PaGE 5.1 Command Line Options Summary

--help
    If set, will show this help page.
--usage
    Synonym for help.
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| File locations |
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--infile
    Name of the input file containing the table of data.
    This file must conform to the format in the README file.
--outfile
    Optional. Name of the output file, if not specified outfile name will be
    derived from the infile name.
--id2info
    Optional. Name of the file containing a mapping of gene id's to names
    or descriptions.
--id2url
    Optional. Name ot the file containing a mapping of gene id's to urls.
--id_filter_file
    If you just want to run the algorithm on a subset of the genes in your
    data file, you can put the id's for those genes in a file, one per line,
    and specify that file with this option.
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| Output Options |
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--output_gene_confidence_list
    Optional.  Set this to output a tab delimited file that maps every gene to
    its confidence of differential expression.
--output_text
    Optional.  Set this to output the results also in text format.
--note
    Optional. A string that will be included at the top of the output file.
--aux_page_size
    Optional.  A whole number greater than zero.  This specifies the minimum
    number of tags there can be in one pattern before the results for that
    pattern are written to an auxiliary page (this keeps the main results page
    from getting too large).  This argument is optional, the default is 500.
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| Study Design and Nature of the Input Data |
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--num_channels
    Is your data one or two channels?  (note: Affymetrix is considered one
    channel).
--design
    For two channel data, either set this to "R" for "reference" design,
    or "D" for "direct comparisons" (see the documentation for more
    information on this setting).
--data_is_logged
    Use this option if your data has already been log transformed.
--data_not_logged
    Use this option if your data has not been log transformed.
--paired
    The data is paired.
--unpaired
    The data is not paired.
--missing_value
    If you have missing values designated by a string (such as "NA"), specify
    that string with this option.  You can either put quotes around the string
    or not, it doesn't matter as long as the string has no spaces.
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| Statistics and Parameter Settings |
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--level_confidence
    A number between 0 and 1.  Generate the levels with this confidence.
    See the README file for more information on this parameter.  This can
    be set separately for each group using --level_confidence_list (see
    below)
    NOTE: This parameter can be set at the end of the run after the program has
    displayed a summary breakdown of how many genes are found with what
    confidence.  To do this either set the command line option to "L" (for
    "later"), or do not specify this command line option and enter "L" when
    the program prompts for the level confidence
--level_confidence_list
    Comma-separated list of confidences.  If there are more than two
    conditions (or more than one direct comparision), each position in the
    pattern can have its own confidence specified by this list.  E.g. if
    there are 4 conditions, the list might be .8,.7,.9 (note four conditions
    gives patterns of length 3)
--min_presence
    A positive integer specifying the minimum number of values a tag should
    have in each condition in order to not be discarded.  This can be set
    separately for each condition using --min_presence_list
--min_presence_list
    Comma-separated list of positive integers, one for each condition,
    specifying the minimum number of values a tag should have, for each
    condition, in order not to be discarded.  E.g. if there are three
    conditions, the list might be 4,6,3
--use_logged_data
    Use this option to run the algorithm on the logged data (you can only
    use this option if using the t-statistic as statistic).  Logging the
    data usually give better results, but there is no rule.  Sometimes
    different genes can be picked up either way.  It is generally best,
    if using the t-statistic, to go with the logged data.  You might try
    both ways and see if it makes much difference.  Both ways give valid
    results, what can be effected is the power.
--use_unlogged_data
    Use this option to run the algorithm on the unlogged data.  (See
    --use_loggged_data option above for more information.)
--tstat
    Use the t-statistic as statistic.
--means
    Use the ratio of the means of the two groups as statistic.
--tstat_tuning_parameter
    Optional.  The value of the t-statistic tuning parameter.  This is set to
    a default value determined separately for each data set, but can be
    adjusted to possibly increase the power of the results.  See the
    documentation for more information on this parameter.
--shift
    Optional.  A real number greater than zero.  This number will be added to
    all intensities (of the unlogged data).  See the documentation for more on
    why you might use this parameter.
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| Configuration |
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--silent_mode
    Optional. Do not output warning messages or progress to screen.
--num_permutations
    Optional.  The number of permutations to use.  The default is to use all
    or 200, whichever is smaller.  You might want to lower it to increase the
    speed, though at a possible loss power or accuracy
--num_bins
    Optional.  The number of bins to use in granularizing the statistic over
    its range.  This is set to a default of 1000 and you probably shouldn't
    need to change it.