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GenomeAtlas 3.0.ws2

DNA structural atlases for complete microbial Genomes


WSDL GenomeAtlas/GenomeAtlas_3_0_ws2.wsdl
Schema definitions ws_genomeatlas_3_0_ws2.xsd
../common/ws_common_1_0b.xsd

We recommend that the first time users should load the WSDL file above to SoapUI and investigate the Web Service operations in that environment. SoapUI is a desktop application for inspecting, invoking, developing and functional/load/compliance testing of Web Services over HTTP. It can be downloaded free of charge from http://www.soapui.org/.

Examples of client side scripts using the service

FilenameTypeCompatibilityAuthorDescription
output4.txt (459.0 KB)
querygenomes.pl (2.8 KB) Perl Genome Atlas 3.0.ws2 Peter Fischer Hallin
Query Genome Atlas database 3.0 (by project id, organism, accession etc.)
prodigal.pl (3.0 KB) Perl Genome Atlas 3.0 ws2 Peter Fischer Hallin
Prodidgal gene prediction client
test.pl (7.6 KB) Perl Genome Atlas 3.0 ws2 Peter Fischer Hallin
Standalone test script - all prerequisites embedded
curvature.out (219.5 KB)
getseq.pl (973 B) Perl Genome Atlas 3.0.ws2 Peter Fischer Hallin
Download genome sequence of a genbank accession no.
output2.txt (2.0 KB)
trnascan.pl (2.4 KB) Perl Genome Atlas 3.0 ws2 Peter Fischer Hallin
run tRNAscan SE on input fasta
getprot.pl (964 B) Perl Genome Atlas 3.0.ws2 Peter Fischer Hallin
Download translation of annotated genes
DNAproperties.pl (1.4 KB) Perl Genome Atlas 3.0.ws2 Peter Fischer Hallin
Calculate DNA properties
xml-compile.pl (3.2 KB) Perl NA Peter Fischer Hallin
Helper scripts used to initiate XML::Compile's proxys (WSDL+XSD)
output3.txt (300 B)
getorfs.pl (957 B) Perl Genome Atlas 3.0.ws2 Peter Fischer Hallin
Download annotated ORFs of genome
output1.txt (4.3 KB)
fasta.inc.pl (877 B) Perl NA Peter Fischer Hallin
Helper script to parse input fasta file

Documentation

 
  This Web Service accesses the database records and various tools of the 
  GenomeAtlas database v3. The records maintained by this database are synchronized regularly
  with the Entrez Genome Project (http://www.ncbi.nlm.nih.gov/genomes/lproks.cgi?view=1) 
  
  #
  # DATABASE LOOK-UP FUNCTIONS 
  #
1.  getSeq
    Get one or more genomic sequences from the Genome Atlas database (update regularly against 
    Entrez Microbial Genomes), providing the genbank accession number.
    Input: 
           * 'genbank'    : A genbank accession number
    Output:
           * 'sequencedata'
       * 'sequence' [array]
               * 'id'     : id sequence  
         * 'comment': comment of sequence
               * 'seq'    : The DNA sequence of the genome
2.  getProt
    Get the protein sequences encoded by annotated coding regions of GenBank record
    Input:
           * 'genbank'    : A genbank accession number
    Output:
           * 'sequencedata'
       * 'sequence' [array]
               * 'id'     : id sequence  
         * 'comment': comment of sequence
               * 'seq'    : The translations of the predicted protein coding genes
    
3.  getOrfs
    Get the nucleotide sequences of annotated coding regions of GenBank record
    Input:
           * 'accession': Ond or more GenBank accession numbers.
    Output:
           * 'contig' 
            * 'id': accession number as provided in input  
            * 'sequencedata': An array of sequencedata objects
             * 'id'  : The identifier of the sequence ( output from GenBank record converter )
             * 'seq' : Protein coding DNA sequence
    
 4. queryGenomes
    Query records of the GenomeAtlas database 
    Input: 
          * 'search' : Records can be search by various optional fields (AND separated) All fields
                 except 'pid' are surrounded by wildcards.
           * 'kingdom'     : bacteria / archaea
           * 'phyla'       : Phyla
           * 'pid'         : Project id
           * 'organism'    : Organism name
           * 'genbank'     : Genbank accession number
           * 'refseq'      : RefSeq accession number
           * 'segment'     : Segment / replicon name (e.g. 'GENOME[PID]', 'Chromosome"', 'pVir' ...)
           * 'hideMerged'  : yes / no: Hide merged segments (GENOME[PID])

