arrayQCplot: software for checking the quality of microarray data

SUMMARY: arrayQCplot is a software for the exploratory analysis of microarray data. This software focuses on quality control and generates newly developed plots for quality and reproducibility checks. It is developed using R and provides a user-friendly graphical interface for graphics and statistical analysis. Therefore, novice users will find arrayQCplot as an easy-to-use software for checking the quality of their data by a simple mouse click. AVAILABILITY: arrayQCplot software is available from Bioconductor at http://www.bioconductor.org. A more detailed manual is available at http://bibs.snu.ac.kr/software/arrayQCplot CONTACT: tspark@stats.snu.ac.kr.     

下一代测序中ChIP-seq数据的处理与分析

将染色质免疫共沉淀技术(ChIP)与下一代高通量测序技术相结合的染色质免疫共沉淀测序(ChIP-seq),已成为功能基因组学、特别是基因表达调控领域研究的关键技术。ChIP-seq实验带来的海量数据向生物信息学研究人员提出了新的挑战。由于此领域数据处理技术的发展大大滞后于实验技术进步,有必要系统地介绍和回顾ChIP-seq数据处理的各个方面,以便更多研究人员进入此领域设计或改进相应的算法。文章结合实例详细介绍了ChIP-seq数据整个流程,并重点讨论了其中的主要问题和关键环节,为这一研究领域的科研人员提供一个快速而深入的认识。     

GBSA: a comprehensive software for analysing whole genome bisulfite sequencing data

High-throughput sequencing is increasingly being used in combination with bisulfite (BS) assays to study DNA methylation at nucleotide resolution. Although several programmes provide genome-wide alignment of BS-treated reads, the resulting information is not readily interpretable and often requires further bioinformatic steps for meaningful analysis. Current post-alignment BS-sequencing programmes are generally focused on the gene-specific level, a restrictive feature when analysis in the non-coding regions, such as enhancers and intergenic microRNAs, is required. Here, we present Genome Bisulfite Sequencing Analyser (GBSA—http://ctrad-csi.nus.edu.sg/gbsa), a free open-source software capable of analysing whole-genome bisulfite sequencing data with either a gene-centric or gene-independent focus. Through analysis of the largest published data sets to date, we demonstrate GBSA’s features in providing sequencing quality assessment, methylation scoring, functional data management and visualization of genomic methylation at nucleotide resolution. Additionally, we show that GBSA’s output can be easily integrated with other high-throughput sequencing data, such as RNA-Seq or ChIP-seq, to elucidate the role of methylated intergenic regions in gene regulation. In essence, GBSA allows an investigator to explore not only known loci but also all the genomic regions, for which methylation studies could lead to the discovery of new regulatory mechanisms.     

Assignment validation software suite for the evaluation and presentation of protein resonance assignment data

We present a set of utilities and graphical user interface (GUI) tools for evaluating the quality of protein resonance assignments. The Assignment Validation Software (AVS) suite, together with new GUI features in the AutoAssign software package, provides a set of reports and graphs for validating protein resonance assignment data before its use in structure analysis and/or submission to the BioMagResBank (BMRB). Input includes a listing of resonance assignments and a summary of sequential connectivity data (i.e. triple resonance, NOE, or other data) used in deriving the assignments. These tools are useful for evaluating the accuracy of protein resonance assignments determined by either automated or manual methods.     

ChIPpeakAnno: a Bioconductor package to annotate ChIP-seq and ChIP-chip data

Background  

Chromatin immunoprecipitation (ChIP) followed by high-throughput sequencing (ChIP-seq) or ChIP followed by genome tiling array analysis (ChIP-chip) have become standard technologies for genome-wide identification of DNA-binding protein target sites. A number of algorithms have been developed in parallel that allow identification of binding sites from ChIP-seq or ChIP-chip datasets and subsequent visualization in the University of California Santa Cruz (UCSC) Genome Browser as custom annotation tracks. However, summarizing these tracks can be a daunting task, particularly if there are a large number of binding sites or the binding sites are distributed widely across the genome.     

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.