Provided by: libtfbs-perl_0.7.1-2_amd64 bug


       TFBS::Matrix::PFM - class for raw position frequency matrix patterns


       ·   creating a TFBS::Matrix::PFM object manually:

               my $matrixref = [ [ 12,  3,  0,  0,  4,  0 ],
                                 [  0,  0,  0, 11,  7,  0 ],
                                 [  0,  9, 12,  0,  0,  0 ],
                                 [  0,  0,  0,  1,  1, 12 ]
               my $pfm = TFBS::Matrix::PFM->new(-matrix => $matrixref,
                                                -name   => "MyProfile",
                                                -ID     => "M0001"
               # or

               my $matrixstring =
                   "12 3 0 0 4 0\n0 0 0 11 7 0\n0 9 12 0 0 0\n0 0 0 1 1 12";

               my $pfm = TFBS::Matrix::PFM->new(-matrixstring => $matrixstring,
                                                -name         => "MyProfile",
                                                -ID           => "M0001"

       ·   retrieving a TFBS::Matix::PFM object from a database:

           (See documentation of individual TFBS::DB::* modules to learn how to connect to
           different types of pattern databases and retrieve TFBS::Matrix::* objects from them.)

               my $db_obj = TFBS::DB::JASPAR2->new
                               (-connect => ["dbi:mysql:JASPAR2:myhost",
                                             "myusername", "mypassword"]);
               my $pfm = $db_obj->get_Matrix_by_ID("M0001", "PFM");
               # or
               my $pfm = $db_obj->get_Matrix_by_name("MyProfile", "PFM");

       ·   retrieving list of individual TFBS::Matrix::PFM objects from a TFBS::MatrixSet object

           (See the TFBS::MatrixSet to learn how to create objects for storage and manipulation
           of multiple matrices.)

               my @pfm_list = $matrixset->all_patterns(-sort_by=>"name");

       ·   convert a raw frequency matrix to other matrix types:

               my $pwm = $pfm->to_PWM(); # convert to position weight matrix
               my $icm = $icm->to_ICM(); # convert to information con


       TFBS::Matrix::PFM is a class whose instances are objects representing raw position
       frequency matrices (PFMs). A PFM is derived from N nucleotide patterns of fixed size, e.g.
       the set of sequences


       will give the matrix:

           A:[ 12  3  0  0  4  0 ]
           C:[  0  0  0 11  7  0 ]
           G:[  0  9 12  0  0  0 ]
           T:[  0  0  0  1  1 12 ]

       which contains the count of each nucleotide at each position in the sequence. (If you have
       a set of sequences as above and want to create a TFBS::Matrix::PFM object out of them,
       have a look at TFBS::PatternGen::SimplePFM module.)

       PFMs are easily converted to other types of matrices, namely information content matrices
       and position weight matrices. A TFBS::Matrix::PFM object has the methods to_ICM and to_PWM
       which do just that, returning a TFBS::Matrix::ICM and TFBS::Matrix::PWM objects,


       Please send bug reports and other comments to the author.

AUTHOR - Boris Lenhard

       Boris Lenhard <>


       The rest of the documentation details each of the object methods. Internal methods are
       preceded with an underscore.

        Title   : new
        Usage   : my $pfm = TFBS::Matrix::PFM->new(%args)
        Function: constructor for the TFBS::Matrix::PFM object
        Returns : a new TFBS::Matrix::PFM object
        Args    : # you must specify either one of the following three:

                  -matrix,      # reference to an array of arrays of integers
                  -matrixstring,# a string containing four lines
                                # of tab- or space-delimited integers
                  -matrixfile,  # the name of a file containing four lines
                                # of tab- or space-delimited integers

                  -name,        # string, OPTIONAL
                  -ID,          # string, OPTIONAL
                  -class,       # string, OPTIONAL
                  -tags         # an array reference, OPTIONAL
       Warnings  : Warns if the matrix provided has columns with different
                   sums. Columns with different sums contradict the usual
                   origin of matrix data and, unless you are absolutely sure
                   that column sums _should_ be different, it would be wise to
                   check your matrices.