  Output: An array of entries containing:
   * 'descriptions'  : A genome atlas database record
      * 'entry'
          * 'field'       : The name of the field (e.g. ATCONTENT, NGENES)
    * 'description' : A descriptive text for the field
   * 'entry'  : A genome atlas database record
           * 'kingdom'     : bacteria / archaea
           * 'phyla'       : Phyla
           * 'pid'         : Project id
           * 'organism'    : Organism name
           * 'genbank'     : Genbank accession number
           * 'refseq'      : RefSeq accession number
           * 'segment'     : Segment / replicon name (e.g. 'GENOME[PID]', 'Chromosome"', 'pVir' ...)
     * 'properties'  : Returned the calculated gemomic properties of the segment
    * 'ATCONTENT'
    * 'NGENES'
    * 'LENGTH'
    * 'BPPRGENE'
    * 'CODING_FRACTION'
    * 'GEOMETRY'
    * 'RNAMMER_TSU_COUNT'
    * 'RNAMMER_SSU_COUNT'
    * 'RNAMMER_LSU_COUNT'
    * 'GLO_DIR_REPEAT'
    * 'GLO_INV_REPEAT'
    * 'SR_PERCENT'
    * 'ANN_TRNA_COUNT'
    * 'TRNA_SCAN_COUNT'
    * 'TRUE_PROTEINS'
    * 'TRUE_PROT_RATIO'
    * '60_ORIGIN'
    * '60_TERMINUS'
    * 'ADNACC'
    * 'CURVATURE_AVG'
    * 'ELHASSAN_AVG'
    * 'OLSON_AVG'
    * 'ORNSTEIN_AVG'
    * 'RRRECIEVER_COUNT'
    * 'HISKA_1_COUNT'
    * 'HISKA_2_COUNT'
    * 'HISKA_3_COUNT'
    * 'HISKA_COUNT'
    * 'HWE_HK_COUNT'
    * 'LOC_DIR_REPEAT'
    * 'LOC_EVR_REPEAT'
    * 'LOC_INV_REPEAT'
    * 'LOC_MIR_REPEAT'

5.  getFeatures
    Get details for all annotated features of a single genbank record
    Input: 
            * 'accession' : Genbank accession number
            * 'features'  : Comma separated list of features to be returned
                            (e.g. all or cds,rrna,trna)
            * 'keys'      : Comma separated list of keys to be returned
                            (e.g. all or locus_tag,gene,translation)
              
    Output: 'features': An array of 'feature' elements, containing:
            * 'type'  : feature type, e.g. CDS, rRNA, tRNA
            * 'begin' : lower boundary of annotation 
            * 'end'   : upper boundary of annotation 
            * 'end'   : upper boundary of annotation
            * 'dir'   : Annotation direction + or /
            * 'label' : Acquired from 'gene' annotation
            * 'featurekey' : An array of additional annotation keys provided in the Genbank record
             * 'Key'       : the annotation key, e.g. 'product'  
             * 'Value'     : the annotation value, e.g. '16S ribosomal RNA'  

            Please be aware, that begin and end refers to the boundaries of the annotation,
            meaning that if multiple concatenations/junctions are present in the annotation, begin
            end and will only refer to the smallest and largest of those numbers. To get a detailed map
            of the junction, this is found in the 'featurekey' element, having attribute key=coordinates.

#
# TOOLS      
#

6.  DNApropertyRun
    Calculates structural and physical properties of the DNA molecule. These properties
    are used in the DNA Atlas representation on the Genome Atlas web pages. Properties include
    Intrinsic Curvature, Stacking energy, position preference, various repeats etc. (please see
    below for documentation). Use operation 'pollQueue' to poll the status of the job.
    
