BioJava:CookBook:Core:Overview

Draft copy of Core module design and capabilities.

When doing the analysis of code from Biojava 1 and what should be done in Biojava3 and emphasis was placed on breaking the code into modules. Thus core represent a collection of classes that would be common to other modules. The common elements for all modules is reading, writing and representation of sequence data. We also thought it was important to use Java to model the biological relationships between sequences as accurately as possible. The Biojava3 api should establish concrete relationships that help the computer scientist understand the biology through code and be familiar to the Biologist when writing code.

In the genomic view of sequence data we now have very large data sets which presents challenges in loading everything into memory or retreating to a database and let it handle that complexity. We want to allow easy integration of sequence databases such as BioSQL but at the same time support large sequence datasets loaded from disk or accessed via web services. This is why the Sequence Interface reigns supreme! By modeling the relationships between a ProteinSequence and a GeneSequence it isn’t unreasonable to expect that if you load a protein sequence with an accession id that you should be able to use a method in the protein sequence to retrieve the gene sequence that codes for that protein sequence. Once you have the gene sequence you should be able to easily extract intron sequences or sequence data flanking the gene sequence for analysis. By leveraging the REST or Web Services of public data sources like Uniprot or NCBI we want the api to hide these implementation details but offer enough flexibility that other public or private data sources can be easily integrated into BioJava3.

An additional design goal is to keep the size of biojava3-core module as small as possible by not making it a convient place to add in new classes that do not directly relate to protein or DNA sequences or become dependent on external jar files. As an example we are currently using Java 6 XML api to process XML files which has performance issues as compared to Dom4J. It is tempting to make Dom4J a standard library in BioJava3 because of its speed and api but it is no longer being actively developed. We are using the Java 6 api for REST or WebService calls where we could use Axis or some other interesting 3rd party library. Before you realize it core has a large number of external dependencies which creates potential problems for developers who are using the Biojava3 api in their application if a different version of an external api is required. For now Core is all about sequences and keeping it as small as possible. Currently, the biojava3-core module is being developed as part of the day job for two developers with tight deadlines and never enough time to do extensive documentation or even minimal documentation. Now that the biojava3-core module is settling down we will be working on finishing the JavaDoc, adding additional test cases and providing examples in the wiki.

The core sequence classes

  • AbstractSequence
    • DNASequence
      • ChromosomeSequence
      • GeneSequence
      • IntronSequence
      • ExonSequence
      • TranscriptSequence
    • RNASequence
    • ProteinSequence

String is King but Sequence Interface reigns supreme

We really want to make it easy to create a sequence and what could be easier than using a String.


`           ProteinSequence proteinSequence = new ProteinSequence("ARNDCEQGHILKMFPSTWYVBZJX");`  
`           DNASequence dnaSequence = new DNASequence("ATCG");`

The storage of the sequence data is defined by the Sequence interface which allows for some interesting and we hope useful abstraction. The simplest Sequence interface to represent a sequences as a String is the ArrayListSequenceReader and is the default data store when creating a sequence from a string. For large genomic data you can create a ChromosomeSequence from a TwoBitSequenceReader or FourBitSequenceReader and reduce the in memory storage requirements. By using the Sequence Interface we can easily extend the concept of local sequence storage in a fasta file to loading the sequence from Uniprot or NCBI based on an accession ID. The following is a simple example of creating a ProteinSequence using a Uniprot ID where the UniprotProxySequenceReader implements the Sequence interface and knows how to take the Uniprot ID and retrieve the sequence data from Uniprot. The UniprotProxySequenceReader can implement other feature interfaces and using the XML data that describes the Protein Sequence we can give a list of known mutations or mutagenenis studies with references to papers. This also allows us to link the Uniprot ID to the NCBI ID and retrieve the gene sequence data from NCBI via the NCBIProxySequenceReader. We are still in the early stages of extending these sequence relationships and expect some api changes. The abstraction of the sequence storage to an interface allows for a great deal of flexibility but has also added some challenges in how to handle situations when something goes wrong and you need to throw an exception. By introducing the ability to load sequences from remote URLs when the internet is not working or you have implemented a lazy instantiation approach to loading sequence data we have made it difficult to handle error conditions without making every method throw an exception. This a design work in progress as we get feedback from developers and expect some level of api changes as we improve the overall design.


