Provided by: infernal_1.1.5-3_amd64 
NAME
cmcalibrate - fit exponential tails for covariance model E-value determination
SYNOPSIS
cmcalibrate [options] cmfile
DESCRIPTION
cmcalibrate determines exponential tail parameters for E-value determination by generating random
sequences, searching them with the CM and collecting the scores of the resulting hits. A histogram of the
bit scores of the hits is fit to an exponential tail, and the parameters of the fitted tail are saved to
the CM file. The exponential tail parameters are then used to estimate the statistical significance of
hits found in cmsearch and cmscan.
A CM file must be calibrated with cmcalibrate before it can be used in cmsearch or cmscan, with a single
exception: it is not necessary to calibrate CM files that include only models with zero basepairs before
running cmsearch.
cmcalibrate is very slow. It takes a couple of hours to calibrate a single average sized CM on a single
CPU. cmcalibrate will run in parallel on four cores if Infernal was built on a system that supports
POSIX threading (see the Installation section of the user guide for more information) and that system has
at least 4 cores. Using <n> cores will result in roughly <n> -fold acceleration versus a single CPU. You
can specify the number of cores be <n> to use with the --cpu <n> option. MPI (Message Passing Interface)
can be also be used for parallelization with the --mpi option if Infernal was built with MPI enabled, but
using more than 161 processors is not recommended because increasing past 161 won't accelerate the
calibration. See the Installation section of the user guide for more information.
The --forecast option can be used to estimate how long the program will take to run for a given cmfile on
the current machine. To predict the running time on <n> processors with MPI, additionally use the
--nforecast <n> option.
Some large models require a lot of memory to calibrate. You can determine how much memory is required
with the --memreq option. For these models, you may be limited by the available RAM on your system.
Another strategy for parallelization that can be useful when a lot of memory is required per core is to
split the calibration into <n> separate computations or partitions, each of which can be performed
separately, potentially in parallel if you have access to a computer cluster. The results from each
computation can then be merged together for the final calibration. To do this, first run cmcalibrate with
the --split, --ptot <n> and --cfile <f> options, which will save the <n> separate partition commands into
the file <f> . After all of these commands have been executed, you can then combine the results and
create a calibrated model file by calling again with the --merge and --ptot <n> options. See the
"Parallelizing calibration of large models by splitting into partitions" subsection of the tutorial in
the user's guide for more information.
The random sequences searched in cmcalibrate are generated by an HMM that was trained on real genomic
sequences with various GC contents. The goal is to have the GC distributions in the random sequences be
similar to those in actual genomic sequences.
Four rounds of searches and subsequent exponential tail fits are performed, one each for the four
different CM algorithms that can be used in cmsearch and cmscan: glocal CYK, glocal Inside, local CYK and
local Inside.
The E-values parameters determined by cmcalibrate are only used by the cmsearch and cmscan programs. If
you are not going to use these programs then do not waste time calibrating your models.
OPTIONS
-h Help; print a brief reminder of command line usage and available options.
-L <x> Set the total length of random sequences to search to <x> megabases (Mb). By default, <x> is 1.6
Mb. Increasing <x> will make the exponential tail fits more precise and E-values more accurate,
but will take longer (doubling <x> will roughly double the running time). Decreasing <x> is not
recommended as it will make the fits less precise and the E-values less accurate.
OPTIONS FOR PREDICTING REQUIRED TIME AND MEMORY
--forecast
Predict the running time of the calibration of cmfile (with provided options) on the current
machine and exit. The calibration is not performed. The predictions should be considered rough
estimates. If multithreading is enabled (see Installation section of user guide), the timing will
take into account the number of available cores.
--nforecast <n>
With --forecast, specify that <n> processors will be used for the calibration. This might be
useful for predicting the running time of an MPI run with <n> processors.
--memreq
Predict the amount of required memory for calibrating cmfile (with provided options) on the
current machine and exit. The calibration is not performed.
OPTIONS CONTROLLING EXPONENTIAL TAIL FITS
--gtailn <x>
fit the exponential tail for glocal Inside and glocal CYK to the <n> highest scores in the
histogram tail, where <n> is <x> times the number of Mb searched. The default value of <x> is 250.
The value 250 was chosen because it works well empirically relative to other values.
--ltailn <x>
fit the exponential tail for local Inside and local CYK to the <n> highest scores in the histogram
tail, where <n> is <x> times the number of Mb searched. The default value of <x> is 750. The
value 750 was chosen because it works well empirically relative to other values.
--tailp <x>
Ignore the --gtailn and --ltailn prefixed options and fit the <x> fraction tail of the histogram
to an exponential tail, for all search modes.
OPTIONAL OUTPUT FILES
--hfile <f>
Save the histograms fit to file <f>. The format of this file is two space delimited columns per
line. The first column is the x-axis values of bit scores of each bin. The second column is the y-
axis values of number of hits per bin. Each series is delimited by a line with a single character
"&". The file will contain one series for each of the four exponential tail fits in the following
order: glocal CYK, glocal Inside, local CYK, and local Inside.