    Input: 
            * 'method'    : Calculation method, specifying which result are to be generated,
                            e.g. 'Intrinsic Curvature' (see documentation below)
            * 'sequence'   
             * 'id'       : Sequence identifier
             * 'seq'      : DNA sequence

                           The following DNA properties can be calculated:

                           Intrinsic Curvature
                             DNA curvature is calculated using the CURVATURE programme (Bolshoy et al. 1991, Shpigelman 
                             et al. 1993). The term curved DNA here refers to DNA that is intrinsically curved 
                             in solution and can be readily characterised by anomalous migration in acrylamide 
                             gels. There are different models for curved DNA (Sinden et al. 1998), although the 
                             predictions for curvature fragments largerthan a few hundred bp is essentially the 
                             same (Haran et al. 1994). The scale is in arbitrary "Curvature units", which ranges 
                             from 0 (e.g. no curvature) to 1.0, which is the curvature of DNA when wrapped around 
                             the nucleosome. The scale used for this atlas ranges 3 standard deviations around 
                             the mean. 

                              * R.R. Sinden and C.E. Pearson and V.N. Potaman and D.W. Ussery DNA: Structure and 
                                Function (1998) 5A:1-141 

                              * E.S. Shpigelman and E.N. Trifonov and A. Bolshoy CURVATURE: Software for the Analysis 
                                of Curved DNA. (1993) 9:435-444 

                              * T.E. Haran and J.D. Kahn and D.M. Crothers Sequences elements responsible for 
                                DNA curvature (1994) 225:729-738 

                              * A. Bolshoy and P. McNamara and R.E. Harrington and E.N. Trifonov Curved DNA Without 
                                A-A - Experimental Estimation of All 16 DNA Wedge Angles (1991) 88:2312-2316 

                            Position Preference
                             - a trinucleotide model based on the preferential location 
                             of sequences within nucleosomal core sequences (Satchwell et al. 1986). We use the 
                             magnitude (e.g.absolute values) of the trinucleotide numbers as a measure of DNA 
                             flexibility (Baldi et al. 1996). The trinucleotide values range from essentially 
                             zero (0.003, presumably more flexible), to 0.28 (considered rigid). Since very few 
                             of the trinucleotide have values close to zero (e.g. little preference for nucleosome 
                             positioning), this measureis considered most sensitive towards the low ("flexibity") 
 

                              * S.C. Satchwell and H.R. Drew and A.A. Travers Sequence periodicities in chicken 
                                nucleosome core DNA (1986) 191:659-675 

                              * P. Baldi and S. Brunak and Y. Chauvin and A. Krogh Naturally occurring nucleosome 
                                positioning signals in human exons and introns. (1996) 263:503-510 

                            Stacking Energy
                             Base-stacking energies are from the dinucleotide values provided by (Ornstein et 
                             al. 1978). The scale is in kcal/mol, and the dinucleotide values range from -3.82 
                             kcal/mol (will melt easily) up to a maximum value of -14.59 kcal/mol (which would 
                             require more energy to destack or melt the helix). (All 10 values are listed in the 
                             table below.) A positive peak in base-stacking (i.e., numbers closer to 0) reflectsregions 
                             of the helix which would de-stack or melt more readily. Conversely, minima (larger 
                             negative numbers) in this plot would represent more stable regions of the chromosome. 
                             
                             Dinucleotide melting energies in kcal/mols:
                            
                               (GC).(GC)  -14.59
                               (AC).(GT)  -10.51
                               (TC).(GA)   -9.81
                               (CG).(CG)   -9.61
                               (GG).(CC)   -8.26
                               (AT).(AT)   -6.57
                               (TG).(CA)   -6.57
                               (AG).(CT)   -6.78
                               (AA).(TT)   -5.37
                               (TA).(TA)   -3.82
 

                              * R.L. Ornstein and R. Rein and D.L. Breen and R.D. MacElroy An optimized potential 
                                function for the calculation of nucleic acid interaction energies. I. Base stacking 
                                (1978) 17:2341-2360
                 
                            Protein Deformability
                             "Protein Induced Deformability" dinucleotide values are from protein induced deformation 
                             of DNA helices as determined by examination of more than a hundred cr et et al. 1997al 
                             structures of DNA/protein complexes (Olson et al. 1998). The dinucleotide values 
                             range from 2.1 (the least deformable dinucleotide), to 12.1 (i.e., the dinucleotide 
                             step (CpG), which is often deformed by proteins). Thus, on this scale, a larger value 
                             reflects a more deformable sequence whilst a smaller value indicates a region where 
                             the DNA helix is less likely to be changed dramatically by proteins. The average 
                             protein deformability value in the entire E. coli K-12 genome is 5.12. 

