BackgroundChromatin is a dynamic but highly regulated structure. DNA-binding proteins such as transcription factors, epigenetic and chromatin modifiers are responsible for regulating specific gene expression pattern and may result in different phenotypes. To reveal the identity of the proteins associated with the specific region on DNA, chromatin immunoprecipitation (ChIP) is the most widely used technique. ChIP assay followed by next generation sequencing (ChIP-seq) or microarray (ChIP-chip) is often used to study patterns of protein-binding profiles in different cell types and in cancer samples on a genome-wide scale. However, only a limited number of bioinformatics tools are available for ChIP datasets analysis.ResultsWe present ChIPseek, a web-based tool for ChIP data analysis providing summary statistics in graphs and offering several commonly demanded analyses. ChIPseek can provide statistical summary of the dataset including histogram of peak length distribution, histogram of distances to the nearest transcription start site (TSS), and pie chart (or bar chart) of genomic locations for users to have a comprehensive view on the dataset for further analysis. For examining the potential functions of peaks, ChIPseek provides peak annotation, visualization of peak genomic location, motif identification, sequence extraction, and comparison between datasets. Beyond that, ChIPseek also offers users the flexibility to filter peaks and re-analyze the filtered subset of peaks. ChIPseek supports 20 different genome assemblies for 12 model organisms including human, mouse, rat, worm, fly, frog, zebrafish, chicken, yeast, fission yeast, Arabidopsis, and rice. We use demo datasets to demonstrate the usage and intuitive user interface of ChIPseek.ConclusionsChIPseek provides a user-friendly interface for biologists to analyze large-scale ChIP data without requiring any programing skills. All the results and figures produced by ChIPseek can be downloaded for further analysis. The analysis tools built into ChIPseek, especially the ones for selecting and examine a subset of peaks from ChIP data, provides invaluable helps for exploring the high through-put data from either ChIP-seq or ChIP-chip. ChIPseek is freely available at http://chipseek.cgu.edu.tw.

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AbsatractAlong with the constant improvement in high-throughput sequencing technology, an increasing number of transcriptome sequencing projects are carried out in organisms without decoded genome information and even on environmental biological samples. To study the biological functions of novel transcripts, the very first task is to identify their potential functions. We present a web-based annotation tool, FunctionAnnotator, which offers comprehensive annotations, including GO term assignment, enzyme annotation, domain/motif identification and predictions for subcellular localization. To accelerate the annotation process, we have optimized the computation processes and used parallel computing for all annotation steps. Moreover, FunctionAnnotator is designed to be versatile, and it generates a variety of useful outputs for facilitating other analyses. Here, we demonstrate how FunctionAnnotator can be helpful in annotating non-model organisms. We further illustrate that FunctionAnnotator can estimate the taxonomic composition of environmental samples and assist in the identification of novel proteins by combining RNA-Seq data with proteomics technology. In summary, FunctionAnnotator can efficiently annotate transcriptomes and greatly benefits studies focusing on non-model organisms or metatranscriptomes. FunctionAnnotator, a comprehensive annotation web-service tool, is freely available online at: http://fa.cgu.edu.tw/. This new web-based annotator will shed light on field studies involving organisms without a reference genome.