.\" DO NOT MODIFY THIS FILE!  It was generated by help2man 1.49.3.
.TH CNVKIT_SEGMETRICS "1" "July 2023" "cnvkit.py segmetrics 0.9.10" "User Commands"
.SH NAME
cnvkit_segmetrics \- Compute segment-level metrics from bin-level log2 ratios.
.SH DESCRIPTION
usage: cnvkit.py segmetrics [\-h] \fB\-s\fR SEGMENTS [\-\-drop\-low\-coverage]
.TP
[\-o FILENAME] [\-\-mean] [\-\-median] [\-\-mode]
[\-\-t\-test] [\-\-stdev] [\-\-sem] [\-\-mad] [\-\-mse]
[\-\-iqr] [\-\-bivar] [\-\-ci] [\-\-pi] [\-a ALPHA]
[\-b BOOTSTRAP] [\-\-smooth\-bootstrap]
cnarray
.SS "positional arguments:"
.TP
cnarray
Bin\-level copy ratio data file (*.cnn, *.cnr).
.SS "options:"
.TP
\fB\-h\fR, \fB\-\-help\fR
show this help message and exit
.TP
\fB\-s\fR SEGMENTS, \fB\-\-segments\fR SEGMENTS
Segmentation data file (*.cns, output of the 'segment'
command).
.TP
\fB\-\-drop\-low\-coverage\fR
Drop very\-low\-coverage bins before calculations to
avoid negative bias in poor\-quality tumor samples.
.TP
\fB\-o\fR FILENAME, \fB\-\-output\fR FILENAME
Output table file name.
.SS "Statistics available:"
.TP
\fB\-\-mean\fR
Mean log2 ratio (unweighted).
.TP
\fB\-\-median\fR
Median.
.TP
\fB\-\-mode\fR
Mode (i.e. peak density of bin log2 ratios).
.TP
\fB\-\-t\-test\fR
One\-sample t\-test of bin log2 ratios versus 0.0.
.TP
\fB\-\-stdev\fR
Standard deviation.
.TP
\fB\-\-sem\fR
Standard error of the mean.
.TP
\fB\-\-mad\fR
Median absolute deviation (standardized).
.TP
\fB\-\-mse\fR
Mean squared error.
.TP
\fB\-\-iqr\fR
Inter\-quartile range.
.TP
\fB\-\-bivar\fR
Tukey's biweight midvariance.
.TP
\fB\-\-ci\fR
Confidence interval (by bootstrap).
.TP
\fB\-\-pi\fR
Prediction interval.
.TP
\fB\-a\fR ALPHA, \fB\-\-alpha\fR ALPHA
Level to estimate confidence and prediction intervals;
use with \fB\-\-ci\fR and \fB\-\-pi\fR. [Default: 0.05]
.TP
\fB\-b\fR BOOTSTRAP, \fB\-\-bootstrap\fR BOOTSTRAP
Number of bootstrap iterations to estimate confidence
interval; use with \fB\-\-ci\fR. [Default: 100]
.TP
\fB\-\-smooth\-bootstrap\fR
Apply Gaussian noise to bootstrap samples, a.k.a.
smoothed bootstrap, to estimate confidence interval;
use with \fB\-\-ci\fR.