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PubMed2005

CASCAD: a database of annotated candidate single nucleotide polymorphisms associated with expressed sequences.

BACKGROUND: With the recent progress made in large-scale genome sequencing projects a vast amount of novel data is becoming available. A comparative sequence analysis, exploiting sequence information from various resources, can be used to uncover hidden information, such as genetic variation. Although there are enormous amounts of SNPs for a wide variety of organisms submitted to NCBI dbSNP and annotated in most genome assembly viewers like Ensembl and the UCSC Genome Browser, these platforms do not easily allow for extensive annotation and incorporation of experimental data supporting the polymorphism. However, such information is very important for selecting the most promising and useful candidate polymorphisms for use in experimental setups. DESCRIPTION: The CASCAD database is designed for presentation and query of candidate SNPs that are retrieved by in silico mining of high-throughput sequencing data. Currently, the database provides collections of laboratory rat (Rattus norvegicus) and zebrafish (Danio rerio) candidate SNPs. The database stores detailed information about raw data supporting the candidate, extensive annotation and links to external databases (e.g. GenBank, Ensembl, UniGene, and LocusLink), verification information, and predictions of a potential effect for non-synonymous polymorphisms in coding regions. The CASCAD website allows search based on an arbitrary combination of 27 different parameters related to characteristics like candidate SNP quality, genomic localization, and sequence data source or strain. In addition, the database can be queried with any custom nucleotide sequences of interest. The interface is crosslinked to other public databases and tightly coupled with primer design and local genome assembly interfaces in order to facilitate experimental verification of candidates. CONCLUSIONS: The CASCAD database discloses detailed information on rat and zebrafish candidate SNPs, including the raw data underlying its discovery. An advanced web-based search interface http://cascad.niob.knaw.nl allows universal access to the database content and allows various queries supporting many types of research utilizing single nucleotide polymorphisms.

Animals↗
PubMed2005

A generally applicable validation scheme for the assessment of factors involved in reproducibility and quality of DNA-microarray data.

BACKGROUND: In research laboratories using DNA-microarrays, usually a number of researchers perform experiments, each generating possible sources of error. There is a need for a quick and robust method to assess data quality and sources of errors in DNA-microarray experiments. To this end, a novel and cost-effective validation scheme was devised, implemented, and employed. RESULTS: A number of validation experiments were performed on Lactococcus lactis IL1403 amplicon-based DNA-microarrays. Using the validation scheme and ANOVA, the factors contributing to the variance in normalized DNA-microarray data were estimated. Day-to-day as well as experimenter-dependent variances were shown to contribute strongly to the variance, while dye and culturing had a relatively modest contribution to the variance. CONCLUSION: Even in cases where 90% of the data were kept for analysis and the experiments were performed under challenging conditions (e.g. on different days), the CV was at an acceptable 25%. Clustering experiments showed that trends can be reliably detected also from genes with very low expression levels. The validation scheme thus allows determining conditions that could be improved to yield even higher DNA-microarray data quality.

Analysis of Variance↗
PubMed2023

Inference of phylogenetic trees directly from raw sequencing reads using Read2Tree.

Current methods for inference of phylogenetic trees require running complex pipelines at substantial computational and labor costs, with additional constraints in sequencing coverage, assembly and annotation quality, especially for large datasets. To overcome these challenges, we present Read2Tree, which directly processes raw sequencing reads into groups of corresponding genes and bypasses traditional steps in phylogeny inference, such as genome assembly, annotation and all-versus-all sequence comparisons, while retaining accuracy. In a benchmark encompassing a broad variety of datasets, Read2Tree is 10-100 times faster than assembly-based approaches and in most cases more accurate-the exception being when sequencing coverage is high and reference species very distant. Here, to illustrate the broad applicability of the tool, we reconstruct a yeast tree of life of 435 species spanning 590 million years of evolution. We also apply Read2Tree to >10,000 Coronaviridae samples, accurately classifying highly diverse animal samples and near-identical severe acute respiratory syndrome coronavirus 2 sequences on a single tree. The speed, accuracy and versatility of Read2Tree enable comparative genomics at scale.

Animals↗
PubMed2003

Analysis and functional annotation of an expressed sequence tag collection for tropical crop sugarcane.

