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Bio-ToolBox-1.32
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/ Bio::ToolBox::Data

NAME

Bio::ToolBox::Data - Reading, writing, and manipulating data structure

SYNOPSIS

use Bio::ToolBox::Data;

### Create new gene list from database
my $Data = Bio::ToolBox::Data->new(
      db      => 'hg19',
      feature => 'gene:ensGene',
);

my $Data = Bio::ToolBox::Data->new(
      db      => 'hg19',
      feature => 'genome',
      win     => 1000,
      step    => 1000,
);


### Open a pre-existing file
my $Data = Bio::ToolBox::Data->new(
      file    => 'coordinates.bed',
);


### Get a specific value
my $value = $Data->value($row, $column);


### Replace or add a value
$Data->value($row, $column, $new_value);


### Iterate through a Data structure one row at a time
my $stream = $Data->row_stream;
while (my $row = $stream->next_row) {
	  # get the positional information from the file data
	  # assuming that the input file had these identifiable columns
	  my $seq_id = $row->seq_id;
	  my $start  = $row->start;
	  my $stop   = $row->end;
	  
	  # generate a Bio::Seq object from the database using 
	  # these coordinates 
	  my $region = $db->segment($seq_id, $start, $stop);
	  
	  # modify a row value
	  my $value = $row->value($column);
	  my $new_value = $value + 1;
	  $row->value($column, $new_value);
}


### write the data to file
my $success = $Data->write_file(
     filename     => 'new_data.txt',
     gz           => 1,
);
print "wrote new file $success\n"; # file is new_data.txt.gz

DESCRIPTION

This module works with the primary Bio::ToolBox Data structure. Simply, it is a complex data structure representing a tabbed-delimited table (array of arrays), with plenty of options for metadata. Many common bioinformatic file formats are simply tabbed-delimited text files (think BED and GFF). Each row is a feature or genomic interval, and each column is a piece of information about that feature, such as name, type, and/or coordinates. We can append to that file additional columns of information, perhaps scores from genomic data sets. We can record metadata regarding how and where we obtained that data. Finally, we can write the updated table to a new file.

METHODS

Initializing the structure

new()

Initialize a new Data structure. This generally requires options, provided as an array of key => values. A new list of features may be obtained from an annotation database or an existing file may be loaded. If you do not pass any options, a new empty structure will be generated for you to populate.

These are the options available.

file => $filename

Provide the path and name to an existing tabbed-delimited text file. BED and GFF files and their variants are accepted. Except for structured files, e.g. BED and GFF, the first line is assumed to be column header names. Commented lines (beginning with #) are parsed as metadata. The files may be compressed (gzip or bzip2).

stream => 1

Indicate that the file should be opened as a file stream. A Bio::ToolBox::Data::Stream object will be returned. This is a convenience method.

feature => $type
feature => "$type:$source"
feature => 'genome'

For de novo lists from an annotation database, provide the GFF type or type:source (columns 3 and 2) for collection. A comma delimited string may be accepted (not an array).

For a list of genomic intervals across the genome, specify a feature of 'genome'.

db => $name
db => $path
db => $database_object

Provide the name of the database from which to collect the features. It may be a short name, whereupon it is checked in the Bio::ToolBox configuration file .biotoolbox.cfg for connection information. Alternatively, a path to a database file or directory may be given.

If you already have an opened Bio::DB::SeqFeature::Store database object, you can simply pass that. See Bio::ToolBox::db_helper for more information. However, this in general should be discouraged, since the name of the database will not be properly recorded when saving to file. It is better to simply pass the name of database again; multiple connections to the same database are smartly handled in the background.

win => $integer
step => $integer

If generating a list of genomic intervals, optionally provide the window and step values. Default values are defined in the Bio::ToolBox configuration file .biotoolbox.cfg.

columns => [qw(Column1 Column2 ...)]
datasets => [qw(Column1 Column2 ...)]

When no file is given or database given to search, then a new, empty Data object is returned. In this case, you may optionally provide the column names in advance as an anonymous array. You may also optionally provide a general feature name, if desired.

