12 Parameter descriptions

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12 Parameter descriptions

This section alphabetically explains all the parameters that can be specified in an init file. Where appropriate, the type of the parameter and any default value is listed. The default values are automatically used by the program if the user does not specify any alternative setting. The `dump_parameters` option can be used to verify the default values. See Section 6.

The `drawmodel` and `prettyalign` programs do not use parameter files.

The SAM-T2K paramaters are discussed elsewhere. See Section 4.

The parameter reading routines will accept variations in capitalization and the presence or absence of underscores.

SAM supports reading compressed input files. If any of the file name arguments to the options end in a `.gz` or `.Z` extension. SAM will read the files using the appropriate decompression program. If an input file does not exist and does not have a `.gz` or `.Z` extension is not found, SAM will try to read from a compressed file with one of these extensions.

a2mdots (0 or 1) (1):
  By default (1), `align2model` will place dots in the sequence alignment to fill space need for other sequences' insertions. If set to 0, these dots are not printed. See Section 10.1.

adjust_score (0, 1 or 2) (2):
  If set, and local or semi-local scoring is performed, simple null model scores are adjusted according to the log of the model and sequence length (1) or log of the sequence length (2), so that final scores are somewhat independent of sequence length and/or model length. This parameter is used by `hmmscore`. See Section 10.2.4.

adpstyle (1, 4, or 5) (1):
  The dynamic programming style for alignment and multiple domain alignment used by `hmmscore` and `align2model`. Setting to 1 indicates Viterbi alignment, 4 indicates posterior-decoded alignment on transitions and character emissions, 5 indicates posterior-decoded alignment on only character emissions . If `adpstyle` is set for other than 1, 4, or 5, it is changed to 1 (Viterbi). See also the description of `dpstyle`. See Section 9.5, Section 10.1.2, and Section 10.2.5.

aligncheckonly (0 or 1) (1):
  If set and an `alignfile` is provided, `uniqueseq` will only thin based on `percentid` calculated according to the alignment, rather than first eliminating duplicate sequences and then thinning based on `percentid`. See Section 10.12.9.

alignfile (string) ():
  A file containing an alignment of sequences for use with `modelfromalign`, `uniqueseq`, and `sortseq`, or as an initial model for `buildmodel`. See Section 10.7. See Section 10.2.

align_fim (0 or 1) (0):
  Add FIMs to the ends of a model generated by `modelfromalign` or an alignfile in `buildmodel`. See Section 10.7.

alignment_weights (string) ():
  A file containing sequence weights for alignments used to form initial models with `buildmodel` or models with `modelfromalign`. The external weights have precedence over the internal ones, but a warning message will be generated unless `aweight_method` is set to zero. See Section 9.4.

alignshort (integer) (-1):
  When less than 0 (default), multiple domain search produces an alignment file that copies the entire sequence for each copy of the domain occurring within the sequence. When 0, only the region matching the model is printed. When greater than zero, that many characters to the left and the right of the domain are also printed to the file. In both cases, sequence IDs in the new file can be used to locate where the `hmmscore` found copies of the model. See Section 10.2.5.

alphabet (string) (protein):
  This system supports a variety of alphabets, the most common being DNA, RNA, and protein (use the `listalphabets` program to to see the remaining predefined alphabets). The protein alphabet is the default, and does not need to be specified. The abbreviation `a` may be used in place of `alphabet`. If unset, the first `train`, `test`, or `db` file is checked to see if the `alphabet` can be determined from the data. A comma-separated list of alphabets is required for using multi-track HMMs. The `alphabet_def` command may be used to define an alphabet. See Section 7.1, Section 10.2.6, and Section 10.12.1.

alphabet_def (string) ():
  The `alphabet_def` variable can be used to define an alphabet of 2 to 25 letters plus a (require) all-matching wildcard character. In the quoted string argument, both an alphabet name and the list of characters, with the wildcard last, must be specified. See Section 7.1.1.

alphbackfile (string) ():
  The `alphbackfile` can be used to specify a background proababilty file for an alphabet. Multiple files can be specified, each preceded by the `alphbackfile` designator. See Section 7.1.3.

anneal_length (float) (0.8):
  Indicates the speed with which noise should be decreased to zero. If greater than 1, decrease linearly over `anneal_length` re-estimates. If less than one, decrease exponentially. See Section 9.1.

anneal_noise (float) (5):
  Amount of noise to add to the model (decreased linearly or exponentially according to `anneal_length`. See Section 9.1.

auto_fim (0 or 1) (1):
  Cause `hmmscore` and `align2model` to automatically add FIMs to the model (and to the user's null model, if used) before scoring when null model subtraction is used or fully local scoring (`SW` is 2) is used. Also, in alignments, the FIM-induced delete state is automatically removed whenever `auto_fim` is set, regardless of whether or not FIMs were originally present in the model. See Section 10.2.

aweight_bits (float) (0.5):
  Target bits per column to save in determining alignment sequence weighting. See Section 9.4.3.

aweight_exponent (float) (0.5):
  Exponent in determining alignment sequence weighting. See Section 9.4.3.

aweight_method (0, 1, 2, or 3) (1):
  Internal weighting method for initial alignment provided to `buildmodel` or `modelfromalign`. 0 (none), 1 (karplus), 2 (henikoff), or 3 (flat). If non-zero and an `alignment_weights` file is specified, the external weights are used and a warning message is printed to standard error. See Section 9.4.3.

binary_output (0 or 1) (0):
  Tells model-generating programs to write models in text format if set to 0 or a binary format if set to 1. Default is text or 0. See Section 8.4.5.

