A score system for quality evaluation of RNA sequence tags: an improvement for gene expression profiling

Background: High-throughput molecular approaches for gene expression profiling, such as Serial Analysis of Gene Expression (SAGE), Massively Parallel Signature Sequencing (MPSS) or Sequencing-by-Synthesis (SBS) represent powerful techniques that provide global transcription profiles of different cell types through sequencing of short fragments of transcripts, denominated sequence tags. These techniques have improved our understanding about the relationships between these expression profiles and cellular phenotypes. Despite this, more reliable datasets are still necessary. In this work, we present a web-based tool named S3T: Score System for Sequence Tags, to index sequenced tags in accordance with their reliability. This is made through a series of evaluations based on a defined rule set. S3T allows the identification/selection of tags, considered more reliable for further gene expression analysis. Results: This methodology was applied to a public SAGE dataset. In order to compare data before and after filtering, a hierarchical clustering analysis was performed in samples from the same type of tissue, in distinct biological conditions, using these two datasets. Our results provide evidences suggesting that it is possible to find more congruous clusters after using S3T scoring system. Conclusion: These results substantiate the proposed application to generate more reliable data. This is a significant contribution for determination of global gene expression profiles. The library analysis with S3T is freely available at http://gdm.fmrp.usp.br/s3t/.S3T source code and datasets can also be downloaded from the aforementioned website.

Brazilian flavonoid database: Application of quality evaluation system

Much information on flavonoid content of Brazilian foods has already been obtained; however, this information is spread in scientific publications and non-published data. The objectives of this work were to compile and evaluate the quality of national flavonoid data according to the United States Department of Agriculture`s Data Quality Evaluation System (USDA-DQES) with few modifications, for future dissemination in the TBCA-USP (Brazilian Food Composition Database). For the compilation, the most abundant compounds in the flavonoid subclasses were considered (flavonols, flavones, isoflavones, flavanones, flavan-3-ols, and anthocyanidins) and the analysis of the compounds by HPLC was adopted as criteria for data inclusion. The evaluation system considers five categories, and the maximum score assigned to each category is 20. For each data, a confidence code (CC) was attributed (A, B, C and D), indicating the quality and reliability of the information. Flavonoid data (773) present in 197 Brazilian foods were evaluated. The CC ""C"" (as average) was attributed to 99% of the data and ""B"" (above average) to 1%. The main categories assigned low average scores were: number of samples; sampling plan and analytical quality control (average scores 2, 5 and 4, respectively). The analytical method category received an average score of 9. The category assigned the highest score was the sample handling (20 average). These results show that researchers need to be conscious about the importance of the number and plan of evaluated samples and the complete description and documentation of all the processes of methodology execution and analytical quality control. (C) 2010 Elsevier Inc. All rights reserved.