--sfile <f>
Save survival plot information to file <f>. The format of this file is two space delimited
columns per line. The first column is the x-axis values of bit scores of each bin. The second
column is the y-axis values of fraction of hits that meet or exceed the score for each bin. Each
series is delimited by a line with a single character "&". The file will contain three series of
data for each of the four CM search modes in the following order: glocal CYK, glocal Inside, local
CYK, and local Inside. The first series is the empirical survival plot from the histogram of hits
to the random sequence. The second series is the exponential tail fit to the empirical
distribution. The third series is the exponential tail fit if lambda were fixed and set as the
natural log of 2 (0.691314718).
--qqfile <f>
Save quantile-quantile plot information to file <f>. The format of this file is two space
delimited columns per line. The first column is the x-axis values, and the second column is the y-
axis values. The distance of the points from the identity line (y=x) is a measure of how good the
exponential tail fit is, the closer the points are to the identity line, the better the fit is.
Each series is delimited by a line with a single character "&". The file will contain one series
of empirical data for each of the four exponential tail fits in the following order: glocal CYK,
glocal Inside, local CYK and local Inside.
--ffile <f>
Save space delimited statistics of different exponential tail fits to file <f>. The file will
contain the lambda and mu values for exponential tails fit to histogram tails of different sizes.
The fields in the file are labelled informatively.
--xfile <f>
Save a list of the scores in each fit histogram tail to file <f>. Each line of this file will
have a different score indicating one hit existed in the tail with that score. Each series is
delimited by a line with a single character "&". The file will contain one series for each of the
four exponential tail fits in the following order: glocal CYK, glocal Inside, local CYK, and local
Inside.
OPTIONS CONTROLLING SPLIT, PARTITION AND MERGE MODES:
--split
Prepare a partitioned calibration. This option only works in combination with the --ptot <n> and
--cfile <f> options, and will prepare a calibration split into <n> separate partitions. The
commands to run all of the partitions will be in the file <f> .
--cfile <f>
With --split, save the commands for all partitions to file <f> .
--proot <s>
With --split, specify that the per-partition scores files be named <s>.<n> where <n> is the
partition index. By default they will be named <s>.calib.<n> where <s> is the name of the CM file
to be calibrated (including path).
--part <n>
specify that this is partition <n> out of <n2> from --ptot <n2>. Must be used in combination with
--ptot and --pfile .
--ptot <n>
With --split, --part or --merge, specify that there are <n> total partitions.
--pfile <f>
With --part , specify that scores for this partition be saved to file <f>
--merge
Merge scores from multiple previously executed partitions and calibrate CMs. If you used the
option --proot <s> with cmcalibrate when you ran it with --split to setup the partitions, use
--proot <s> again with --merge. The full cmcalibrate --merge command to use will have been output
to standard output when the initial cmcalibrate --split command was executed.
OTHER OPTIONS
--seed <n>
Seed the random number generator with <n>, an integer >= 0. If <n> is nonzero, stochastic
simulations will be reproducible; the same command will give the same results. If <n> is 0, the
random number generator is seeded arbitrarily, and stochastic simulations will vary from run to
run of the same command. The default seed is 181.
--beta <x>
By default query-dependent banding (QDB) is used to accelerate the CM search algorithms with a
beta tail loss probability of 1E-15. This beta value can be changed to <x> with --beta <x>. The
beta parameter is the amount of probability mass excluded during band calculation, higher values
of beta give greater speedups but sacrifice more accuracy than lower values. The default value
used is 1E-15. (For more information on QDB see Nawrocki and Eddy, PLoS Computational Biology
3(3): e56.)
--nonbanded
Turn off QDB during E-value calibration. This will slow down calibration.
--nonull3
Turn off the null3 post hoc additional null model. This is not recommended unless you plan on
using the same option to cmsearch and/or cmscan.
--random
Use the background null model of the CM to generate the random sequences, instead of the more
realistic HMM. Unless the CM was built using the --null option to cmbuild, the background null
model will be 25% each A, C, G and U.
--gc <f>
Generate the random sequences using the nucleotide distribution from the sequence file <f>.
--cpu <n>
Set the number of parallel worker threads to <n>. On multicore machines, the default is 4. You
can also control this number by setting an environment variable, INFERNAL_NCPU. There is also a
master thread, so the actual number of threads that Infernal spawns is <n>+1. This option is not
available if Infernal was compiled with POSIX threads support turned off.
--mpi Run as an MPI parallel program. This option will only be available if Infernal has been configured
and built with the "--enable-mpi" flag (see the Installation section of the user guide for more
information).
SEE ALSO
See infernal(1) for a master man page with a list of all the individual man pages for programs in the
Infernal package.
For complete documentation, see the user guide that came with your Infernal distribution (Userguide.pdf);
or see the Infernal web page (http://eddylab.org/infernal/).
COPYRIGHT
Copyright (C) 2023 Howard Hughes Medical Institute.
Freely distributed under the BSD open source license.
For additional information on copyright and licensing, see the file called COPYRIGHT in your Infernal
source distribution, or see the Infernal web page (http://eddylab.org/infernal/).
AUTHOR
http://eddylab.org
Infernal 1.1.5 Sep 2023 cmcalibrate(1)