This is a free web-based application for the processing of high-throughput RNA-Seq data (wapRNA) from next generation sequencing (NGS) platforms, such as Genome Analyzer of Illumina Inc. (Solexa) and SOLiD of Applied Biosystems (SOLiD). wapRNA provides an integrated tool for RNA sequence, refers to the use of High-throughput sequencing technologies to sequence cDNAs in order to get information about a sample's RNA content. Due to the deep coverage and base level resolution provided by next-generation sequencing instruments, wapRNA provides researchers with efficient ways to measure RNA sequence experimentally, allowing them to get information such as how different alleles of a gene are expressed, detect post-transcriptional mutations or identifying gene fusions, annotate the known miRNAs or predict the news and so on.
However, each RNA-Seq experiment produces up to 20~30Gb sequence data, that's a huge challenge for the corresponding bioinformatics analysis. The software has not been able to keep up with advances in the instrumentation--a particular problem for small research groups that can't spare resources for software development or informatics support. There are a number of open source analysis tools available for RNA-Seq, such as CalTech's Enhanced Read Analysis of Gene Expression, or ERANGE, but using these tools is tricky for researchers who are not comfortable with a UNIX machine. Thus, we developed this web-based automatic and integrated program package to process the RNA-seq data include RNA and miRNA, named wapRNA.
The significant benefit of wapRNA is easy-to-use for users, and in order to avoid the network bottleneck, we provide a local executable package for users to install on local machines and users can download the whole package from the download page.
wapRNA is available for both RNA and miRNA sequences. Features
for researchers include:
♦ Web-based application and easy to use
♦ Support both Solid and Solexa NGS reads
♦ Short-Reads mapping and results report
♦ Sequence annotation (based on ENSEMBL, TIGR, and BROAD et al)
♦ Data mining on sequence alignments and text annotations
♦ Built-in workflows for common discovery challenges across tools (GO and KEGG tools for functional analysis)