                              * Goffeau et al. The Yeast Genome Directory (1997) 387 (supplement):5-105 

                              * W.K. Olson and A.A. Gorin and X.J. Lu and L.M. Hock and V.B. Zhurkin DNA sequence-dependent 
                                deformability deduced from protein-DNA crystal complexes. (1998) 95:11163-11168 

                            Propeller twist
                             We use propeller twist as a measure of helix rigidity, since the propeller twist 
                             angles have been shown to be inversely related to rigidity of the DNA helix in crystals 
                             (el Hassan et al. 1996). Thus, a region with high propeller twist would 
                             mean the helix is quite rigid in this area, and similarly regions that are quite 
                             flexible would have a low propeller twist. Propeller twist values were obtained from 
                             cr et et al. 1997allographic data (el et al. 1996), with the exception of the TA 
                             step, which was taken from a theoretical estimate (Gorin et al. 1995). Plots using 
                             other sets of propeller twist dinucleotide values were very similar (data not shown). 
                             The average propeller twist value in the entire E. coli K-12 genome is -12.63 degrees. 
 
                              * Goffeau et al. The Yeast Genome Directory (1997) 387 (supplement):5-105 

                              * M.A. el Hassan and C.R. Calladine Propeller-twisting of base-pairs and the conformational 
                                mobility of dinucleotide steps in DNA. (1996) 259:95-103 

                              * A.A. Gorin and V.B. Zhurkin and W.K. Olson B-DNA twisting correlates with base-pair 
                                morphology. (1995) 247:34-48 

                            DNase I Sensitivity
                             DNase I values are based on experimentally determined trinucleotide values (Brukner 
                             et al. 1995, Brukner et al. 1995). These values are reflectiveof the anisotropic 
                             flexibility or "bendability" of a particular DNAsequence. The trinucleotide values 
                             range from -0.280 (rigid) to +0.194 (very "bendable" towards the major groove). Smoothing 
                             over a large regions, (which is necessary for viewing entire genomes) tends to smooth 
                             out differences in bendability. The average DNase I ("bendability") value in the 
 
                              * I. Brukner and R. Sanchez and D. Suck and S. Pongor Sequence-dependent bending 
                                propensity of DNA as revealed by DNase I: parameters for trinucleotides. (1995) 14:1812-1818 
                                

                              * I. Brukner and R. Sanchez and D. Suck and S. Pongor Trinucleotide models for DNA 
                                bending propensity: comparison of models based on DNaseI digestion and nucleosome 
                                packaging data. (1995) 13:309-317

                            Palindromic hexamers
                             For a given sequence, any palindrome of 6 nt (e.g., AAATTT) is given a value of 1, 
                             while all bases not included inpalindromic hexamers are given a value of 0 (van et 
                             al. 2003). 

                              * van Noort V, Worning P, Ussery DW, Rosche WA, Sinden RR Strand misalignments lead 
                                to quasipalindrome correction (2003) 19:365-9 

                            G Content
                             The "G Content" of a given sequence is merely the fraction of G's in a given sequence 
                             (Jensen et al. 1999). It can range from 0(no G's), to 1 (all G's). For a sequence 
                             that is 50% AT content, one would expect roughly 25% G's. 

                              * L. J. Jensen and C. Friis and D.W. Ussery Three views of complete chromosomes 
                                (1999) 150:773-777

                            A Content
                             The "A Content" of a given sequence is merely the fraction of A's in a given sequence 
                             (Jensen et al. 1999). It can range from 0(no A's), to 1 (all A's). For a sequence 
                             that is 50% AT content, one would expect roughly 25% A's. 

                              * L. J. Jensen and C. Friis and D.W. Ussery Three views of complete chromosomes 
                                (1999) 150:773-777

                            T Content
                             The "T Content" of a given sequence is merely the fraction of T's in a given sequence 
                             (Jensen et al. 1999). It can range from 0(no T's), to 1 (all T's). For a sequence 
                             that is 50% AT content, one would expect roughly 25% T's. 

                              * L. J. Jensen and C. Friis and D.W. Ussery Three views of complete chromosomes 
                                (1999) 150:773-777 

                            C Content
                             The "C Content" of a given sequence is merely the fraction of C's in a given sequence 
                             (Jensen et al. 1999). It can range from 0(no C's), to 1 (all C's). For a sequence 
                             that is 50% AT content, one would expect roughly 25% C's. 

