Chipster
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Application data |
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| Created by | Kallio A, Hupponen T, Gentile M, Tuimala J, Klemelä P, Scheinin I, Mattila K, Saren A-M, Naktinis R, Korpelainen E |
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| Biological application domain(s) | ChIP-seq, RNA-Seq, Immunoprecipitation experiment, DNA methylation |
| Principal bioinformatics method(s) | Sequencing quality control, Sequence trimming, Read mapping, Peak calling, Sequence motif recognition, Differential expression analysis, Pathway or network analysis, Methylation analysis, Genome visualisation |
| Created at | CSC - IT Center for Science, Finland |
| Maintained? | Yes |
| Input format(s) | FASTQ, SAM, BAM, BED, GTF |
| Output format(s) | FASTQ, SAM, BAM, BED, GTF |
| Programming language(s) | Java, R |
| Licence | GPLv3 |
| Operating system(s) | platform-independent |
Summary: User-friendly NGS data analysis software with built-in genome browser and workflow functionality. Chipster includes tools for ChIP-seq, RNA-seq, miRNA-seq and MeDIP-seq analysis, and functionality for exome-seq and CGH-seq will soon be added.
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Description
The open source Chipster software provides an intuitive graphical user interface to NGS and microarray data analysis tools, interactive visualizations and workflow functionality. Version 2.0 contains analysis and visualization tools for ChIP-seq, RNA-seq, miRNA-seq and methyl-seq data. It is easy to integrate new tools to Chipster, please see our technical manual for details.
Users can perform their whole data analysis in Chipster from quality control, preprocessing, and alignment to normalization, statistical analysis and downstream applications such as pathway enrichment and motif discovery. Popular packages such as FastQC, FASTX, SAMtools, BEDTools, Bowtie, BWA and TopHat are included, and care has been taken to serve them in a biologist-friendly manner. Analysis pipelines can easily be saved as automatic, reusable workflows, which can be shared with other users.
The ChIP-seq analysis tools enable users to detect peaks with MACS, filter them based on p-value, number of reads etc., and scan them for common sequence motifs to be matched against the JASPAR database. Users can also retrieve the nearby genes, filter them based on several criteria, and perform pathway analysis.
Data from miRNA-seq experiments can be normalized and analyzed for differential expression through integration of the edgeR Bioconductor package. Target genes for miRNA:s can be retrieved from several databases and analyzed for pathway enrichment. For RNA-seq data users can also opt for the integrated Cufflinks package.
Chipster’s built-in genome browser allows seamless visualization of reads and results in their genomic context using Ensembl annotations. Users can zoom in to nucleotide level, highlight SNP:s and view the automatically calculated coverage. Cross-talk between the genome browser and BED files allows users to quickly inspect genomic regions by simply clicking on the data row of interest.
Technically Chipster is a Java-based client-server system. It is open source, and new tools can easily be added using a simple mark-up language. We are currently working with the Hadoop MapReduce framework so that large jobs can be run in the cloud. Also, a virtual machine distribution of Chipster is being set up to make the server installation even easier. Taken together, Chipster provides an easy way to serve NGS data analysis tools in a biologist-friendly manner.
Chipster team participates in the SeqAhead COST action BM1006 "Next Generation Sequencing Data Analysis Network". The complete list of tools developed by the SeqAhead network can be found here.
Links
- Chipster Homepage [ edit link ]
- Chipster Source code [ edit link ]
- Chipster Manual [ edit link ]
- Chipster Publication full text [ edit link ]
References
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