NAME

Bio::Gonzales::SummarizedExperiment - represent experimental matrix-like data (assay) with features and sample info

SYNOPSIS

DESCRIPTION

http://bioconductor.org/packages/devel/bioc/vignettes/SummarizedExperiment/inst/doc/SummarizedExperiment.html

ATTRIBUTES

assay

    my $assay = $se->assay;

Return the assay of the summarized experiment.

col_data

    my $col_data = $se->col_data;
    $se->col_data(\@col_data);

row_data

row_names

col_names

row_data_names

col_data_names

meta_data

na_value

Set the NA value if the object is stored. Internally, while in memory, undef will be used. So this value will only have an effect if data is read or written somewhere. Default is Bio::Gonzales::SummarizedExperiment::NA_VALUE.

METHODS

data

    my $assay = $se->data;

A alias for assay.

add_col

add_cols

add_rows

aggregate

$se = $se->aggregate_by_idcs(\@idcs, sub { ... }, \@col_names)

The callback gets passed the grouping keys, rows and row indices. $_ is set to the group has that comes from the (internally used) $se->group function.

    sub {
      my ($key, $rows, $row_idcs) = @_;
      my $group = $_;
    }

$se = $se->aggregate_by_names(\@names, sub { ... }, \@col_names)

apply

as_hash

cbind

clone

col_apply

col_idx

col_idx_map

    my $I = $se->col_idx_map;
    my %I = $se->col_idx_map;

Returns a hash that maps the column names to their column index. col_idx_map is context sensitve and returns a hash in list context and a hash reference in scalar context.

col_idx_match

col_names_to_idcs

col_rename

dim

each

extract_col_by_idx

extract_col_by_name

group

group_by_idcs

group_by_names

has_col_data

has_col_names =head2 has_row_data =head2 has_row_names =head2 header =head2 header_idx =head2 header_idx_match =head2 inconsistencies =head2 json_spew =head2 make_consistent =head2 merge

Merge two SummarizedExperiment objects.

    use Bio::Gonzales::SummarizedExperiment;
    my $se_x = Bio::Gonzales::SummarizedExperiment->new(
      assay => [ [ 1, "homer", "simpson" ], [ 2, "bart", "simpson" ], [ 3, "lisa simpson" ] ],
      col_names => [qw(user_id first_name surname)]
    );
    
    my $se_y = Bio::Gonzales::SummarizedExperiment->new(
      assay => [ [ 1, 120 ], [ 2, 20 ] ],
      col_names => [qw(user_id weight_kg)]
    );
    
    # inner join by default
    my $merged_se = $se_x->merge($se_y, { by => [ 'user_id' ] });
    
    # user_id first_name surname weight_kg
    # 1       homer      simpson 120
    # 2       bart       simpson 20
    # Lisa is missing, because the $se_y lacks weight information.

names_to_idcs =head2 ncol =head2 nrow =head2 rbind =head2 row_apply

Apply a callback to each row. $se-row_apply(@args)> is equivalent to $se-apply(1, @args)>

    use Bio::Gonzales::SummarizedExperiment;
    my $se = Bio::Gonzales::SummarizedExperiment->new(
      assay => [ [ 1, "homer", "simpson" ], [ 2, "bart", "simpson" ], [ 3, "lisa", "simpson" ] ],
      col_names => [qw(user_id first_name surname)]
    );

    # WITHOUT MODIFYING THE SUMMARIZEDEXPERIMENT OBJECT
    $se->row_apply(sub { (my $name = $_->[1]) =~ s/[ra]/z/; $name });
    # [ 'homez', 'bzrt', 'lisz' ];

    $se->extract_col_by_idx(1);
    # [ 'homer', 'bart', 'lisa' ];


    # WITH MODIFYING THE SUMMARIZEDEXPERIMENT OBJECT
    $se->row_apply(sub { $_->[1] =~ s/[ra]/z/; $_->[1] });
    # [ 'homez', 'bzrt', 'lisz' ];

    $se->extract_col_by_idx(1);
    # [ 'homez', 'bzrt', 'lisz' ];

row_idx =head2 row_idx_map =head2 row_idx_match =head2 shuffle

slice_by_idcs

    $se->slice_by_idcs(\@idcs);
    $se->slice_by_idcs([0,5,13]);

Extract a column-"slice" from the summarized experiment. The indices select the columns.

slice_by_names

slurp_assay

    my $se = Bio::Gonzales::SummarizedExperiment->slurp_assay($source, \%params);
    my $se = Bio::Gonzales::SummarizedExperiment->slurp_assay("data.csv", { header => 1, sep => ';' });

Create a new summarized experiment from matrix/tabular data.

sort =head2 spew_assay =head2 subset =head2 encode_as_json =head2 transpose =head2 uniq

LIMITATIONS

NOTES

By convention,

• constructor or function arguments ending in ? are optional

• methods ending in ! will modify the object it is called on

SEE ALSO

AUTHOR

jw bargsten, <jwb at cpan dot org>

cpanm Bio::Gonzales

perl -MCPAN -e shell
install Bio::Gonzales