-
Notifications
You must be signed in to change notification settings - Fork 8
RNAcode - Detecting protein coding genes in multiple sequence alignment
License
ViennaRNA/RNAcode
Folders and files
Name | Name | Last commit message | Last commit date | |
---|---|---|---|---|
Repository files navigation
RNAcode -- Analyze the protein coding potential in multiple sequence alignments 0. About RNAcode ================ RNAcode predicts protein coding regions in an alignment of homologous nucleotide sequences. The prediction is based on evolutionary signatures typical for protein genese, i.e. the presence of synonyomous/conservative nucleotide mutations, conservation of the reading frame and absence of stop codons. RNAcode does not rely on any species specific sequence characteristics whatsoever and does not use any machine learning techniques. The only input required for RNAcode is a multiple sequence alignment either in MAF or Clustal W format. RNAcode reports local regions of unusual high coding potential together with an associated p-value. 1. Installation =============== You can compile and install RNAcode like this: # ./configure # make # make install (as root) See INSTALL for details and more advanced installation options. 2. Usage ======== 2.1 Synopsis ------------ Analyze alignment (Clustal W or MAF form) with standard options and print detailed results page: # RNAcode data.aln Analyze alignment and show best non-overlapping hits below a p-value cutoff of 0.01 in gtf format: # RNAcode --outfile results.gtf --gtf --best-only --cutoff 0.01 Create color annotations for high scoring coding segments: # RNAcode --eps data.aln 2.2 Input alignment ------------------- The input alignment needs to be formatted in ClustalW format or MAF format (http://genome.ucsc.edu/FAQ/FAQformat#format5). The latter format allows to include genomic coordinates which can be used to produce annotation files. Important: RNAcode uses the first sequence as reference sequence, i.e. all results and reported coding regions apply to this reference sequence. Currently the alignments has to contain at least 3 sequences. Gaps have to be given as dash ('-'). Unspecified letters given as 'N' are allowed and treated neurally during all calculations. No difference is made between uppercase or lowercase input, i.e. 'softly'-repeat masked sequences which use lowercase letters for masked regions are treated the same way as unmasked sequences. 2.3. Command line ----------------- RNAcode is invoked as follows: # RNAcode [OPTIONS] alignment.aln alignment is the alignment file and OPTIONS is one of the follwing command-line options either given in one-letter form with a single dash or as long option with double dash: --outfile -o (default: stdout) File to which the output is written. Defaults to standard output. --cutoff -p (default: 1.0) Show only regions that have a p-value below the given number. By default all hits are shown. --num-samples -n (default: 100) Number of random alignments that are sampled to calculate the p-value. RNAcode estimates the significance of a coding prediction by sampling a given number of random alignments. Default is 100 which gives reasonably stable p-values that are useful for assessing the relevance of a prediction. --stop-early -s Setting this option stops the sampling process as soon as it is clear that the best hit will not fall below the given p-value cutoff. For example, assume a p-value cutoff of 0.05 (see --cutoff) and a sample size of 1000 is given (see --num-samples). As soon as 50 random samples score better than the original alignment, the process is stopped and all hits in the original alignment are reported as p>0.05 (or by convention as 1.0 in gtf and tabular output). --best-region -r Show only best non-overlapping hits By default all positive scoring segments are shown in the output if they fall below the given p-value cutoff. If two hits overlap (different frame or different strand) and --best-region is given only the hit with the highest score is shown. Strong coding regions often lead to statistically significant signals also in other frames. These hits are suppressed by this option and only the correct reading frame is reported. --best-only -b Show only best hit This options shows only the one single best hit for each alignment. --pars -c Scoring parameters as comma separated string: "DELTA,OMEGA,omega,stop_penalty" See the appendix of the Paper for an explanation for the meaning of these parameters. Default: "-10.0,-4.0,-2.0,-8.0" --gtf -g --tabular -t Changes the default output to two different machine readable formats (see next section). --eps -e Create colored plots in EPS format. The generated plots are resolution independent vector graphics that can be included in any graphics software. For each high scoring segment below a given cutoff (see --eps-cutoff) a file named hss-N.eps is created (N is the running number of the high scoring segment). See documents/color-legend.pdf for an explanation of the color scheme. --eps-cutoff -i Create plots only for high scoring segments with p better than this cutoff (default: 0.05) --eps-dir -d Directory to save EPS files in. Default: "eps" 2.4. Output format ------------------ In the default output each prediction is reported on one line by 10 fields. 1. HSS id Unique running number for each high scoring segment predicted in one RNAcode call 2. Frame: The reading frame phasing relative to the starting nucleotide position in the reference sequence. +1 means that the first nucleotide in the reference sequence is in the same frame as the predicted coding region. Negative frames indicate that the predicted regions are on the reverse complement strand. 3. Length: The length of the predicted region in amino acids 4. From: The position of the first/last amino acid in the translated 5. To: nucleotide sequence of the reference sequence starting with 1. 6. Name The name of the reference sequence as given in the input alignment. 7. Start The nucleotide position in the reference sequence of the 8. End predicted coding region. If no genomic coordinates are given (if you provide a CLUSTAL W as input) the first nucleotide position in the references sequence is set to 1, otherwise the positions are the 1-based genomic coordinates as given in the input MAF file. 9. Score The coding potential score. High scores indicate high coding potential. 10. P The p-value associated with the score. This is the probability that a random alignment with same properties contains an equally good or better hit. If --tabular is given, the output is printed as tab-delimited list without header or any other output. With --gtf the output is formated as GTF genome annotation file. 4. Citing RNAcode ================= RNAcode: robust discrimination of coding and noncoding regions in comparative sequence data Washietl S, Findeiss S, Muller S, Kalkhof S, von Bergen M, Hofacker IL, Stadler PF, Goldman N RNA (2011), in revision 3. Contact ========== Stefan Washietl <wash@mit.edu>
About
RNAcode - Detecting protein coding genes in multiple sequence alignment
Resources
License
Stars
Watchers
Forks
Packages 0
No packages published