If successful, the method will return a Bio::ToolBox::Data object.

duplicate()

This will create a new Data object containing the same column headers and metadata, but lacking the table content, i.e. no rows of data. File name metadata, if present in the original, is not preserved. The purpose here, for example, is to allow one to selectively copy rows from one row to another.

General Metadata

There is a variety of general metadata regarding the Data structure.

The following methods may be used to access or set these metadata properties.

feature()
feature($text)

Returns or sets the name of the features used to collect the list of features. The actual feature types are listed in the table, so this metadata is merely descriptive.

feature_type

Returns one of three specific values describing the contents of the data table inferred by the presence of specific column names. This provides a clue as to whether the table features represent genomic regions (defined by coordinate positions) or named database features. The return values include:

coordinate: Table includes at least chromosome and start
named: Table includes name, type, and/or Primary_ID
unknown: unrecognized
program($name)

Returns or sets the name of the program generating the list.

database($name)

Returns or sets the name or path of the database from which the features were derived.

The following methods may be used to access metadata only.

gff
bed

Returns the GFF version number or the number of BED columns indicating that the Data structure is properly formatted as such. A value of 0 means they are not formatted as such.

File information

filename
path
basename
extension

Returns the filename, full path, basename, and extension of the filename. Concatenating the last three values will reconstitute the first original filename.

add_file_metadata($filename)

Add filename metadata. This will automatically parse the path, basename, and recognized extension from the passed filename.

Comments

Comments are any other commented lines from a text file (lines beginning with a #) that were not parsed as metadata.

comments

Returns a copy of the array containing commented lines.

add_comment($text)

Appends the text string to the comment array.

delete_comment
delete_comment($index)

Deletes a comment. Provide the array index of the comment to delete. If an index is not provided, ALL comments will be deleted!

The Data table

The Data table is the array of arrays containing all of the actual information.

list_columns

Returns an array or array reference of the column names in ascending (left to right) order.

number_columns

Returns the number of columns in the Data table.

last_row

Returns the array index number of the last row. Since the header row is index 0, this is also the number of actual content rows.

column_values($index)

Returns an array or array reference representing the values in the specified column. This includes the column header as the first element. Pass the method the column index.

add_column($name)
add_column(\@column_data)

Appends a new column to the Data table at the rightmost position (highest index). It adds the column header name and creates a new column metadata hash. Pass the method one of two possibilities. Pass a text string representing the new column name, in which case no data will be added to the column. Alternatively, pass an array reference, and the contents of the array will become the column data. If the Data table already has rows, then the passed array reference must have the same number of elements.

It returns the new column index if successful.

copy_column($index)

This will copy a column, appending the duplicate column at the rightmost position (highest index). It will duplicate column metadata as well. It will return the new index position.

delete_column($index1, $index2, ...)

Deletes one or more specified columns. Any remaining columns rightwards will have their indices shifted down appropriately. If you had identified one of the shifted columns, you may need to re-find or calculate its new index.

reorder_column($index1, $index, ...)

Reorders columns into the specified order. Provide the new desired order of indices. Columns could be duplicated or deleted using this method. The columns will adopt their new index numbers.

add_row
add_row(\@values)
add_row($row)

Add a new row of data values to the end of the Data table. Optionally provide either a reference to an array of values to put in the row, or pass a <Bio::ToolBox::Data::Feature> row object, such as one obtained from another Data object. If the number of columns do not match, the array is filled up with null values for missing columns, or excess values are dropped.

delete_row($row1, $row2, ...)

Deletes one or more specified rows. Rows are spliced out highest to lowest index to avoid issues. Be very careful deleting rows while simultaneously iterating through the table!

row_values($row)

Returns a copy of an array for the specified row index. Modifying this returned array does not migrate back to the Data table; Use the value method below instead.

value($row, $column)
value($row, $column, $new_value)

Returns or sets the value at a specific row or column index. Index positions are 0-based (header row is index 0).