calibrate (integer) (0):
  Perform model calibration in `hmmscore` either with random sequences or, when `db` is used, to a database of sequences. With a database, all sequences in the database are used for calibration with any non-zero setting of `calibrate`. With random sequences, if `calibrate` is set to 1, an internal default number of sequences is used; otherwise `calibrate` sequences are used. If `calibrate` is less than zero, that random or database sequences are scored, but calibration is not performed. With a database, the E-values reported are the newly-calibrated E-values. See Section 10.2.10.

constraints (string) ():
  Specify a constraints definition file to be read. This option maybe specified multiple times. See Section 9.7.

constraints_out (string) ():
  Specify the name for a constraints definition file to create. See Section 9.7.

constraints_from_align (0 or 1) (0):
  If a true value is specified, constraints will be be created for all aligned positions when a model is created from an alignment. See Section 9.7.

cutinsert (float) (0.5):
  If this fraction of sequences use an insert state, surgery will replaced with one or more match states. See Section 9.2.

cutmatch (float) (0.5):
  When fewer than this fraction of sequences use a match state, surgery will delete the state. See Section 9.2.

db (string) ():
  A file containing a database of sequences, to be scored against a model in `hmmscore` or aligned to a model in `align2model`, or for other purposes. Multiple instances of the `db` variable add to the list of database files, rather than replacing the previous `db` file name. A comma-separated list of parallel databases, one per track, is required for multi-track HMMs. The `id` and `not_id` options can be used multiple times to restrict processing to specific sequences. Probabilistic sequences are created if HMMs are provided as the `db` files, possible associated with `dbguide` guide sequences. See Section 10.2, Section 10.2.6, and Section 7.3.

dbguide (string) ():
  A file containing sequences of the same length as probabalistic sequences specified with `db`. This sequence will be used when generating alignments rather than the sequence of most probable letters of the probabalistic sequence. See Section 7.3.

dbsize (integer) (0):
  When greater than 0, this value is used in the calculation of E-values rather than the number of sequences that are read in to `hmmscore`. This is useful for correctly calculating E-values when multiple scoring runs are performed, and to avoid having to perform a complete reading of the database twice, once to calculate the number of sequences, and second time to score the sequences. See Section 10.2.

del_jump_conf (float) (1.0):
  Confidence in the regularizer for transitions leaving a delete state. The regularizer's transition values are multiplied by this number. See Section 8.1.

distfile (string) ():
  File with already-calculated sequence distances for use with the `makehist`, `makeroc`, `makeroc2`, and `sortesq` programs. See Section 10.2, Section 10.11, and Section 10.12.8..

distfile2 (string) ():
  A second file with already-calculated sequence distances for use with the `makehist`, `makeroc` or `makeroc2`. See Section 10.11.

dpstyle (0, 1, 2, 3, 4, or 5) (0):
  Flavor of internal dynamic programming for scoring and training. 0 indicates forward-backward (see `adpstyle` for alignment). (EM) sum-of-all-paths, 1 indicates Viterbi single best path, 2 indicates EM with the posteriors saved in a `.pdoc` file, 3 (for use with `grabdp`, but presently identical to 0) indicates EM outputting the frequency counts of each sequence in its own `.freq` file, 4 indicates most probable alignment (posterior-decoded alignment on transitions and emissions), and 5 indicates most probable alignment (posterior-decoded alignment on emissions only). See Section 9.5, Section 10.2, and Section 10.1.

dump_match_probs (0 or 1) (0):
  When the `grabdp` program is run with this flag set, it generates an RDB file listing the amino acid posterior probabilities for each node, and the amino acid priors. Priors are listed with the node label ``FREQAVE''.

dump_parameters (0, 1, or 2) (0):
  Normally, only modified parameters are printed to the output file. If this is set to 1, all parameters are printed. If 2, and specified alone on the command line, `buildmodel` and `align2model` will dump parameters and exit. Because in this case an alphabet is not specified and a regularizer not created, a setting of 2 will not reveal the default regularizer. See Section 8.4.

Emax (float) (0.001):
  When a selection variable includes 4 in its binary representation, `Emax` is used to determine what sequences are selected. Also, when `select_score/seq`, sequences with an E-value better than `Emax` are selected. See Section 10.2.

family_base_file (string) ():
  If non-null, and `sequence_weights` and `family_specific` are specified, initial models are read in from the files whose names are created by appending `.i.mod`, where `i` is an integer corresponding to the family number. For example, if there are three families and the base name is `test`, the family models will be read in from `test.0.mod`, `test.1.mod`, and `test.2.mod`. The first model in the file (of any type, including MODEL, REGULARIZER, NULLMODEL, and FREQUENCIES) is used. An error will result if the models are of different lengths. See Section 9.4.

FIM_method_train (0, 1, 2, 3, 5, 6) (-1):
  During the model building process, one may employ an initial model that contains FIMs. The table probabilities can readily be changed to reflect different distributions. Negative values only cause changes to the tables when models are created by the program, rather than being read in. The default setting of -1 uses the letter frequencies in the training set when generating new models. See Section 8.6.

FIM_method_score (0, 1, 2, 3, 5, 6) (-6):
  Similar to `FIM_method_train`, except that the insert probabilities in the FIMs are changed before sequences are scored against the model. Negative values only cause changes when FIMs are added to the model. When set to 0, it is treated as for adding FIMs. The default method of -6 uses the geometric average of match state probabilities. See Section 10.2.1.

fimstrength (float) (1.0):
  A factor by which to multiply the FIM letter emission probabilities. If set to 2.0, for example, each letter will have twice the probability of being generated as in the normalized insert state. This can be used to encourage the use of FIMs. The value is also applied to simple null models. When set to a value less than 0, the absolute value of `fimstrength` is applied to all insert states, FIM or otherwise. See Section 8.5.

