Class VariantDataFrame

A DataFrame of variant's data that is indexed "variant type AND chromosome possition". We create an "DataFrame" for each variant type: SNP(A), SNP(C), SNP(G), SNP(T), INS, DEL, MNP, MIXED, OTHER. Each DataFrame is indexed by chromosome position. DataFrames have columns for each field to annotate. The `VariantDataFrame` class represents a data structure for storing and annotating variant data indexed by variant type and chromosome position. This class manages multiple `DataFrame` objects, each corresponding to a different variant type (e.g., SNP, INS, DEL, MNP, MIXED, OTHER). Each `DataFrame` is indexed by chromosome position and contains columns for various fields to annotate. Key functionalities of this class include: - Loading and saving `VariantDataFrame` objects from/to files. - Adding variant data to the appropriate `DataFrame`. - Annotating VCF entries with fields from the `VariantDataFrame`. - Checking the integrity of the data frames. - Resizing and optimizing memory usage of the data frames. The class also provides methods to set a prefix for field names, calculate the total memory size of the data frames, and generate a string representation of the `VariantDataFrame`. The class implements `Serializable` to allow for serialization and deserialization of its instances. Example usage: - Load a `VariantDataFrame` from a file: `VariantDataFrame vd = VariantDataFrame.load(chr, fileName, emptyIfNotFound);` - Add a variant to the `VariantDataFrame`: `vd.add(variantVcfEntry);` - Annotate a VCF entry: `int found = vd.annotate(vcfEntry, fieldNames);` - Save the `VariantDataFrame` to a file: `vd.save(fileName);` - Check the integrity of the data frames: `vd.check();` - Resize and optimize memory usage: `vd.resize();` - Set a prefix for field names: `vd.setPrefix(prefix);` - Get the total memory size of the data frames: `long size = vd.sizeBytes();` - Get a string representation of the `VariantDataFrame`: `String str = vd.toString();`