        Title   : column_sum
        Usage   : my $nr_sequences = $pfm->column_sum()
        Function: calculates the sum of elements of one column
                  (the first one by default) which normally equals the
                  number of sequences used to derive the PFM.
        Returns : the sum of elements of one column (an integer)
        Args    : columnn number (starting from 1), OPTIONAL - you DO NOT
                  need to specify it unless you are dealing with a matrix

        Title   : to_PWM
        Usage   : my $pwm = $pfm->to_PWM()
        Function: converts a raw frequency matrix (a TFBS::Matrix::PFM object)
                  to position weight matrix. At present it assumes uniform
                  background distribution of nucleotide frequencies.
        Returns : a new TFBS::Matrix::PWM object
        Args    : none; in the future releases, it should be able to accept
                  a user defined background probability of the four

        Title   : to_ICM
        Usage   : my $icm = $pfm->to_ICM()
        Function: converts a raw frequency matrix (a TFBS::Matrix::PFM object)
                  to information content matrix. At present it assumes uniform
                  background distribution of nucleotide frequencies.
        Returns : a new TFBS::Matrix::ICM object
        Args    : -small_sample_correction # undef (default), 'schneider' or 'pseudocounts'

       How a PFM is converted to ICM:

       For a PFM element PFM[i,k], the probability without pseudocounts is estimated to be simply

         p[i,k] = PFM[i,k] / Z

       where - Z equals the column sum of the matrix i.e. the number of motifs used to construct
       the PFM.  - i is the column index (position in the motif) - k is the row index (a letter
       in the alphacer, here k is one of (A,C,G,T)

       Here is how one normally calculates the pseudocount-corrected positional probability

         p'[i,k] = (PFM[i,k] + 0.25*sqrt(Z)) / (Z + sqrt(Z))

       0.25 is for the flat distribution of nucleotides, and sqrt(Z) is the recommended
       pseudocount weight. In the general case,

         p'[i,k] = (PFM[i,k] + q[k]*B) / (Z + B)

       where q[k] is the background distribution of the letter (nucleotide) k, and B an arbitrary
       pseudocount value or expression (for no pseudocounts B=0).

       For a given position i, the deviation from random distribution in bits is calculated as
       (Baldi and Brunak eq. 1.9 (2ed) or 1.8 (1ed)):

       - for an arbitrary alphabet of A letters:

         D[i] = log2(A) + sum_for_all_k(p[i,k]*log2(p[i,k]))

       - special case for nucleotides (A=4)

         D[i] = 2 + sum_for_all_k(p[i,k]*log2(p[i,k]))

       D[i] equals the information content of the position i in the motif. To calculate the
       entire ICM, you have to calculate the contrubution of each nucleotide at a position i to
       D[i], i.e.

       ICM[i,k] = p'[i,k] * D[i]

        Title   : draw_logo
        Usage   : my $gd_image = $pfm->draw_logo()
        Function: draws a sequence logo; similar to the
                  method in TFBS::Matrix::ICM, but can automatically calculate
                  error bars for drawing
        Returns : a GD image object (see documentation of GD module)
        Args    : many; PFM-specific options are:
                  -small_sample_correction # One of
                                           # "Schneider" (uses correction
                                           #   described by Schneider et al.
                                           #   (Schneider t et al. (1986) J.Biol.Chem.
                                           # "pseudocounts" - standard pseudocount
                                           #   correction,  more suitable for
                                           #   PFMs with large r column sums
                                           # If the parameter is omitted, small
                                           # sample correction is not applied

                  -draw_error_bars         # if true, adds error bars to each position
                                           # in the logo. To calculate the error bars,
                                           # it uses the -small_sample_connection
                                           # argument if explicitly set,
                                           # or "Schneider" by default
       For other args, see draw_logo entry in TFBS::Matrix::ICM documentation

        Title   : add_PFM
        Usage   : $pfm->add_PFM($another_pfm)
        Function: adds the values of $pnother_pfm matrix to $pfm
        Returns : reference to the updated $pfm object
        Args    : a TFBS::Matrix::PFM object

       The above methods are common to all matrix objects. Please consult TFBS::Matrix to find
       out how to use them.