fimtrans (float) (1.0):
  When 0.0, the FIM's insert to insert probability is 1.0. When greater than 0.0, a factor by which to multiply the model's geometric average match to match probability to produce the FIM's insert-to-insert probability. When less than 0.0, the FIM is adjusted as according to the absolute value of `fimtrans`, and the non-FIM insert-to-insert probability is set to , where is the regularized and normalized frequency counts for the transition and is the FIM insert-to-insert transition. See Section 8.5.

firstsequence (integer) ():
  Name of a sequence database, the first sequence of which will be aligned to the model as a guide sequence in `fragfinder`. See Section 10.4.

fisher_feature (string) (match_prior simple):
  Specifies the type of Fisher score vector features the `get_fisher_scores` will be generated. The following value are valid. This parameter maybe specified multiple times.
  - `trans` - Compute gradients from the model transition parameters.
  - `insert` - Compute gradients from the model insert parameters.
  - `match` - Compute gradients from the model match parameters
  - `match_prior` - Compute gradients from a mixture decomposition of the model match parameters with the prior library use to train the model.
  - `simple` - Include the simple NLL-NULL score as a feature.
  If this parameter is not explictly specified, `match_prior` and `simple` are used. See Section 10.6.

fracinsert (float) (1.0):
  When an insert state is being replaced, surgery will replace it with the average number or characters generated by the insert state multiplied by this number. See Section 9.2.

FREQUENCIES () ():
  A model structure that has frequency counts rather than probabilities. Output by `buildmodel` if the `print_frequencies` parameter is set to 1. The `drawmodel` program is the only program that can use frequencies as input. See Section 8.4..

fraglen (integer) (10):
  Length of fragments for `fragfinder` to produce for each model match state. See Section 10.4.

genprot_prior (string) (rsdb-comp2.32comp.gen):
  Dirichlet mixture for randomly generated protein sequences output by `genseq` and used in HMM model calibration. See Section 10.12.3 and Section 10.2.10.

genehl2_prior (string) (t99-2d-comp.9comp.gen):
  Dirichlet mixture for randomly generated secondary structure alphabet EHL2 sequences output by `genseq` and used in HMM model calibration. See Section 10.12.3, Section 10.2.10, and Section 7.1.

genebghtl_prior (string) (t99-ebghtl-comp.9comp.gen):
  Dirichlet mixture for randomly generated secondary structure alphabet EHL2 sequences output by `genseq` and used in HMM model calibration. See Section 10.12.3, Section 10.2.10, and Section 7.1.

gs_mean_log_len (float) (5.4151):
  Logarithm of mean sequence length used for randomly generated protein sequences output by `genseq` and used in HMM model calibration. See Section 10.12.3 and Section 10.2.10.

gs_sd_log_len (float) (1.03632564):
  Logarithm of standard deviation of sequence length used for randomly generated protein sequences output by `genseq` and used in HMM model calibration. See Section 10.12.3 and Section 10.2.10.

histbins (integer) (10):
  Number of bins used by the `makehist` program. See Section 10.11.1.

id (string) ():
  A sequence identifier, used to restrict `align2model` or `hmmscore` to only considering specific sequences. Multiple occurrences of the `id` parameter are added to the list of sequence identifiers, rather than replacing the value of `id`. The `not_id` command is used to exclude sequences, and has precedence over `id`.

initial_noise (float) (-1.0):
  When greater than zero, amount of noise to add for the first iteration. See Section 9.1.

ins_jump_conf (float) (1.0):
  Confidence in the regularizer for transitions leaving an insert state. The regularizer's transition values are multiplied by this number. See Section 8.1.

insconf (float) (10000):
  Confidence in the regularizer for character probabilities in an insert state. The high default means that the regularizer will overpower the actual counts determined by aligning sequences to the model. The regularizer's character insert values are multiplied by this number. See Section 8.1.

insert (string) ():
  Insert another parameter file. The single character `i` may be used in place of `insert`. See Section 6.

insert_file_dna (string) ():
  Insert another parameter file if the current alphabet has been set to DNA. This is particularly useful for alphabet-specific regularizers. See Section 6.

insert_file_protein (string) ():
  Insert another parameter file if the current alphabet has been set to protein. This is particularly useful for alphabet-specific regularizers. See Section 6.

insert_file_rna (string) ():
  Insert another parameter file if the current alphabet has been set to RNA. This is particularly useful for alphabet-specific regularizers. See Section 6.

Insert_method_train (0, 1, 2, 3, 5) (-1):
  Similar to `FIM_method_train` except that the insert probabilities are changed in the nodes that are not FIMs. Negative values only cause changes to the tables when models are created by the program, rather than being read in. The default method -1 uses the letter frequencies in the training set when generating models. If the model or regularizer includes a GENERIC node, then its match and insert tables are also filled in with these values. See Section 8.6.

Insert_method_score (0, 1, 2, 3, 5, 6) (0):
  Similar to `FIM_method_score` except that the insert probabilities are changed in the nodes that are not FIMs. Negative values only cause changes to the tables when models are created by the program, rather than being read in. The default method 0 is to not change the insert tables during scoring. See Section 10.2.1.

internal_weight (0, 1, 2) (1):
  Use internal maximum discrimination sequence weighting. Automatically turned off if not explicitly set and external weights are used. See Section 9.4.4.

jump_in_prob (float) (1.0):
  The probability cost of jumping into the center of the model when the `SW` option is set. See Section 10.2.4.

jump_out_prob (float) (1.0):
  The probability cost of jumping out of the center of the model when the `SW` option is set. See Section 10.2.4.

keepannotations (0, 1) (1):
  Keep sequence annotations for sequence output. Short versions of the annotations are included in distance files as well. Annotations are frequently longer than the sequences themselves, so setting this to 0 can save considerable amounts of memory.

kestrel_fallback (0 or 1) (1):
  Enables or disables fallback into sequential mode if a Kestrel is board is not available after the specified number of retries or if features not implemented on Kestrel are requested. See Section 10.2.