                              * L. J. Jensen and C. Friis and D.W. Ussery Three views of complete chromosomes 
                                (1999) 150:773-777 

                            GC Skew
                             For many genomes there is a strand bias, such that one strand tends to have more 
                             G's, whilst the other strand has more C's.This GC-skew bias can be measured the number 
                             of G's minus the number of C's over a fixed length (e.g. 10,000 bp) of DNA(Jensen 
                             et al. 1999). The values can range from +1 (all G's on the examined sequence, with 
                             all C's on the other strand), to -1(the reverse case - all C's on the examined sequence, 
                             and all G's on the other strand). There is a correlation with GC-skewand the replication 
                             leading and lagging strands. 

                              * L. J. Jensen and C. Friis and D.W. Ussery Three views of complete chromosomes 
                                (1999) 150:773-777 

                            Percent AT
                             The percent AT is a running average of the AT content, over a given window size. 
                             Typically for a bacterial genomes of about5 Mbp, the window size is 10,000 bp. The 
                             Percent AT can range from 0 (no AT content) to 1 (100% AT). The Percent AT iscorrelated 
                             with other DNA structural features, such that AT rich regions are often more readily 
                             melted, tend to be lessflexible and more rigid, although they can also be readily 
                             compacted chromatin proteins (Pedersen et al. 2000). 

                              * A.G. Pedersen and L.J. Jensen and H.H. St\aerfeldt and S. Brunak and D.W. Ussery 
                                A DNA structural atlas of \textitE. coli (2000) 299:907-930 

                            AT Skew
                             For some genomes there is also an AT strand bias, such that one strand tends to have 
                             more A's, whilst the other strand hasmore T's. This AT-skew bias is measured as the 
                             number of A's minus the number of T's over a fixed length (e.g. 10,000 bp) ofDNA 
                             (Jensen et al. 1999). The values can range from +1 (all A's on the examined sequence, 
                             with all T's on the other strand), to-1 (the reverse case - all T's on the examined 
                             sequence, and all A's on the other strand). For some genomes, there is acorrelation 
                             with AT-skew and the replication leading and lagging strands. 

                              * L. J. Jensen and C. Friis and D.W. Ussery Three views of complete chromosomes 
                                (1999) 150:773-777 

                            Global Direct Repeats
                             Global Direct repeats are found by taking the first 100 bp of sequence, and
                             looking for the best match within the whole segment, on the same strand, in the
                             same direction [5' to 3'] (Skovgaard et al. 2002). Values are binned into 10
                             values, and represent the lower end of the best match, and range from 0 (10% or
                             less match) to 9 (at least 90 out of the 100 nucleotides match perfectly).


                            Global Inverted Repeats
                             Global Direct repeats are found by taking the first 100 bp of sequence, and
                             looking for the best match within the whole segment, on the opposite strand, in
                             the same direction  [5' to 3'] (Skovgaard et al. 2002). Values are binned into
                             10 values, and represent the lower end of the best match and range from 0 (10%
                             or less match) to 9 (at least 90 out of the 100 nucleotides match perfectly).

                             * M. Skovgaard and L.J. Jensen and C. Friis and H.H. Staerfeldt,and P. Worning
                             and S. Brunak The Atlas Visualization of Genomewide Information (2002) 33:49-63

                            Direct Repeats
                             Local Direct repeats are found by taking a 100 bp sequence window, and looking for 
                             the best match of a 30 bp piece withinthat window, on the same strand, in the same 
                             direction (Jensen et al. 1999). Values can range from 0 (no match at all) to 1(one 
                             or more perfect match within the window). 

                              * L. J. Jensen and C. Friis and D.W. Ussery Three views of complete chromosomes 
                                (1999) 150:773-777 

                            Everted Repeats
                             Local Everted repeats are found by taking a 100 bp sequence window, and looking for 
                             the best match of a 30 bp piece withinthat window, on the opposite strand, in the 
                             same direction (Jensen et al. 1999). Values can range from 0 (no match at all) to 
                             1(one or more perfect match within the window). 

                              * L. J. Jensen and C. Friis and D.W. Ussery Three views of complete chromosomes 
                                (1999) 150:773-777

                            Local Inverted Repeats
                             Local Inverted repeats are found by taking a 100 bp sequence window, and looking 
                             for the best match of a 30 bp piece withinthat window, on the opposite strand, in 
                             the opposite direction (Jensen et al. 1999). Values can range from 0 (no match at 
                             all)to 1 (one or more perfect match within the window). 