To contribute to our understanding of the genome complexity of sugarcane, we undertook a large-scale expressed sequence tag (EST) program. More than 260,000 cDNA clones were partially sequenced from 26 standard cDNA libraries generated from different sugarcane tissues. After the processing of the sequences, 237,954 high-quality ESTs were identified. These ESTs were assembled into 43,141 putative transcripts. Of the assembled sequences, 35.6% presented no matches with existing sequences in public databases. A global analysis of the whole SUCEST data set indicated that 14,409 assembled sequences (33% of the total) contained at least one cDNA clone with a full-length insert. Annotation of the 43,141 assembled sequences associated almost 50% of the putative identified sugarcane genes with protein metabolism, cellular communication/signal transduction, bioenergetics, and stress responses. Inspection of the translated assembled sequences for conserved protein domains revealed 40,821 amino acid sequences with 1415 Pfam domains. Reassembling the consensus sequences of the 43,141 transcripts revealed a 22% redundancy in the first assembling. This indicated that possibly 33,620 unique genes had been identified and indicated that >90% of the sugarcane expressed genes were tagged.

Computational Biology↗
PubMed2006

Female pelvis: MR imaging at 3.0 T with sensitivity encoding and flip-angle sweep technique.

This study had institutional review board approval; all 33 patients (mean age, 47 years +/- 16 [standard deviation]) gave informed consent. The aim was to prospectively evaluate the diagnostic image quality yielded by a 3.0-T T2-weighted turbo spin-echo magnetic resonance imaging sequence with a very short imaging time versus that yielded by a standard 3.0-T sequence at imaging of the female pelvis. Signal-to-noise ratio and delineation of gynecologic disorders were approximately equal between the two sequences. The majority of tissue contrasts were comparable, but contrast between fluid and muscle was significantly higher and motion artifacts were reduced (P < .001 for both) with the short imaging time sequence. The fast sequence maintained or improved image quality and thus seems to be advantageous for uncooperative patients.

Adolescent↗
PubMed2003

Demystified...tissue microarray technology.

Several "high throughput methods" have been introduced into research and routine laboratories during the past decade. Providing a new approach to the analysis of genomic alterations and RNA or protein expression patterns, these new techniques generate a plethora of new data in a relatively short time, and promise to deliver clues to the diagnosis and treatment of human cancer. Along with these revolutionary developments, new tools for the interpretation of these large sets of data became necessary and are now widely available. Tissue microarray (TMA) technology is one of these new tools. It is based on the idea of applying miniaturisation and a high throughput approach to the analysis of intact tissues. The potential and the scientific value of TMAs in modern research have been demonstrated in a logarithmically increasing number of studies. The spectrum for additional applications is widening rapidly, and comprises quality control in histotechnology, longterm tissue banking, and the continuing education of pathologists. This review covers the basic technical aspects of TMA production and discusses the current and potential future applications of TMA technology.

Animals↗
PubMed2005

Quality determination and the repair of poor quality spots in array experiments.

BACKGROUND: A common feature of microarray experiments is the occurrence of missing gene expression data. These missing values occur for a variety of reasons, in particular, because of the filtering of poor quality spots and the removal of undefined values when a logarithmic transformation is applied to negative background-corrected intensities. The efficiency and power of an analysis performed can be substantially reduced by having an incomplete matrix of gene intensities. Additionally, most statistical methods require a complete intensity matrix. Furthermore, biases may be introduced into analyses through missing information on some genes. Thus methods for appropriately replacing (imputing) missing data and/or weighting poor quality spots are required. RESULTS: We present a likelihood-based method for imputing missing data or weighting poor quality spots that requires a number of biological or technical replicates. This likelihood-based approach assumes that the data for a given spot arising from each channel of a two-dye (two-channel) cDNA microarray comparison experiment independently come from a three-component mixture distribution--the parameters of which are estimated through use of a constrained E-M algorithm. Posterior probabilities of belonging to each component of the mixture distributions are calculated and used to decide whether imputation is required. These posterior probabilities may also be used to construct quality weights that can down-weight poor quality spots in any analysis performed afterwards. The approach is illustrated using data obtained from an experiment to observe gene expression changes with 24 hr paclitaxel (Taxol) treatment on a human cervical cancer derived cell line (HeLa). CONCLUSION: As the quality of microarray experiments affect downstream processes, it is important to have a reliable and automatic method of identifying poor quality spots and arrays. We propose a method of identifying poor quality spots, and suggest a method of repairing the arrays by either imputation or assigning quality weights to the spots. This repaired data set would be less biased and can be analysed using any of the appropriate statistical methods found in the microarray literature.

Algorithms↗
PubMed2006

Tests for differential gene expression using weights in oligonucleotide microarray experiments.