kestrel_min_model_len (integer) (0):
  Specifies the minimum model length to use with Kestrel implementation of `hmmscore` EM scoring. Models smaller than this value will be be scored using the sequential algorithm. This is useful as small models may be slower on Kestrel. See Section 10.2.

kestrel_remote_db_dir (integer) ():
  Specifies the remote directory containing the sequence databases in Kestrel format. This should be in Windows-NT syntax, for example `\\merlin\data`. See Section 10.2.

kestrel_retry_cnt (integer) (0):
  Specifies the number of times to retries if a Kestrel board is not available. See Section 10.2.

kestrel_retry_time (integer) (0):
  Specifies the number of seconds to wait between retries when Kestrel board is not available.

kestrel_use_simulator (integer) (0):
  Use the Kestrel simulator. This is useful when debugging the SAM Kestrel code. The number of simulated PEs will be set to the minimum required to hold the model. See Section 10.2.

kestrel_num_extra_pe (integer) (0):
  When using the Kestrel simulator for debugging SAM, increase the number of simulated PEs by the specified number. See Section 10.2.

kestrel_dual_mapping (integer) (-1):
  Used for debugging Kestrel dual mapping code. When set to -1, dual mapping is selected if the model will fit in Kestrel PE array. If 0, then the dual mapping algorithm is never used. If 1, then the dual mapping is always used with an error generated if the model will not fit. See Section 10.2.

lambda (float) (1.0):
  Scaling factor for HMM e-value calculations. Best set using the `calibrate` option of `hmmscore`. For `pathprob` output scaling use `ppscale`, and for Smith & Waterman E-value scoring, use `swlambda`. See Section 10.2.10.

logo_auto_size (0/1) (0):
  Set to 1 to resize the logo to a single 8.5 by 11 page. See Section 10.10.4.

logo_bars_per_line (integer) (0):
  Number of bars per line. Default setting of 0 allows variance for cosmetic reasons. See Section 10.10.4.

logo_bw (0/1) (0):
  If set to 1, make a black and white logo, ignoring color information. See Section 10.10.4.

logo_captions (filename) ():
  A file of captions. Each caption has two integers (start and end bars) on one line, and the caption on the following line. Captions can overlap, in which case they will be stacked on the final logo. See Section 10.10.4.

logo_captionf (filename) ():
  Captions as above, but taken from a sequence file. Each of the first `logo_captionf_manyseq` sequences has its own line on the logo. After these lines, captions from any `logo_captions` file will be displayed. Each run of identical characters will be collapsed into a single caption. Intended for secondary structure (see `logo_captionf_ignoreCL` and `logo_captionf_numseq`, below). See Section 10.10.4.

logo_captionf_ignoreCL (integer) (1):
  If non-zero, ignore `C' and `L' characters in the sequence-based caption file (see `logo_captionf`. See Section 10.10.4.

logo_captionf_numseq (integer) (1):
  Number of sequences from the `logo_captionf` file to process. If 1, the default, only the first sequence is used to label the logo. See Section 10.10.4.

logo_captionf_color (filename) ():
  Colors for the caption FASTA format file `logo_captionf`. Normally installed files include protein.colors, nucleotide.colors, and stride.colors. If not specified, black will be used. See Section 10.10.4.

logo_color_file (filename) ():
  Color file for the characters. Internal defaults exist for protein, nucleotide, and secondary structure. Each line has a character and 3 RGB numbers between 0.0 and 1.0, inclusive, but, not more than 9 characters. The pound sign (#) is a comment indicator. See Section 10.10.4.

logo_font (fontname) (Courier):
  Postscript font for logo letters. See Section 10.10.4.

logo_savings (filename) ():
  Use a bit savings file for logo creation rather than a SAM modelfile. Savings files have one line per bar of: (bits label percentage label percentage ... newline) where `bits' is the total bar heigth, labels are single characters, and percentages are of the bar height. See Section 10.10.4.

logo_scale (float) (20.0):
  Vertical scale in points per bit of the logo. See Section 10.10.4.

logo_sections (string) ():
  A string (e.g. `"3-8,12,15"`) indicating which bars to display. See Section 10.10.4.

logo_sig_height (float) (1.0):
  Height in points of smallest charector other than X to display. See Section 10.10.4.

logo_start_num (integer) (1):
  The sequence index of the first bar in the logo. HMM files (`modelfile`), `logo_captionf`, and `logo_under_file` are all automatically adjusted to start with this index. Bar indices in `logo_sections`, `logo_caption`, and `logo_savings` are not adjusted by this amount. See Section 10.10.4.

logo_title (string) (runname):
  Title of the logo. Default is the current runname. See Section 10.10.4.

logo_title_font (fontname) (Times-Roman):
  Postscript font for the logo title. See Section 10.10.4.

logo_under_file (filename) ():
  A file with one FASTA-format sequence, to provide lablels, such as amino acid names in a sequence, one character per logo bar. Useful for visually comparing a sequence and a model. See Section 10.10.4.

logo_under_color (filename) ():
  A color file for use with the underfile sequence. Normally installed files include `protein.colors`, `nucleotide.colors`, and `stride.colors`. If not specified, black will be used. PRIOR_PATH is searched for the file if not in the current directory. See Section 10.10.4.

max_seq_length (integer) (2500):
  Used to specify maximum sequence length for Kestrel database processing and the maximum sequence length for `splitseq` database splitting. See Section 10.12.6.

mainline_cutoff (float) (0.5):
  Changing this value will set both `cutmatch` and `cutinsert` to the new value. See Section 9.2.