                              * L. J. Jensen and C. Friis and D.W. Ussery Three views of complete chromosomes 
                                (1999) 150:773-777 

                            Mirror Repeats
                             Local Mirror repeats are found by taking a 100 bp sequence window, and looking for 
                             the best match of a 30 bp piece withinthat window, on the same strand, in the opposite 
                             direction (Jensen et al. 1999). Values can range from 0 (no match at all) to 1(one 
                             or more perfect match within the window). 

                              * L. J. Jensen and C. Friis and D.W. Ussery Three views of complete chromosomes 
                                (1999) 150:773-777 

                            Quasi-palindromes
                             "Quasi-palindromes" are short inverted repeats, which are found by taking a 30 bp 
                             piece of sequence, and looking for matcheswith at least 6 out of 7 nt matching, on 
                             the opposite strand, in the opposite direction (van et al. 2003). Values canrange 
                             from 0 (no match at all) to 1 (one or more perfect match within the window). 

                              * van Noort V, Worning P, Ussery DW, Rosche WA, Sinden RR Strand misalignments lead 
                                to quasipalindrome correction (2003) 19:365-9 

                            Perfect-palindromes
                             "Perfect-palindromes" are short inverted repeats, which are found by taking a 30 
                             bp piece of sequence, and looking forperfect matches of 7 nt or longer, on the opposite 
                             strand, in the opposite direction (van et al. 2003). Values can rangefrom 0 (no match 
                             at all) to 1 (one or more perfect match within the window). 

                              * van Noort V, Worning P, Ussery DW, Rosche WA, Sinden RR Strand misalignments lead 
                                to quasipalindrome correction (2003) 19:365-9

                            Simple Repeats
                             A "simple repeat" is a region which contains a simple oligonucleotide repeat, like 
                             microsattelites. Simple repeats are foundby looking for tandem repeats of length 
                             R within a 2R-bp window. By using the values 12, 14, 15, 16, and 18 for R, allsimple 
                             repeats of lengths 1 through 9 are calculated, of length of at least 24 bp (Jensen 
                             et al. 1999). Values can range from 0(no match at all) to 1 (one or more perfect 
                             match within the window). 

                              * L. J. Jensen and C. Friis and D.W. Ussery Three views of complete chromosomes 
                                (1999) 150:773-777 
                             
                             Current undocumented properties are:
                            AAAA
                            CCCC
                            TTTT
                            GGGG
                            T4 or C4 vs. A4 or G4
                            (Y)10 vs. (R)10
                            (CR)5 vs. (YG)5
                            (CA)3
                            (CG)3
                            (TA)3
                            (TG)3
                            (YR)5
              
    Output: 
            * 'jobid'     : The 32 byte identification string of the job
            * 'datetime'  : The last timepoint at which the status of the job has changed
            * 'status'    : Possible values are QUEUED, ACTIVE, FINISHED, WAITING, REJECTED, 
                            UNKNOWN JOBID or QUEUE DOWN
            * 'expires'   : Normal expire time is 24hrs. Job results should be downloaded 
                            before that.

7.  DNApropertyFetchResult
    Retrieves the result from a job submitted using 'DNApropertyRun'

    Input: 
            * 'jobid'     : The 32 byte identification string of the job
    Output: 
            * 'method'    : Method, as provided in request
            * 'values'    : Calculation results given as a string separated by comma. Each
                            position in the list corresponds to the position in the input 
                            sequence.

8.  trnascanRun
    Submit the input parapeter(s) and sequence data and returns a job identifier
    to tRNAscan-SE 1.23 (April 2002)
    
    Input:
          * 'kingdom'     : The kingdom of the genomic sequence
                            3 kingdoms are available: bac, euk, arc. This is specified
                            only once for the sequences in the current job.
          * 'sequence'    : (A single sequence object containing:)
           *  'id'        : The identifier of the sequence
           *  'seq'       : The sequence specified as one continous string
    Output:
          * 'jobid'       : The 32 byte identification string of the job
          * 'datetime'    : The last timepoint at which the status of the job has changed
          * 'status'      : Possible values are QUEUED, ACTIVE, FINISHED, WAITING, REJECTED, 
                            UNKNOWN JOBID or QUEUE DOWN

     
9. trnascanFetchResult 
   Once the status is 'FINISHED' the results generated by the Web Service can be retrieved by
   specifying the jobid;
  
