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Spliceman was created to apply those findings by predicting the likelihood of splicing mutations based on the distances in positional distributions between RNA sequences. Users enter a DNA sequence as input to the program with an indicated mutation. Spliceman isolates the changed hexamers and computes the [[L1-distance]] between the frequencies of each each hexamer appearing at each location near the splice site to measure the differences in their positional distributions. They distances are then assigned percentile ranks to estimate the likelihood of a splicing mutation.<ref name="spliceman"></ref>
Spliceman was created to apply those findings by predicting the likelihood of splicing mutations based on the distances in positional distributions between RNA sequences. Users enter a DNA sequence as input to the program with an indicated mutation. Spliceman isolates the changed hexamers and computes the [[L1-distance]] between the frequencies of each each hexamer appearing at each location near the splice site to measure the differences in their positional distributions. They distances are then assigned percentile ranks to estimate the likelihood of a splicing mutation.<ref name="spliceman"></ref>


The [http://fairbrother.biomed.brown.edu/spliceman/ Spliceman] tool is available for free online on the website for the Fairbrother Lab. A second version of the tool, [http://fairbrother.biomed.brown.edu/beta/upload Spliceman 2.0], has been developed to accept inputs in a wider array of file formats. This makes the tool more compatible with other tools that handle variants.
The [http://fairbrother.biomed.brown.edu/spliceman/ Spliceman] tool is available for free online on the website for the Fairbrother Lab.
A second version of the tool, [http://fairbrother.biomed.brown.edu/beta/upload Spliceman 2.0], has been developed to accept inputs in a wider array of file formats. This makes the tool more compatible with other tools that handle variants. It can handle many more variations than its precursor due to its ability to accept files of larger sizes. Spliceman 2.0 outputs a report that includes more data and visualization of those data,


==References==
==References==

Revision as of 15:54, 16 June 2016

Spliceman is an online tool created in 2011 for the study of RNA splicing by the Fairbrother Lab at Brown University that predicts the likelihood of mutations around splice sites to impact splicing.[1]

The tool was created to take advantage of findings in 2011 on positional distribution analysis. Each hexamer of DNA base pairs has a positional distribution near splice sites where it was most likely to occur. Point mutations that change one hexamer to another with large changes in positional distributions were shown to be more likely to cause splicing mutations than mutations with small changes to positional distributions.[2]

Spliceman was created to apply those findings by predicting the likelihood of splicing mutations based on the distances in positional distributions between RNA sequences. Users enter a DNA sequence as input to the program with an indicated mutation. Spliceman isolates the changed hexamers and computes the L1-distance between the frequencies of each each hexamer appearing at each location near the splice site to measure the differences in their positional distributions. They distances are then assigned percentile ranks to estimate the likelihood of a splicing mutation.[1]

The Spliceman tool is available for free online on the website for the Fairbrother Lab.

A second version of the tool, Spliceman 2.0, has been developed to accept inputs in a wider array of file formats. This makes the tool more compatible with other tools that handle variants. It can handle many more variations than its precursor due to its ability to accept files of larger sizes. Spliceman 2.0 outputs a report that includes more data and visualization of those data,

References

  1. ^ a b Lim, Kian Huat; Fairbrother, William G. (10 February 2012). "Spliceman—a computational web server that predicts sequence variations in pre-mRNA splicing" (PDF). Bioinformatics. 28 (7): 1031–1032. doi:10.1093/bioinformatics/bts074. PMID 22328782. Retrieved 13 June 2016.
  2. ^ Lim, Kian Huat; Ferraris, Luciana; Filloux, Madeleine E.; Raphael, Benjamin J.; Fairbrother, William G. (5 July 2011). "Using positional distribution to identify splicing elements and predict pre-mRNA processing defects in human genes". Proceedings of the National Academy of Sciences of the United States of America. 108 (27): 11093–11098. doi:10.1073/pnas.1101135108. PMID 21685335. Retrieved 7 June 2016.