many_files (0-15) (0):
  When zero, all the output of `buildmodel` is sent to the `.mod` file. If the binary expansion of `many_files` includes a `1' (e.g., is odd), `buildmodel` will create multiple files for the probability model, frequency model, and the run statistics. If the binary expansion of `many_files` includes a `2' (e.g., 2, 3, 6, 7, 10, 11, 14, 15), the `hmmscore` score information (.dist) is sent to standard output. If the binary expansion of `many_files` includes a `4' (e.g., 4, 5, 6, 7, 12, 13, 14, 15), the `hmmscore` multiple domain score information (.mstat) is sent to standard output. If the binary expansion of `many_files` includes an `8' (e.g., 8, 9, 10, 11, 12, 13, 14, 15), `hmmscore` will name model library distance files using only the model name listed in the model libarary, rather than a combination of the runname, model name, and position within the model libarary. See Section 5, Section 10.2.3, and Section 10.2.5.

match_jump_conf (float) (1.0):
  Confidence in the regularizer for transitions leaving a match state. The regularizer's transition values are multiplied by this number. See Section 8.1.

matchconf (float) (1.0):
  Confidence in the regularizer for character probabilities in a match state. The regularizer's character match values are multiplied by this number. This variable is ignored if a prior library is used. See Section 8.1.

maxinserts (integer) (100):
  In buildmodel, the maximum number of states inserted after any node by the surgery. See Section 9.2.

maxmem (integer) (0):
  Maximum size of dynamic programming array to use for training and alignment. See Grice, Hughey, and Speck, and Tarnas and Hughey CABIOS papers for more information on the algorithm used. Depending on system configuration, performance may increase with higher values. If set to zero (the default), SAM will always use the smallest possible amount of space.

maxmodlen (integer) (0):
  When starting with multiple, randomly generated models, the longest model to use. If set to 0 (the default), the value is calculated as 10% above the average sequence length when needed. See Section 8.4.1.

maxposdecodemem (integer) (100000000):
  Maximum amount of memory, in bytes, to allocate for posterior-decoded alighments. These alignments require space proportional to the product of the sequence length and the HMM length. Sequences that are too long will be aligned using the Viterbi algorithm. See Section 10.1.

mdNLLnull (float) (-10.0):
  Criterion by which subsequences are judged to be matches to a single motif (model) during a multiple domain alignment if there is a 1 in the bit pattern of `select_md`. All occurrences for which NLL-NULL is better than the specified value are considered matches. See Section 10.2.5.

mdNLLcomplex (float) (-10.0):
  Criterion by which subsequences are judged to be matches to a single motif (model) during a multiple domain alignment if there is a 2 in the bit pattern of `select_md`. All occurrences for which NLL-NULL user's null or reverse null model score is better than the specified value are considered matches. See Section 10.2.5.

mdEmax (float) (0.01):
  Criterion by which subsequences are judged to be matches to a single motif (model) during a multiple domain alignment if there is a 4 in the bit pattern of `select_md`. All occurrences for which reverse sequence null model e-value is better than the specified value are considered matches. See Section 10.2.5.

minmodlen (integer) (0):
  When starting with multiple, randomly generated models, the shortest model to use. If set to 0 (the default), the value is calculated as 10% below the average sequence length when needed. See Section 8.4.1. See Section 8.4.1.

MODEL () ():
  Specify an initial model. See Section 8.4..

model_abort_length (integer) (10000):
  In `buildmodel`, if the initial model length is greater than this number, an error message is printed and the program is aborted. This is to avoid giant models that will never complete training because of their memory or execution time requirements.

model_file (string) ():
  If non-null, this file is read for an initial model. The first model in the file (of any type, including MODEL, REGULARIZER, NULLMODEL, and FREQUENCIES) is used. This will override any models present in inserted files. See Section 5.

modellength (integer) (-1):
  When greater than 0, sets the model length to a specific value in `buildmodel`. (overridden if a model or regularizer without a GENERIC node is present). If equal to 0 and `maxmodlen` is less than 1, all model lengths are set to the average length of the training sequences. If less than 0, model length(s) are set to a random value between `minmodlen` and `maxmodlen` according to `randseed`. These two bounds will default to 90% and 110% of average sequence length if `maxmodlen` is less than 1. See Section 8.4.1.

model_library (string) ():
  Specify a library of models for scoring or calibration. See Section 10.2.10.

modlib_absolute (0/1) (1):
  Use absolute path names when creating a model library file. See Section 10.2.10.

Motifcutoff (float) (0.5):
  In multiple motif search, fragments which are smaller than this fraction of the model length are not considered for further processing. Further, processing stops if a fragment of length less than the square of `Motifcutoff` is the best match (this is needed when using SW scoring with weak thresholds). See Section 10.2.5.

NLLnull (float) (-10.0):
  If a selection variable is odd, this value is checked against a sequence's simple null model score. See Section 10.2.

NLLcomplex (float) (-10.0):
  If a selection variable includes 2 in its binary representation, this value is checked against a sequence's user or reverse sequence null model score. See Section 10.2.

NLLfile (string) ():
  Alias for `distfile`.

NLLfile2 (string) ():
  Alias for `distfile2`

Nmodels (integer) (3):
  Multiple initial models can be trained simultaneously, with the best one being used for surgery and further training. See Section 8.4.1.

not_id (string) ():
  A sequence identifier, used to eliminate a specific sequecne from consideration by `align2model` or `hmmscore`. Multiple occurrences of the `not_id` parameter are added to the list of sequence identifiers, rather than replacing the value of `not_id`. The `not_id` command is used to exclude sequences, and has precedence over `id`.

NscoreSeq (integer) (100000):
  Maximum number of sequences to be read by the `hmmscore` or `align2model` program.

Nseq (integer) (10000):
  Maximum number of sequences to be read from any of the up to four sequence files or a database files in `buildmodel`. See Section 7.4.

nsurgery (integer) (3):
  Maximum number of surgeries to perform. Each surgery will result in a full EM cycle until `stopcriterion` or `reestimates` is reached.