BACKGROUND: Microarray data analysts commonly filter out genes based on a number of ad hoc criteria prior to any high-level statistical analysis. Such ad hoc approaches could lead to conflicting conclusions with no clear guidance as to which method is most likely to be reproducible. Furthermore, the number of tests performed with concomitant inflation in type I error also plagues the statistical analysis of microarray data, since the number of tested quantities in a study significantly affects the family-wise error rate. It would, therefore, be very useful to develop and adopt strategies that allow quantification of the quality of each probeset, to filter out or give little credence to low-quality or unexpressed probesets, and to incorporate these strategies into gene selection within a multiple testing framework. RESULTS: We have proposed a unified scheme for filtering and gene selection. For Affymetrix gene expression microarrays, we developed new methods for measuring the reliability of a particular probeset in a single array, and we used these to develop measures for a set of arrays. These measures are then used as weights in standard t-statistic calculations, and are incorporated into the multiple testing procedures. We demonstrated the advantages of our methods using simulated data, publicly available spiked-in data as well as data comparing normal muscle to muscle from patients with Duchenne muscular dystrophy (DMD), in which a set of truly differentially expressed genes is known. CONCLUSION: Our quality measures provide convenient ways to search for individual genes of high quality. The quality weighting strategies we proposed for testing differential gene expression have demonstrable improvement on the traditional filtering methods, the standard t-statistic and a regularized t-statistic in Affymetrix data analysis.

Data Interpretation, Statistical↗
PubMed2003

The Stanford Microarray Database: data access and quality assessment tools.

The Stanford Microarray Database (SMD; http://genome-www.stanford.edu/microarray/) serves as a microarray research database for Stanford investigators and their collaborators. In addition, SMD functions as a resource for the entire scientific community, by making freely available all of its source code and providing full public access to data published by SMD users, along with many tools to explore and analyze those data. SMD currently provides public access to data from 3500 microarrays, including data from 85 publications, and this total is increasing rapidly. In this article, we describe some of SMD's newer tools for accessing public data, assessing data quality and for data analysis.

Animals↗
PubMed2006

Inference of population genetic parameters in metagenomics: a clean look at messy data.

Metagenomic projects generate short, overlapping fragments of DNA sequence, each deriving from a different individual. We report a new method for inferring the scaled mutation rate, theta = 2Neu, and the scaled exponential growth rate, R = Ner, from the site-frequency spectrum of these data while accounting for sequencing error via Phred quality scores. After obtaining maximum likelihood parameter estimates for theta and R, we calculate empirical Bayes quality scores reflecting the posterior probability that each apparently polymorphic site is truly polymorphic; these scores can then be used for other applications such as SNP discovery. For realistic parameter ranges, analytic and simulation results show our estimates to be essentially unbiased with tight confidence intervals. In contrast, choosing an arbitrary quality score cutoff (e.g., trimming reads) and ignoring further quality information during inference yields biased estimates with greater variance. We illustrate the use of our technique on a new project analyzing activated sludge from a lab-scale bioreactor seeded by a wastewater treatment plant.

Bacteria↗
PubMed2005

A microarray data analysis framework for postmortem tissues.

This paper will give a complete methodological approach to the processing of oligonucleotide microarray data from postmortem tissue, particularly brain matter. Attention will be drawn to each of the important stages in the process; specifically the quality control, gene expression value calculation, multiple hypothesis testing and correlation analyses. We shall initially discuss the theoretical foundations of each individual method and subsequently apply the ensemble to a sample data set to illustrate and visualise important points.

Algorithms↗
PubMedDate not supplied

Ground water quality assessment using multi-rectangular diagrams.

A new graphical technique is proposed here for classifying chemical analyses of ground water. In this technique, a diagram is constructed using rectangular coordinates. The new diagram, called a multi-rectangular diagram (MRD), uses adjacent multi-rectangles in which each rectangle represents a specific ground water type. This new diagram has the capability to accommodate a large number of data sets. MRDs have been used to classify chemical analyses of ground water in the Chaj Doab area of Pakistan to illustrate this new approach. Using this graphical method, the differentiated ground water types are calcium bicarbonate, magnesium bicarbonate, sodium bicarbonate, and sodium sulfate. Sodium bicarbonate emerges as the most abundant ground water type. MRDs also offer a visual display of the Chebotarev sequence of ground water quality evolution.

Environmental Monitoring↗
PubMed2006

Impact of RNA degradation on gene expression profiles: assessment of different methods to reliably determine RNA quality.