`           UniprotProxySequenceReader`<AminoAcidCompound>uniprotSequence = new UniprotProxySequenceReader`<AminoAcidCompound>`("YA745_GIBZE", AminoAcidCompoundSet.getAminoAcidCompoundSet());`  
`           ProteinSequence proteinSequence = new ProteinSequence(uniprotSequence);`

The use of the SequenceCreator interface also allows us to address large genomic data sets where the sequence data is loaded from a fasta file but done in a way where the sequence is loaded in a lazy fashion when the appropriate method for sequence data or sub-sequence data is needed. The FileProxyProteinSequenceCreator implements the Sequence interface but is very specific to learning the location of the sequence data in the file.


`           File file = new File(inputFile);`  
`           FastaReader`<ProteinSequence,AminoAcidCompound>fastaProxyReader = new FastaReader`<ProteinSequence,AminoAcidCompound>`(file, new GenericFastaHeaderParser`<ProteinSequence,AminoAcidCompound>`(), new FileProxyProteinSequenceCreator(file, AminoAcidCompoundSet.getAminoAcidCompoundSet()));`  
`           LinkedHashMap`<String,ProteinSequence>proteinProxySequences = fastaProxyReader.process();`

`           for(String key : proteinProxySequences.keySet()){`  
`               ProteinSequence proteinSequence = proteinProxySequences.get(key);`  
`               System.out.println(key);`  
`               System.out.println(proteinSequence.toString());`  
`           }`

In the above example a FastaReader class is created where we abstract out the code that is used to parse the Fasta Header and use FileProxyProteinSequenceCreator to learn the beginning and ending offset location of each protein sequence. When the fasta file is parsed instead of loading the sequence data for each sequence into a ProteinSequence using an ArrayListSequenceReader a SequenceFileProxyLoader is used instead. A SequenceFileProxyLoader is created for each sequence and stores the beginning and ending index of each sequence in the fasta file. When sequence data is needed for a ProteinSequence then SequenceFileProxyLoader will use Random I/O and seek to the offset position and return the sequence data. The current implementation of SequenceFileProxyLoader will load the protein sequence data when needed and retain in memory which works great if you are only interested in a subset of sequences. If the application using the API is going to iterate through all sequences in a large fasta file then in the end all sequence data would be loaded into memory. The SequenceFileProxyLoader could be easily extended to maintain a max number of sequences loaded or memory used and free up sequence data that is loaded into memory. This way you can implement the appropriate cacheing algorithm based on the usage of the sequence data.

Helper Classes make it easy

In an effort to provide a flexible and modular api the abstraction can often make it difficult for someone getting started with the api to know what to use. We are implementing a set of classes that have the word Helper in them to hide the abstraction and at the same time provide examples on how to use the underlying API. Typically the helper methods will be static methods and generally should be a small block of glue code. The following code shows the use of FastaReaderHelper and FastaWriterHelper.


`       LinkedHashMap`<String, DNASequence>dnaSequences = FastaReaderHelper.readFastaDNASequence(new File("454Scaffolds.fna"));`  
`       FastaWriterHelper.writeNucleotideSequence(new File("454Scaffolds-1.fna"),dnaSequences.values());`

Working with Sequence Objects

When working with Sequence objects it is important to keep a number of points in mind

  1. You must never rely on the backing storage of a Sequence
  2. Never perform operations on the String form of a Sequence since this will incur a performance penalty
  3. Sequences are iterable and can be stepped through using Java5’s foreach loop construct
  4. All Sequences have a generic capture of the type of compound they contain. Learn to use this capture to increase or decrease the types of Sequence you want to process
  5. If you need to change the contents of a Sequence investigate the views used by Translation on how to avoid costly and unnecessary construction costs
  6. Review SequenceMixin on how to write for Sequences in a very generic manner