Ntrain (integer) (0):
  Number of sequences to train on. If zero, all sequences that were read from the files `train` and `train2` (up to a limit of `Nseq` per file) form the training set. If `Ntrain` is greater than than the number of sequences read in from the files `train`, `train2`, `test`, and `test2`, all sequences are used for training. If `Ntrain` is less than the total number of sequences read in from the four files, all the sequences are randomly partitioned (using `trainseed`) into the training set with `Ntrain` sequences, and of the remaining sequences (i.e., whether or not a sequence occured in a training file or a test file is ignored). See Section 7.4.

nucleotide_prior (string) ():
  The prior library to use if the RNA or DNA sequences are being modeled and `prior_library` has not been set. See Section 8.1.

NULLMODEL () ():
  Identifies a user defined null model in a model file. The parameter `subtract_null` must be set to 3 to use this null model. See Section 10.2.

nullmodel_file (string) ():
  If non-null, this file is read for a user's null model. The first model in the file (of any type, including MODEL, REGULARIZER, NULLMODEL, and FREQUENCIES) is used. This will override any null models present in inserted files. To use this null model, `subtract_null` must be set to 3. See Section 5.

null_score_weight_scale (float) (10.0):
  Used with `get_fisher_scores` to weigh a sequences Fisher scores by how closely they match the model. If non-zero weigh the gradients according to the sequence NLL-NULL score, scaled by this parameter. Each gradient is multiplied by `sigmoid(-score/null_score_weight_scale)`, where `sigmoid` is the logistic function. See Section 10.6.

numpermatch (integer) (5):
  Number of fragments for `fragfinder` to produce for each model match state. See Section 10.4.

percent_id (float) (1.0):
  For alignments passed to `uniqueseq`, specifies fraction identity to use for deleting sequences. If `percent_id` is negative, a message is printed about each sequence that is dropped. See Section 10.12.9.

plotcolumn (integer) (3):
  Column of score file to use in calculating plots. Length (0), simple null model (1), complex or reverse null model (2), or Evalue (3). See Section 10.11.

plotleft (float) (0.0):
  Lowest X axis value on a graph generated by `gnuplot`. The X axis is calculated internally if `plotleft`=`plotright`. Used in conjunction with `makehist`, `makeroc` and `makeroc2`. See Section 10.11.

plotline (float) (0.0):
  Creates a vertical line at this value in a graph generated by `gnuplot` if plotline is nonzero. Used in conjunction with `makehist`, `makeroc` and `makeroc2`. See Section 10.11.

plotmax (float) (0):
  Highest Y axis value on a graph generated by `gnuplot`. The Y axis is calculated internally if `plotmax`=`plotmin`. Used in conjunction with `makehist`, `makeroc` and `makeroc2`. See Section 10.11.

plotmin (float) (0):
  Lowest Y axis value on a graph generated by `gnuplot`. The Y axis is calculated internally if `plotmax`=`plotmin`. Used in conjunction with `makehist`, `makeroc` and `makeroc2`. See Section 10.11.

plotnegate (int) (0):
  Negates the scores on a graph generated by `gnuplot` if set to 1. Used in conjunction with `makehist`, `makeroc` and `makeroc2`. See Section 10.11.

plotps (int) (1):
  Creates a postscript file runname.ps if set to 1. When set to 0, only a .plt file is generated. A square plot postscript file is generated for a setting of 2. For options 1 and 2, the .data and .plt files used to create the postscript file are deleted. When set to 3, the postscript file is generated and the .data and .plt files are retained. Used in conjunction with `makehist`, `makeroc` and `makeroc2`. See Section 10.11.

plotright (float) (0.0):
  Highest X axis value on a graph generated by `gnuplot`. The X axis is calculated internally if `plotleft`=`plotright`. Used in conjunction with `makehist`, `makeroc` and `makeroc2`. See Section 10.11.

ppscale (float) (1.0):
  Scaling factor for `pathprobs` output scaling. For `hmmscore` E-value scoring use `lambda` or `swlambda`. See Section 10.8.

pptrim (float) (0.0):
  If greater than 0, posterior threshold for turning match states into insert states in the creation of a trimmed alignment (.ta2m) in the `pathprobs` program. See Section 10.8.

print_all_models (0 or 1) (0):
  When set, models are printed after each iteration of the forward-backward procedure. Models are printed to files of the form `runname.a.mrrr.mod`, where `mrrr' is the catenation of the number of the model (or 1 if only one model is being estimated at a time) and the re-estimate number. This variable can be toggled at runtime by sending a `SIGUSR2` signal to the program, providing a means to look at intermediate results while the program is running or checkpointing a program run.

print_all_weights (0 or 1) (0):
  When set, a weight output file is generated after each iteration of the forward-backward procedure. Weights are printed to files of the form runname1.weightoutput, where `1' is the number of the iteration.

print_frequencies (0 or 1) (0):
  If this option is set, the frequency counts for each state will be printed as well as the model.

print_surg_models (0 or 1) (0):
  When set, models are printed after each surgery (surgery occurs after a sequence of EM re-estimates). Models are printed to files of the form `runname.s.rr.mod`, where `rrr' is the re-estimation index for the run. When surgery is used, a single winning model is automatically selected after the first EM re-estimation loop if multiple initial models are used. This variable can be toggled at runtime by sending a `SIGUSR1` signal to the program.

prior_library (string) ():
  When set, use Dirichlet mixture priors to regularizer the models. Transition costs and insert states are still regularized by the default (or specified) regularizer, but match states are regularized with Dirichlet mixtures. The `matchconf` variable is ignored if a prior library is used, in favor of the `prior_weight` variable. If `prior_library` is not set and `protein_prior` or `nucleotide_prior` is set, the indicated prior library is used. If neither is set, and proteins are being modeled, and internal default prior library is used. See Section 8.1.