DNA microarray technology enables investigators to measure the expression of several 1000 mRNA species simultaneously in a biological specimen. However, the reliability of the microarray technology to detect transcriptional differences representative of the original samples is affected by the quality of the extracted RNA. Thus, it is of critical importance to standardize sample-handling protocols and to perform a quality assessment of RNA preparations. In this report, 59 human tissue samples were used to evaluate the relationships between RNA quality and gene expression. From Affymetrix GeneChip array data analysis of these samples, we compared the performance of the 28S/18S ratio, two computer methods (RIN and degradometer) and our in-house RNA quality scale (RQS) in assessing RNA quality. The optimal RNA reliability threshold was determined for each method using statistical discrimination measures. We showed that RQS, RIN and degradometer have a similar capacity to detect reliable RNA samples whereas the 28S/18S ratio leads to a misleading categorization. Furthermore, we developed a new approach, based on clustering analyses of full chip expression, to control RNA quality after hybridization experiments. The combination of these methods, allowing monitoring of RNA quality prior to and after the hybridization experiments, ensured reliable and reproducible microarray data.

Cluster Analysis↗
PubMed2005

ADDA: a domain database with global coverage of the protein universe.

We used the Automatic Domain Decomposition Algorithm (ADDA) to generate a database of protein domain families with complete coverage of all protein sequences. Sequences are split into domains and domains are grouped into protein domain families in a completely automated process. The current database contains domains for more than 1.5 million sequences in more than 40,000 domain families. In particular, there are 3828 novel domain families that do not overlap with the curated domain databases Pfam, SCOP and InterPro. The data are freely available for downloading and querying via a web interface (http://ekhidna.biocenter.helsinki.fi:9801/sqgraph/pairsdb).

Algorithms↗
PubMed2002

Nondestructive quality control for microarray production.

The use of microarrays to monitor gene expression has become a standard research tool at both academic and industrial research institutions. Quality control of common printing defects during DNA deposition onto glass substrates is critical to maintaining data integrity and preventing the needless consumption of precious RNA, labeling reagents, and time. Here we demonstrate a nondestructive method for monitoring the quality of every spot on every chip of a microarray production run. We have identified many common manufacturing defects, while not perturbing the attachment of our oligonucleotide target to the substrate or altering further hybridization. This protocol is simple, fast, and inexpensive.

Carbocyanines↗
PubMed2004

A preprocessor for shotgun assembly of large genomes.

The whole-genome shotgun (WGS) assembly technique has been remarkably successful in efforts to determine the sequence of bases that make up a genome. WGS assembly begins with a large collection of short fragments that have been selected at random from a genome. The sequence of bases at each end of the fragment is determined, albeit imprecisely, resulting in a sequence of letters called a "read." Each letter in a read is assigned a quality value, which estimates the probability that a sequencing error occurred in determining that letter. Reads are typically cut off after about 500 letters, where sequencing errors become endemic. We report on a set of procedures that (1) corrects most of the sequencing errors, (2) changes quality values accordingly, and (3) produces a list of "overlaps," i.e., pairs of reads that plausibly come from overlapping parts of the genome. Our procedures, which we call collectively the "UMD Overlapper," can be run iteratively and as a preprocessor for other assemblers. We tested the UMD Overlapper on Celera's Drosophila reads. When we replaced Celera's overlap procedures in the front end of their assembler, it was able to produce a significantly improved genome.

Animals↗
PubMed2004

Quick and simple: quality control of microarray data.

MOTIVATION: Microarrays are high-throughput tools for parallel miniaturized detection of biomolecules. In contrast to experiments using ratios of signals in two channels, experiments with only one fluorescent dye cause special problems for data analysis. The present work compares algorithms for quality filtering on spot level as well as array/slide level. RESULTS: Methods for quantitative spot filtering are discussed and new sets of quality scores for data preprocessing are designed. As measures of spot quality also reflect the quality of protocols, they were employed to find the optimal print buffer in an optimization experiment. In order to determine problematic arrays within a set of replicates we tested methods of outlier detection which can suitably replace the visual inspection of slides. CONTACT: Ursula.Sauer@arcs.ac.at.

Algorithms↗
PubMed2004

A dynamic, web-accessible resource to process raw microarray scan data into consolidated gene expression values: importance of replication.

We propose a freely accessible web-based pipeline, which processes raw microarray scan data to obtain experimentally consolidated gene expression values. The tool MADSCAN, which stands for MicroArray Data Suites of Computed ANalysis, makes a practical choice among the numerous methods available for filtering, normalizing and scaling of raw microarray expression data in a dynamic and automatic way. Different statistical methods have been adapted to extract reliable information from replicate gene spots as well as from replicate microarrays for each biological situation under study. A carefully constructed experimental design thus allows to detect outlying expression values and to identify statistically significant expression values, together with a list of quality controls with proposed threshold values. The integrated processing procedure described here, based on multiple measurements per gene, is decisive for reliably monitoring subtle gene expression changes typical for most biological events.

Data Interpretation, Statistical↗