Column Metadata

Each column has metadata. Each metadata is a series of key => value pairs. The minimum keys are 'index' (the 0-based index of the column) and 'name' (the column header name). Additional keys and values may be queried or set as appropriate. When the file is written, these are stored as commented metadata lines at the beginning of the file.

name($index)
name($index, $new_name)

Convenient method to return the name of the column given the index number. A column may also be renamed by passing a new name.

metadata($index, $key)
metadata($index, $key, $new_value)

Returns or sets the metadata value for a specific $key for a specific column $index.

This may also be used to add a new metadata key. Simply provide the name of a new $key that is not present

If no key is provided, then a hash or hash reference is returned representing the entire metadata for that column.

copy_metadata($source, $target)

This method will copy the metadata (everything except name and index) between the source column and target column. Returns 1 if successful.

delete_metadata($index, $key);

Deletes a column-specific metadata $key and value for a specific column $index. If a $key is not provided, then all metadata keys for that index will be deleted.

find_column($name)

Searches the column names for the specified column name. This employs a case-insensitive grep search, so simple substitutions may be made.

chromo_column
start_column
stop_column
strand_column
name_column
type_column
id_column

These methods will return the identified column best matching the description. Returns undef if that column is not present. These use the find_column() method with a predefined list of aliases.

Efficient Data Access

Most of the time we need to iterate over the Data table, one row at a time, collecting data or processing information. These methods simplify the process.

iterate(sub {})

This method will process a code reference on every row in the data table. Pass a subroutine or code reference. The subroutine will receive the row as a Bio::ToolBox::Data::Feature object. With this object, you can retrieve values, set values, and add new values. For example

$Data->iterate( sub {
   my $row = shift;
   my $number = $row->value($index);
   my $log_number = log($number);
   $row->value($index, $log_number);
} );
row_stream()

This returns an Bio::ToolBox::Data::Iterator object, which has one method, next_row(). Call this method repeatedly until it returns undef to work through each row of data.

Users of the Bio::DB family of database adaptors may recognize the analogy to the seq_stream() method.

next_row()

Called from a Bio::ToolBox::Data::Iterator object, it returns a Bio::ToolBox::Data::Feature object. This object represents the values in the current Data table row.

An example using the iterator is shown below.

my $stream = $Data->row_stream;
while (my $row = $stream->next_row) {
   # each $row is a Bio::ToolBox::Data::Feature object
   # representing the row in the data table
   my $value = $row->value($index);
   # do something with $value
}

Data Table Functions

These methods alter the Data table en masse.

verify()

This method will verify the Data structure, including the metadata and the Data table. It ensures that the table has the correct number of rows and columns as described in the metadata, and that each column has the basic metadata.

If the Data structure is marked as a GFF or BED structure, then the table is checked that the structure matches the proper format. If not, for example when additional columns have been added, then the GFF or BED value is set to null.

This method is automatically called prior to writing the Data table to file.

sort_data($index, $direction);

This method will sort the Data table by the values in the indicated column. It will automatically determine whether the contents of the column are numbers or alphanumeric, and will sort accordingly, either numerically or asciibetically. The first non-null value in the column is used to determine. The sort may fail if the values are not consistent. Pass a second optional value to indicate the direction of the sort. The value should be either 'i' for 'increasing' or 'd' for 'decreasing'. The default order is increasing.

gsort_data

This method will sort the Data table by increasing genomic coordinates. It requires the presence of chromosome and start (or position) columns, identified by their column names. These are automatically identified. Failure to find these columns mean a failure to sort the table. Chromosome names are sorted first by their digits (e.g. chr2 before chr10), and then alphanumerically. Base coordinates are sorted by increasing value. Identical positions are kept in their original order.

splice_data($current_part, $total_parts)

This method will splice the Data table into $total_parts number of pieces, retaining the $current_part piece. The other parts are discarded. This method is intended to be used when a program is forked into separate processes, allowing each child process to work on a subset of the original Data table.