prior_weight (float) (1.0):
  Weight of the prior library, if it is used. See Section 8.1.

protein_prior (string) ():
  The prior library to use if the proteins are being modeled and `prior_library` has not been set. If not set, and proteins are being modeling, an internal default will be used. See Section 8.1.

query (string) ():
  Sequence file, the first sequence of which is used as a Smith and Waterman query. A Smith and Waterman model is built from this single sequence and scored against the database in `hmmscore`. See Section 10.2.8.

randseed (integer) (-1):
  Random seed for noise generation and for selection of initial model lengths if `modellength` is less than one. The default value causes the process's pid to be used, which will then be printed to the output file to enable replication of results.

rdb (0 or 1) (0):
  Create the score file in RDB format with the extension `.dist-rdb` rather than the standard `.dist` format. See Section 10.2.

randomize (integer) (5):
  Determines how noise is added to the model. See Section 9.1.

read_smooth (0 or 1) (0):
  Tells `hmmscore` whether or not to read a smooth curve from `smooth_file`, or its default (`runname.smooth`). See Section 10.2.

reestimates (integer) (40):
  Maximum number of re-estimates to perform after a surgery. Generally, this should be set higher than the number of iterations that have noise. See Section 9.

reglength (integer) (-1):
  Similar to `modellength`, sets the length of the regularizer. Usually not needed. See Section 8.4.1.

REGULARIZER () ():
  Specify an initial regularizer. See Section 8.4.

regularizer_file (string) ():
  If non-null, this file is read for a single-component regularizer. The first model in the file (of any type, including MODEL, REGULARIZER, NULLMODEL, and FREQUENCIES) is used. This will override any regularizers present in inserted files. See Section 5.

rerun (integer) (-1):
  The program optimizes Nmodels models until the first `surgery', and then continues with the best one. Sometimes it is interesting to see how the second best would have done. If the second best is number 4 (starting from 0!), a setting this parameter to 4 would optimize that model. Models can also be accessed using one `print_all_models`.

retrain_noise_scale (float) (0.1):
  If an initial model or alignment is passed to buildmodel, `initial_noise` (or `anneal_noise` if `initial_noise is unspecified`)is scaled by this multiplier, which must be between 0.0 and 1.0. See Section 9.1.

segments (integer) (1):
  Number of segments `hmmscore` should logically split database into. Segmentation is based on number of sequences. See Section 10.2.7.

segment_number (integer) (1):
  Segment number among segments. See Section 10.2.7.

segment_size (integer) (1000):
  Number of sequences read in at a time and given to one of the segments. See Section 10.2.7.

select_align (integer) (0):
  Tells `hmmscore` what selection criteria should be used for placing aligned sequences into the file `runname.a2m`. If 0, no sequences are selected; if 1, sequences are selected according to their simple null model scores and `NLLNull`; if 2, sequences are selected according to their complex, user, or reverse sequence null model score and `NLLcomplex`; if 4, sequences are selected according to their E-values and `Emax`; if 8, all sequences are selected. Selection criteria can be combined: 3 requires sequences to score better than `NLLnull` with the simple null model and `NLLcomplex` with the complex (user's or reverse sequence) null model. Negative numbers indicate that sequences that do not pass the corresponding positive test should be selected. See Section 10.2.

select_mdalign (integer) (0):
  Tells `hmmscore` what selection criteria should be used for performing a multiple domain check on a scored sequence. Sequences that pass the `select_mdalign` criteria are analyzed and recorded if they pass the `select_md` criteria during the mult-domain Viterbi alignment pass. Once sequences have been selected using the `select_mdalign` parameter, the multiple domain seearch procedure is controlled by `select_md` and related parameters. Set to 8 to perform a multiple domain alignment for every sequence. See Section 10.2.

select_md (integer) (1):
  Tells `hmmscore` what selection criteria should be used treating a multiple domain alignment as found, in which case the alignment is written to `runname.mult` with scores in `runname.mstat`. The multiple domain search procedure is only performed on seqeunces that have satisfied the `select_mdalign` criterion in `hmmscore`. Functions as with `select_align` with the variables `mdNLLnull`, `mdNLLcomplex`, and `mdEmax`. Only sequences that pass the selection criteria (which is always based on Viterbi scores) are recorded in the files. The default is to require passing the simple null model test. It does not make sense to set this parameter to 8. See Section 10.2.5.

select_score (integer) (8):
  Tells `hmmscore` what selection criteria should be used for listing sequence scores in the file `runname.dist`. Functions as with `select_align`. See Section 10.2.

select_seq (integer) (0):
  Tells `hmmscore` what selection criteria should be used for placing sequences in the file `runname.sel`. Functions as with `select_align` See Section 10.2.

sequence_models (float) (0.0):
  Build initial models from randomly-selected sequences in the training set when greater than zero. Value indicates the weight the sequence should have when combined with the regularizer. See Section 8.3.

sequence_warning (integer) (0):
  Primarily for debugging. Set to to print out all sequences in which a `wrong' letter was found, or to to print out all sequences.

sequence_weights (string) ():
  File to read for sequence weights. See Section 9.4.

simple_threshold (integer) (0):
  User and reverse sequence scores will not be calculated by `hmmscore` unless the simple null model score is less than this number. Set to 10000 to require all scores to be calculated. See Section 10.2.1.

sort (integer) (4):
  Indicates whether or not sequence scores should be sorted by `hmmscore`. With a value of 1, sequences are sorted by column 1 (simple null model score). With a value of 2, sequences are sorted by column 2 (other null model selections; see `subtract_null`). With a value of 4, sequences are sorted by E-value if available or by column 1. When negative, scores are sorted in reverse order, worst first. When 0, scores are not sorted.