Indexing Sequences By Length

Sometimes it is useful to index a set of sequences by their length. Avoid using any kind of String method to do this since String operations are costly in BioJava (due to the String conversion that must be applied). Here is an example on how to do it for any Sequence object.

```java List<Sequence\> translations = populateFromSomewhere(); Collections.sort(translations, new Comparator<Sequence<? extends Compound>\>() {

public int compare(Sequence<? extends Compound> o1, Sequence<? extends Compound> o2) {
  Integer o1Length = o1.getLength();
  Integer o2Length = o2.getLength();
  return o1Length.compareTo(o2Length);
}

}); ```

Note our usage of the generic type to capture Sequence objects of any type since the assessment of length is something which can be applied to any Sequence not just AminoAcidCompound sequences.

DNA Translation

DNA translation follows the normal biological flow where a portion of DNA (assumed to be CDS) is translated to mRNA. This is translated to a protein sequence using codons. All parts of the translation process are configurable including:

  • CompoundSets used in the Sequence objects
  • The SequenceCreator used
  • The Frame and direction of translation
  • Trimming stop codons
  • IUPAC codon tables

Quick and Dirty

The following translates the given DNASequence to a peptide using the non-ambiguity CompoundSets with Codon table 1 in Frame 1 in the forward orientation.


ProteinSequence protein = new DNASequence("ATG").getRNASequence().getProteinSequence();`

Translating in a Different Frame

A common feature of transcription is the ability to specify the base at which we start translating from DNA to RNA which in turn has an effect on how we convert the resulting RNA into a protein. This can be the difference between a working translation and one full of gibberish. The Frame enum provides all 6 available frames which can be given to the DNA object when we request the RNA. Multiple frames of translations are possible but see later on.


DNASequence dna = new DNASequence("AATG");`  
RNASequence rna = dna.getRNASequence(Frame.TWO);`  
ProteinSequence protein = rna.getProteinSequence();`

Translating in Multiple Frames

This requires a TranscriptionEngine but we will work with the default one for the moment. If you are unsure of the frame a portion of DNA is to be translated in you can specify a number of frames to perform the translation in. The following example attempts to translate a sequence in all three forward frames. The code returns a map of the results keyed by their frame.

java TranscriptionEngine te = TranscriptionEngine.getDefault(); Frame[] frames = Frame.getForwardFrames(); Map<Frame, Sequence<AminoAcidCompound>\> results = te.multipleFrameTranslation(dna, frames);

Using this we can replicate the functionality found in EMBOSS’ transeq package.

Using a TranscriptionEngine

Transcription engines are the workhorse of the translation process. If you want to do something _out of the ordinary_ then normally you will have to build one. A singleton version is available and is what the methods involved in the translation process use when not given an instance of TranscriptionEngine. If building a custom engine then you do this using the Builder object as shown in the following example. Here we will build an engine to

  • Translate bacteria genomes
  • Convert any initiating amino acid which is not methionine into one
  • Trim stops

java TranscriptionEngine.Builder b = new TranscriptionEngine.Builder(); b.table(11).initMet(true).trimStop(true); TranscriptionEngine engine = b.build();

This can be handed to the translation methods like so:


DNASequence dna = new DNASequence("ATG");`  
RNASequence rna = dna.getRNASequence(engine);`  
ProteinSequence protein = rna.getProteinSequence(engine);`

The translation can be started from the TranscriptionEngine directly except this results in more general objects (you will get back objects which implement the Sequence interface and not the true object type).


DNASequence dna = new DNASequence("ATG");`  
TranscriptionEngine engine = TranscriptionEngine.getDefault(); //Get the default engine`  
Sequence`<NucleotideCompound>rna = engine.getDnaRnaTranslator().createSequence(dna);`  
Sequence`<AminoAcidCompound>protein = engine.getRnaAminoAcidTranslator().createSequence(rna);`  
` `  
//Or to jump to it straight away use this method (coming soon)`  
Sequence`<AminoAcidCompound>protein = engine.translate(dna);`

Codon Tables

BioJava supports all IUPAC tables available from the org.biojava3.core.sequence.io.IUPACParser class. It is possible to define your own codon table should BioJava not support it. To do this you can use the IUPACTable object which accepts 3 Strings used to indicate the DNA used for each codon. If this does not suffice then you can implement your own instance of Table to return the required codons. The IUPAC tables we have are:

  • 1 - UNIVERSAL
  • 2 - VERTEBRATE_MITOCHONDRIAL
  • 3 - YEAST_MITOCHONDRIAL
  • 4 - MOLD_MITOCHONDRIAL
  • 5 - INVERTEBRATE_MITOCHONDRIAL
  • 6 - CILIATE_NUCLEAR
  • 9 - ECHINODERM_MITOCHONDRIAL
  • 10 - EUPLOTID_NUCLEAR
  • 11 - BACTERIAL
  • 12 - ALTERNATIVE_YEAST_NUCLEAR
  • 13 - ASCIDIAN_MITOCHONDRIAL
  • 14 - FLATWORM_MITOCHONDRIAL
  • 15 - BLEPHARISMA_MACRONUCLEAR
  • 16 - 2CHLOROPHYCEAN_MITOCHONDRIAL
  • 21 - TREMATODE_MITOCHONDRIAL
  • 23 - SCENEDESMUS_MITOCHONDRIAL

Ambiguous Symbols