XRanges

This data set gives the read counts of 40 samples in 5000 genomic
locations. The rows correspond to genomic segments of 25kbp length and the
columns to samples. An entry is the number of reads that map to the specific
segment of the sample. The "GRanges" object contains the name of the 
reference sequence, start and end position of the genomic segments.
The simulated data contains CNVs given in the <code><a rd-options="" href="/link/CNVRanges?package=cn.mops&version=1.18.0" data-mini-rdoc="cn.mops::CNVRanges">CNVRanges</a></code>
object. It was generated using
distributions of read counts as they appear in real sequencing experiments. 
CNVs were implanted under the assumption that the expected read count is linear
dependent on the copy number (e.g. in a certain genomic we expect 
$lambda$ reads for copy number 2, then we expect 
$2*lambda$ reads for copy number 4).


datasets

cn.mops (Copy Number estimation by a Mixture Of PoissonS)
is a data processing pipeline for copy number variations and
aberrations (CNVs and CNAs) from next generation sequencing
(NGS) data. The package supplies functions to convert BAM files
into read count matrices or genomic ranges objects, which are
the input objects for cn.mops. cn.mops models the depths of
coverage across samples at each genomic position. Therefore, it
does not suffer from read count biases along chromosomes. Using
a Bayesian approach, cn.mops decomposes read variations across
samples into integer copy numbers and noise by its mixture
components and Poisson distributions, respectively. cn.mops
guarantees a low FDR because wrong detections are indicated by
high noise and filtered out. cn.mops is very fast and written
in C++.

Guenter Klambauer

cn.mops

cn.mops - Mixture of Poissons for CNV detection in NGS data

XRanges function

A GRanges object with 5000 rows and 40 value columns across 1 space.

Format

http://www.bioinf.jku.at/software/cnmops/cnmops.html.

Source

This data set gives the read counts of 40 samples in 5000 genomic
locations. The rows correspond to genomic segments of 25kbp length and the
columns to samples. An entry is the number of reads that map to the specific
segment of the sample. The "GRanges" object contains the name of the 
reference sequence, start and end position of the genomic segments.
The simulated data contains CNVs given in the <code><a rd-options='' href='CNVRanges'>CNVRanges</a></code>
object. It was generated using
distributions of read counts as they appear in real sequencing experiments. 
CNVs were implanted under the assumption that the expected read count is linear
dependent on the copy number (e.g. in a certain genomic we expect 
$lambda$ reads for copy number 2, then we expect 
$2*lambda$ reads for copy number 4).


XRanges: A simulated data set for CNV detection from NGS data.

Description

Usage

Arguments

Format

Source

References