing our understanding of PARP1’s role in gene regulation.}, author = {Nalabothula, Narasimharao and Al-Jumaily, Taha and Eteleeb, Abdallah M. and Flight, Robert M. and Xiaorong, Shao and Moseley, Hunter and Rouchka, Eric C. and Fondufe-Mittendorf, Yvonne N.}, doi = {10.1371/journal.pone.0135410}, journal = {PLoS ONE}, month = {aug}, pages = {e0135410}, title = {Genome-Wide Profiling of PARP1 Reveals an Interplay with Gene Regulatory Regions and DNA Methylation}, url = {http://dx.doi.org/10.1371/journal.pone.0135410}, volume = {10}, year = {2015} } @article{Tauler2009, abstract = {In this work the performance and theoretical background behind two of the most commonly used receptor modelling methods in aerosol science, principal components analysis (PCA) and positive matrix factorization (PMF), as well as multivariate curve resolution by alternating least squares (MCR-ALS) and weighted alternating least squares (MCR-WALS), are examined. The performance of the four methods was initially evaluated under standard operational conditions, and modifications regarding data pre-treatment were then included. The methods were applied using raw and scaled data, with and without uncertainty estimations. Strong similarities were found among the sources identified by PMF and MCR-WALS (weighted models), whereas discrepancies were obtained with MCR-ALS (unweighted model). Weighting of input data by means of uncertainty estimates was found to be essential to obtain robust and accurate factor identification. The use of scaled (as opposed to raw) data highlighted the contribution of trace elements to the compositional profiles, which was key to the correct interpretation of the nature of the sources. Our results validate the performance of MCR-WALS for aerosol Pollution studies. (C) 2009 Elsevier Ltd. All rights reserved.}, author = {Tauler, R. and Viana, M. and Querol, X. and Alastuey, A. and Flight, R. M. and Wentzell, P. D. and Hopke, P. K.}, doi = {10.1016/j.atmosenv.2009.05.018}, month = {aug}, title = {Comparison of the results obtained by four receptor modelling methods in aerosol source apportionment studies}, url = {https://www.researchgate.net/profile/Roma_Tauler/publication/233834731_Comparison_of_the_Results_Obtained_by_Four_Receptor_Modeling_Methods_in_Aerosol_Source_Apportionment_Studies/links/00b7d53517b590209f000000.pdf}, year = {2009} }