MiRNAkey
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Application data |
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| Created by | Roy Ronen, Ido Gan |
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| Biological application domain(s) | Regulatory RNA |
| Technology | Illumina |
| Created at | Tel Aviv University |
| Maintained? | No |
| Input format(s) | FASTQ, FASTA |
| Output format(s) | TXT |
| Programming language(s) | Java, Perl |
| Operating system(s) | Linux, Mac OS X |
Summary: A software pipeline for the analysis of microRNA Deep Sequencing data
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Contents
Description
Deep Sequencing technologies (Next Generation Sequencing) are increasingly used to obtain a more accurate depiction of miRNA expression profiles in living cells. This type of analysis is a key step towards improving our understanding of the complexity and mode of miRNA regulation. miRNAkey is a software package designed to be used as a base-station for the analysis of miRNA deep sequencing data. Our package implements common steps taken in the analysis of such data, as well as adds unique features, such as data statistics and multiple mapping levels, generating a novel platform for the analysis of miRNA expression. Through the use of a simple graphical interface, the user can determine the analysis steps. The tabular and graphical output contains detailed reports on the sequence reads and provides an accurate picture of the differentially expressed miRNAs in paired samples.
Fearures
- Search and removal (optional) of the adaptor sequence from the 3' end of each read.
- Mapping each read to known miRNA databases (such as the miRBase mature/precursor databases).
- Using the novel Seq-EM algorithm (optional) to evaluate the distribution of the multiply-mapped reads across the observed miRNAs.
- Counting reads mapped to the different known miRNA species in each sample, and converting these counts into the normalized RPKM expression-index to allow comparison across experiments.
- Quantifying differential expression for miRNAs between paired samples (normally case-control pairs), using Chi-Square analysis, thus obtaining p-values for differential expression of miRNAs.
- Generating additional information regarding the input data, such as plots for multiple-mapping levels and post-clipping read lengths.
- Separating the mapped and the non-mapped reads for further, downstream analysis.
- Generating a detailed sumarry report of the analysis.
Links
References
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