MOTIVATION: Gene lists are routinely produced from various omic studies. Enrichment analysis can link these gene lists with underlying molecular pathways and functional categories such as gene ontology (GO) and other databases. RESULTS: To complement existing tools, we developed ShinyGO based on a large annotation database derived from Ensembl and STRING-db for 59 plant, 256 animal, 115 archeal and 1678 bacterial species. ShinyGO's novel features include graphical visualization of enrichment results and gene characteristics, and application program interface access to KEGG and STRING for the retrieval of pathway diagrams and protein-protein interaction networks. ShinyGO is an intuitive, graphical web application that can help researchers gain actionable insights from gene-sets. AVAILABILITY AND IMPLEMENTATION: http://ge-lab.org/go/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

BACKGROUND: RNA-seq is widely used for transcriptomic profiling, but the bioinformatics analysis of resultant data can be time-consuming and challenging, especially for biologists. We aim to streamline the bioinformatic analyses of gene-level data by developing a user-friendly, interactive web application for exploratory data analysis, differential expression, and pathway analysis. RESULTS: iDEP (integrated Differential Expression and Pathway analysis) seamlessly connects 63 R/Bioconductor packages, 2 web services, and comprehensive annotation and pathway databases for 220 plant and animal species. The workflow can be reproduced by downloading customized R code and related pathway files. As an example, we analyzed an RNA-Seq dataset of lung fibroblasts with Hoxa1 knockdown and revealed the possible roles of SP1 and E2F1 and their target genes, including microRNAs, in blocking G1/S transition. In another example, our analysis shows that in mouse B cells without functional p53, ionizing radiation activates the MYC pathway and its downstream genes involved in cell proliferation, ribosome biogenesis, and non-coding RNA metabolism. In wildtype B cells, radiation induces p53-mediated apoptosis and DNA repair while suppressing the target genes of MYC and E2F1, and leads to growth and cell cycle arrest. iDEP helps unveil the multifaceted functions of p53 and the possible involvement of several microRNAs such as miR-92a, miR-504, and miR-30a. In both examples, we validated known molecular pathways and generated novel, testable hypotheses. CONCLUSIONS: Combining comprehensive analytic functionalities with massive annotation databases, iDEP ( http://ge-lab.org/idep/ ) enables biologists to easily translate transcriptomic and proteomic data into actionable insights.

BACKGROUND: The dynamic, decentralized world-wide-web has become an essential part of scientific research and communication. Researchers create thousands of web sites every year to share software, data and services. These valuable resources tend to disappear over time. The problem has been documented in many subject areas. Our goal is to conduct a cross-disciplinary investigation of the problem and test the effectiveness of existing remedies. RESULTS: We accessed 14,489 unique web pages found in the abstracts within Thomson Reuters' Web of Science citation index that were published between 1996 and 2010 and found that the median lifespan of these web pages was 9.3 years with 62% of them being archived. Survival analysis and logistic regression were used to find significant predictors of URL lifespan. The availability of a web page is most dependent on the time it is published and the top-level domain names. Similar statistical analysis revealed biases in current solutions: the Internet Archive favors web pages with fewer layers in the Universal Resource Locator (URL) while WebCite is significantly influenced by the source of publication. We also created a prototype for a process to submit web pages to the archives and increased coverage of our list of scientific webpages in the Internet Archive and WebCite by 22% and 255%, respectively. CONCLUSION: Our results show that link decay continues to be a problem across different disciplines and that current solutions for static web pages are helping and can be improved.

UNLABELLED: Studying plants using high-throughput genomics technologies is becoming routine, but interpretation of genome-wide expression data in terms of biological pathways remains a challenge, partly due to the lack of pathway databases. To create a knowledgebase for plant pathway analysis, we collected 1683 lists of differentially expressed genes from 397 gene-expression studies, which constitute a molecular signature database of various genetic and environmental perturbations of Arabidopsis. In addition, we extracted 1909 gene sets from various sources such as Gene Ontology, KEGG, AraCyc, Plant Ontology, predicted target genes of microRNAs and transcription factors, and computational gene clusters defined by meta-analysis. With this knowledgebase, we applied Gene Set Enrichment Analysis to an expression profile of cold acclimation and identified expected functional categories and pathways. Our results suggest that the AraPath database can be used to generate specific, testable hypotheses regarding plant molecular pathways from gene expression data. AVAILABILITY: http://bioinformatics.sdstate.edu/arapath/.

MOTIVATION: Taking advantage of the high sensitivity and specificity of LongSAGE tag for transcript detection and genome mapping, we analyzed the 632 813 unique human LongSAGE tags deposited in public databases to identify novel human antisense transcripts. RESULTS: Our study identified 45 321 tags that match the antisense strand of 9804 known mRNA sequences, 6606 of which contain antisense ESTs and 3198 are mapped only by SAGE tags. Quantitative analysis showed that the detected antisense transcripts are present at levels lower than their counterpart sense transcripts. Experimental results confirmed the presence of antisense transcripts detected by the antisense tags. We also constructed an antisense tag database that can be used to identify the antisense SAGE tags originated from the antisense strand of known mRNA sequences included in the RefSeq database. CONCLUSIONS: Our study highlights the benefits of exploring SAGE data for comprehensive identification of human antisense transcripts and demonstrates the prevalence of antisense transcripts in the human genome.