Free Program Predicts How Troublesome a Genetic Mutation Is
smoothjazz writes "Researchers describe a new, freely available Web-based program called Spliceman for predicting whether genetic mutations are likely to disrupt the splicing of messenger RNA, potentially leading to disease. From the article: 'Spliceman makes its predictions about mutations by calculating that distance. It has successfully predicted the known effect of many mutations.
The software has genomic information about 11 species: humans, chimpanzees, rhesus monkeys, mice, rats, dogs, cats, chickens, guinea pigs, frogs, and zebra fish.'"
This app is part of the sex education class in Arkansas!
Rephrased, its a static code analysis tool for mRNA
http://en.wikipedia.org/wiki/List_of_tools_for_static_code_analysis
Now taking bets on 10:1 odds that after posting this, some joker adds spliceman to the wiki page. Frankly it probably does belong there.
Yes, I am one of "those guys" who trys to make my perl scripts Perl::Critic compliant, in addition to running them thru perltidy. The closest thing I know of for Ruby is "laser" and I don't know a good reformatting tool for Ruby.
"Science flies us to the moon. Religion flies us into buildings." - Victor Stenger
This sounds like a great tool for predicting the abilities of new recruits.
Back in the real world, the 'bio age' will be another incentive to get the hell off this planet before someone wipes us out with an engineered disease. I'm sure the 'humans are a cancer' Greenists are just salivating at the thought.
Free Program Predicts How Troublesome a Genetic Mutation Is
No it doesn't.
This is yet another case of how stupid PR does damage to otherwise good science. The original paper (not the PR release) describes a statistical model. The model tells you how likely it is for a mutation to affect splicing. According to ROC curve on figure 4 it isn't nearly as selective or sensitive as you need it to be for any clinical application. It is however a great research tool. The PR article makes another false assumption, by stating that mutations affecting the splicing of an exon invariably cause 'trouble'. In fact it is well established that there is a significant variability in exon usage in perfectly healthy humans (citations below).
1. Kwan, Tony, David Benovoy, Christel Dias, Scott Gurd, David Serre, Harry Zuzan, Tyson A. Clark, et al. “Heritability of Alternative Splicing in the Human Genome.” Genome Res. 17, no. 8 (August 1, 2007): 1210–1218.
2. Zhang, Wei, Shiwei Duan, Emily O. Kistner, Wasim K. Bleibel, R. Stephanie Huang, Tyson A. Clark, Tina X. Chen, et al. “Evaluation of Genetic Variation Contributing to Differences in Gene Expression Between Populations.” The American Journal of Human Genetics 82, no. 3 (March 3, 2008): 631–640.
This is an interesting program, but it's hardly the first (coming from a grad student in Bioinformatics studying variation in the cancer genome). There are a large number of programs attempting to determine the impact of variation in the genome. We use these in our work with the exome (enrichment and sequencing of just the known coding elements in the human genome). A much larger challenge is finding true positive base and indel variation from next-generation sequencing, where alignment and sequencing artifacts lead to many false positive signals.
Here are two of the most popular:
SiFT: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC168916/
PolyPhen: http://www.ncbi.nlm.nih.gov/pubmed/12202775?dopt=Abstract
-Lee
Humans aren't very good at the problem of RNA splice site finding, unfortunately. Like Reversi/Othello, it involves detecting a large number of subtle changes in closely-related states that have dramatic downstream effects. The game would consist primarily of looking at a bunch of roughly hill-shaped graphs and trying to determine which ones cross certain thresholds or most closely resemble certain other curves. Computationally those are pretty manageable tasks.
Bio questions? Ask me to start a Q&A journal. Computer analogies available for most topics!
It's not really a simulation; it just tells you if a given sequence appears to resemble a splice site, and the probability that the single-nucleotide mutation specified by the user will alter that site's tendency to splice. Not a new accomplishment in biology by any means; the headline is sadly and totally overblown.
Bio questions? Ask me to start a Q&A journal. Computer analogies available for most topics!