  `Sort` also indicates whether or not `checkseq` should sort sequence IDs and sequences to check for uniqueness. This sorting requires storing all sequences in memory, so can be quite time consuming.

  See Section 10.2 and Section 10.12.2.

stopcriterion (float) (0.1):
  The re-estimation loop will stop whenever the improvement in the NLL score is less than this number (provided noise is less than 10% of its original value for that iteration), or when the maximum number of `reestimates` is reached. See Section 9.

subtract_null (integer) (4):
  In `hmmscore` and other programs, decides the type of null model to be used. In score files, this will be the second score column (the first is always the simple null model). When set to 0, raw scores are reported in the second column. Setting to 1 provides simple null model scores; to 2, issues a warning and uses the simple null model; to 3, user's input null model; to 4, the reverse sequence null model; and to 5, the scaled reverse sequence null model.

surgery_noise_scale (float) (0.1):
  After the first surgery, `anneal_noise` is scaled by this multiplier, which must be between 0.0 and 1.0. See Section 9.1.

surgfile (string) ():
  A sequence file in a2m alignment format to be used for guiding model surgery. On each surgery step, the sequence is aligned to the model, and model nodes are deleted or inserted to ensure to match the alignment given in surgfile. Optionally, `id` may be used to specify a specific sequence within `surgfile`, otherwise the first sequence will be used. See Section 9.2.

SW (integer) (2):
  When set to 0, `hmmscore`, `buildmodel`, and other programs use model to sequence (global) dynamic programming. When set to 1, SAM programs use submodel to sequence (semilocal) scoring . When set to 2, SAM programs use submodel to subsequence (local) scoring. When set to 3, SAM programs use model to subsequence (domain) scoring. Ignored in Smith and Waterman (`query`) mode. See Section 10.2.4.

swlambda (float) (0.34657):
  Scaling factor for Smith and Waterman e-value calculation and for `pathprobs` single-digit scores. Default is , for base 2 (bit) scoring matrices for which a unit indicates a half-bit. Do not confuse with `ppscale` or `lambda`. See Section 10.2.8.

syncfile (string) ():
  In `buildmodel`, perform sequence-based surgery using the first sequence in this file (or an alternate if `id` is specified). The sequence should be an a2m alignment. See Section 9.2.1.

syncweight (float) (1.0):
  The sequence weight of a synchronization sequence. During the sequence surgery procedure, emission and transition counts are moved in the model. This variable indicates how much count should be treated as corresponding to the guide alignment during the surgery procedure. See Section 9.2.1.

test (string) ():
  A file to read test sequences from. See Section 7.4.
test2 (string) ():
  A second file to read test sequences from. See Section 7.4.

trackcoeff (string) ():
  A comma-separated list of floating-point track coefficients used to compine character emission scores in multi-track HMMs. See Section 10.2.6.

trackmod (string) ():
  A comma-separated list of model files specying a multi-track HMM. See Section 10.2.6.

trackprior (string) ():
  A comma-separated list of Dirichlet mixture priors to be used in model calibration of a single or multi-track HMM. Multiple tracks are generated independently. See Section 10.2.6 and Section 10.2.10.

trainseed (integer) (-1):
  Random seed for partitioning the sequences into the test set and the training set. The default value causes the process's pid to be used, which will then be printed to the output file to enable replication of results. See Section 7.4.

train (string) ():
  A file to read training sequences from. See Section 7.4.
train2 (string) ():
  A second file to read training sequences from. See Section 7.4.

train_reset_inserts (0,1,2,3, or 6) (6):
  At the end of `buildmodel` training, all insert and FIM character tables are set according to this variable, which takes on the same meanings as `FIM_method_train`. The default setting is to set all insert and FIM tables to the normalized geometric average of the match state costs. See Section 8.6.

trans_priors (string) ():
  The name of the structure-specific transition prior library to use when structural information for transition probability estimation is to be used for HMM estimation. See Section 8.1.2.

transweight (float) (1.0):
  A multiplier that affects the influence of the pseudocounts generated by the structure-specific transition priors. See Section 8.1.2.

template (string) ():
  For use with the structure-specific transition prior library. A three- column file (amino acid sequence, secondary structure, accessibility) that is used during HMM estimation to assign a structural environment to each model node. See Section 8.1.2.

use_kestrel (0 or 1) (0):
  If `1`, use the Kestrel implementation of the `hmmscore` scoring algorithm. See Section 10.2.

verbose (0 or 1) (0):
  If set to `1`, more diagnostic status messages are printed in some programs, including `hmmscore` and `uniqueseq`.

viterbi_threshold (integer) (10000):
  If changed from the default 10000, and the dynamic programming style is not Viterbi, sequences must first pass the `viterbi_threshold` for the Viterbi NLL-NULL score before being scored with the selected method. Because Viterbi scoring can be 2-5 times faster than EM-style scoring, this can lead to a considerable execution time savings. A typical use would be to set to, for example, 5 greater than the `simple_threshold` used for calculating the reverse null model score. See Section 10.2.1.

weight_final (float) (1.0):
  The final (steady-state) multiplier of sequence weights. The default (1.0) means that, if no sequence weight file is used, each sequence is weighted as being one sequence. If a weight file is used, all values in that file are multiplied by this value. See Section 9.4 and Section 9.1.

weight_length (float) (0):
  An annealing schedule for the sequence weight multiplier. If greater than 1.0, the weight multiplier is increased from zero linearly over `weight_length` re-estimates. If less than one, increase exponentially. See Section 9.4 and Section 9.1.

write_dist (0 or 1) (0):
  If a non-zero value is specified, `get_fisher_scores` will generate a `runname.dist-rdb` score file. See Section 10.6.

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