Two values are passed to the method. The first is the current part number, 1-based. The second value is the total number of parts that the table should be divided, corresponding to the number of concurrent processes. One easy approach to forking is to use Parallel::ForkManager. The example below shows how to fork into four concurrent processes.

my $Data = Bio::ToolBox::Data->new(file => $file);
my $pm = Parallel::ForkManager->new(4);
for my $i (1..4) {
	$pm->start and next;
	### in child ###
	$Data->splice_data($i, 4);
	# do something with this portion
	# then save to a temporary unique file
	$Data->save("$file_$i");
	$pm->finish;
}
$pm->wait_all_children;
# reload children files
$Data->reload_children(glob "$file_*");

Since each forked child process is separate from their parent process, their contents must be reloaded into the current Data object. The Parallel::ForkManager documentation recommends going through a disk file intermediate. Therefore, write each child Data object to file using a unique name. Once all children have been reaped, they can be reloaded into the current Data object using the reload_children() method.

Remember that if you fork your script into child processes, any database connections must be re-opened; they are typically not clone safe. If you have an existing database connection by using the open_database() method, it should be automatically re-opened for you when you use the splice_data() method, but you will need to call open_database() again in the child process to obtain the new database object.

reload_children(@children_files)

Discards the current data table in memory and reloads two or more files written from forked children processes. Provide the name of the child files in the order you want them loaded. The files will be automatically deleted if successfully loaded. Returns the number of lines reloaded on success.

File Functions

When you are finished modifying the Data table, it may then be written out as a tabbed-delimited text file. If the format corresponds to a valide BED or GFF file, then it may be written in that format.

Several functions are available for writing the Data table, exporting to a compatible GFF file format, or writing a summary of the Data table.

save()
write_file()
write_file($filename)
write_file(%options)

These methods will write the Data structure out to file. It will be first verified as to proper structure. Opened BED and GFF files are checked to see if their structure is maintained. If so, they are written in the same format; if not, they are written as regular tab-delimited text files. You may pass additional options.

filename => $filename

Optionally pass a new filename. Required for new objects; previous opened files may be overwritten if a new name is not provided. If necessary, the file extension may be changed; for example, BED files that no longer match the defined format lose the .bed and gain a .txt extension. Compression may or add or strip .gz as appropriate. If a path is not provided, the current working directory is used.

gz => boolean

Change the compression status of the output file. The default is to maintain the status of the original opened file.

If the file save is successful, it will return the full path and name of the saved file, complete with any changes to the file extension.

summary_file(%options)

Write a separate file summarizing columns of data (mean values). The mean value of each column becomes a row value, and each column header becomes a row identifier (i.e. the table is transposed). The best use of this is to summarize the mean profile of windowed data collected across a feature. See the Bio::ToolBox scripts get_relative_data.pl and get_binned_data.pl as examples. You may pass these options.

filename => $filename

Pass an optional new filename. The default is to take the basename and append "_summed" to it.

startcolumn => $index
stopcolumn => $index

Provide the starting and ending columns to summarize. The default start is the leftmost column without a recognized standard name. The default ending column is the last rightmost column. Indexes are 0-based.

If successful, it will return the name of the file saved.

Verifying Datasets

When working with row Features and collecting scores, the dataset from which you are collecting must be verified prior to collection. This ensures that the proper database adaptor is available and loaded, and that the dataset is correctly specified (otherwise nothing would be collected). This verification is normally performed transparently when you call get_score() or get_position_scores(). However, datasets may be explicitly verified prior to calling the score methods.

verify_dataset($dataset)
verify_dataset($dataset, $database)

Pass the name of the dataset (GFF type or type:source) for a GFF3-based database, e.g. <Bio::DB::SeqFeature::Store>, or path and file name for a data file, e.g. Bam, BigWig, BigBed, or USeq file. If a separate database is being used, pass the name or opened database object as a second parameter. For more advance options, see "verify_or_request_feature_types" in Bio::ToolBox::db_helper.

The name of the verified dataset, with a prefix if necessary, is returned.

AUTHOR

Timothy J. Parnell, PhD
Dept of Oncological Sciences
Huntsman Cancer Institute
University of Utah
Salt Lake City, UT, 84112

This package is free software; you can redistribute it and/or modify it under the terms of the Artistic License 2.0.