GPsInElevGaps

Extracts subsets of the gffTSV associated with gene predictions that fall within regions
of detected gapped or elevated read coverage.

internal

Automate the detection of gaps and elevations in mapped sequencing
read coverage using a 2D pattern-matching algorithm. 'ProActive' detects, characterizes
and visualizes read coverage patterns in both genomes and metagenomes. Optionally,
users may provide gene annotations associated with their genome or metagenome
in the form of a .gff file. In this case, 'ProActive' will generate an additional
output table containing the gene annotations found within the detected regions of gapped
and elevated read coverage. Additionally, users can search for gene
annotations of interest in the output read coverage plots.

Jessie Maier

ProActive

Detect Elevations and Gaps in Mapped Sequencing Read Coverage

Manuel Kleiner

GPsInElevGaps function

<dl><dt>elevGapSummList</dt>
<dd>A list containing pattern-match information associated with all
elevation and gap classifications. (i.e. no NoPattern classifications)</dd>
<dt>windowSize</dt>
<dd>The number of basepairs to average read coverage values over.
Options are 100, 200, 500, 1000 ONLY. Default is 1000.</dd>
<dt>gffTSV</dt>
<dd>Optional, a .gff file (TSV) containing gene predictions associated with the .fasta
file used to generate the pileup.</dd>
<dt>mode</dt>
<dd>Either "genome" or "metagenome"</dd>
<dt>chunkContigs</dt>
<dd>TRUE or FALSE, If TRUE and `mode`="metagenome", contigs longer
than the `chunkSize` will be 'chunked' into smaller subsets and pattern-matching
will be performed on each subset. Default is FALSE.</dd>
<dt>chunkSize</dt>
<dd>If `mode`="genome" OR if `mode`="metagenome" and `chunkContigs`=TRUE,
chunk the genome or contigs, respectively, into smaller subsets for pattern-matching.</dd></dl>

Arguments

Detect gene predictions in elevations and gaps — GPsInElevGaps

<dl>

<dt>elevGapSummList</dt>
<dd>A list containing pattern-match information associated with all
elevation and gap classifications. (i.e. no NoPattern classifications)</dd>


<dt>windowSize</dt>
<dd>The number of basepairs to average read coverage values over.
Options are 100, 200, 500, 1000 ONLY. Default is 1000.</dd>


<dt>gffTSV</dt>
<dd>Optional, a .gff file (TSV) containing gene predictions associated with the .fasta
file used to generate the pileup.</dd>


<dt>mode</dt>
<dd>Either "genome" or "metagenome"</dd>


<dt>chunkContigs</dt>
<dd>TRUE or FALSE, If TRUE and `mode`="metagenome", contigs longer
than the `chunkSize` will be 'chunked' into smaller subsets and pattern-matching
will be performed on each subset. Default is FALSE.</dd>


<dt>chunkSize</dt>
<dd>If `mode`="genome" OR if `mode`="metagenome" and `chunkContigs`=TRUE,
chunk the genome or contigs, respectively, into smaller subsets for pattern-matching.</dd>

</dl>

GPsInElevGaps: Detect gene predictions in elevations and gaps

Description

Usage

Arguments