    Input
          * 'jobid'       : The 32 byte identification string of the job
    Output
          * 'annsource'
           * 'method'     : The name of the prediction method
           * 'version'    : Version of name of the prediction method
          * 'ann' (ann object with the following content:) 
           * 'sequence' 
            * 'id'        : sequence identifier as uploaded by the user
            * 'seq'       : sequence as uploaded by the user
           * 'annrecords'
            * 'annrecord'
             * 'feature'  : E.g. 'Ala,TGC'
             * 'range'
              * 'begin'   : begin position of the tRNA gene
              * 'end'     : end position of the tRNA gene
             * 'score' 
              * 'value'   : Cove score
10. pollQueue [common]
    Once obtained from 'runService', a job identification can be used to poll the
    status to see if the result is ready for download.

    Input 
          * 'jobid'       : The 32 byte identification string of the job
    Output
          * 'jobid'       : The 32 byte identification string of the job
          * 'datetime'    : The last timepoint at which the status of the job has changed
          * 'status'      : Possible values are QUEUED, ACTIVE, FINISHED, WAITING, REJECTED, 
                            UNKNOWN JOBID or QUEUE DOWN

  
11. aaUsage
    Calculate the amino acid usage in a genome (proteome) and generates 
    a base64 encoded image (PNG) showing a diagram of this usage.
    Input
          * 'contig'        : Array of genome sequences
           * 'id'           : Identifier of the genome
           * 'sequencedata' : Container for one or more sequences (typically a proteome)
            * 'sequence'    
             * 'id'         : Id of the protein 
             * 'seq'        : Protein sequence 
    Output
           * 'sequence'
            * 'id'          : Genome identifier, provided in the input
            * 'image'       : Image object
             * 'comment'    : Description of the image
             * 'encoding'   : Encoding of the binary content of the image (base64)
             * 'MIMEtype'   : File type (image/png)
             * 'content'    : Encoded binary content
            * 'aaUsage'
             * 'entry'      
              * 'name'      : Name of the amino acid, e.g. Ala, Val, Leu ... 
              * 'count'     : Number of occurences in the genome
              * 'freq'      : Frequency of the amino acid
              * 'group'     : Amino acid class: Polar,Aromatic,Sulfur,
                              Aliphatic,Structural,+,-

12. codonUsage
    Calculate the codon usage in a genome (orfs) and generates 
    a base64 encoded image (PNG) showing a diagram of this usage.
    Input
          * 'contig'        : Array of genome sequences
           * 'id'           : Identifier of the genome
           * 'sequencedata' : Container for one or more sequences (typically a proteome)
            * 'sequence'    
             * 'id'         : Id of the protein 
             * 'seq'        : Protein sequence 
    Output
           * 'sequence'
            * 'id'          : Genome identifier, provided in the input
            * 'image'       : Image object
             * 'comment'    : Description of the image
             * 'encoding'   : Encoding of the binary content of the image (base64)
             * 'MIMEtype'   : File type (image/png)
             * 'content'    : Encoded binary content
            * 'aaUsage'
             * 'entry'      
              * 'codon'     : DNA triplet (e.g. ATG ...)
              * 'freq'      : Frequency of the triplet
              * 'count'     : Number of occurrences in each genome
              * 'aa'        : Corresponding amino acid

13.  prodigalFetchResult
    Retrieves the result from a job submitted using 'runProdigal'

    Input: 
            * 'jobid'     : The 32 byte identification string of the job
    Output: 
            * 'method'    : Method, as provided in request
            * 'values'    : Calculation results given as a string separated by comma. Each
                            position in the list corresponds to the position in the input 
                            sequence.

14. runProdigal
    Run gene predictor 'prodigal' through a set of contigs. All contigs
    as a whole are used for codon statistics.

    Input
          * 'transl_tbl'   : Translation table, use 11 if in doubt.
          * 'sequencedata' : Container for one or more sequences
           * 'sequence'    
            * 'id'         : Id of the protein 
            * 'seq'        : Protein sequence 
    Output
            * 'jobid'     : The 32 byte identification string of the job


    For more information, please contact Peter F. Hallin: pfh@cbs.dtu.dk,
    David W. Ussery (dave@cbs.dtu.dk), or Krisoffer Rapacki (rapacki@cbs.dtu.dk)