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Detect clusters of anomalously mapped pairs (version 1.0.0)

Sample Name:

Input BAM file (.ab.bam):

Chromosomes list file (.len):

Tabulated file format with Chromosome ID (integer from 1), name and length

Type of sequencing technology and libraries:

Read 1 length (bp):

Length of the first read in a pair (left read)

Read 2 length (bp):

Length of the second read in a pair (right read)

Type of SV to detect:

Linking procedure:

Detection and isolation of links

Do you want to split the original mate file per chromosome for parallel computing?:

Untick it if already done

Window size (bp):

Equal to at least “2µ+2√2σ

Step length size (bp):

Equal to 1/2 or 1/4 of the window size

Filtering procedure:

Filtering of links according different parameters and thresholds

Do you want to split the original link file per chromosome for parallel computing?:

Untick it if (the linking is) already done

List of chromosome names to keep or exclude:

Minimum number of pairs in a cluster:

Strand filtering procedure:

Order filtering procedure:

Insert-size filtering procedure:

Minimal number of sigma fold for the insert size filtering and to call insertions and deletions:

minimal number of sigma fold for the insert size filtering to call tandem duplications:

Minimal number of sigma fold for the insert size filtering to call singletons:

for Illumina mate-pairs only

Mean insert size value (µ) of normally mapped mate-pairs, in bp:

Calculated sd value (σ) from the distribution of normally mapped mate-pairs, in bp:

Minimal number of pairs in a subgroup of paired-end reads for balanced events:

Minimal final filtering score for calling SVs:

A value of 1 means all the pairs in a cluster were consistent between each other after applying filters

Do you want to have filtered links in a tabulated file format showing significant SVs?:

Output file conversion:

Converts filtered links to Circos/BED files format for graphical view of SVs

What it does

SVDetect - Version : 0.8b

Parallel version (nCPU=8)

SVDetect is a application for the isolation and the type prediction of intra- and inter-chromosomal rearrangements from paired-end/mate-pair sequencing data provided by the high-throughput sequencing technologies

This tool aims to identifying structural variations (SVs) with both clustering and sliding-window strategies, and helping in their visualization at the genome scale. SVDetect is compatible with SOLiD and Illumina (>=1.3) reads.

Manual documentation available at the http://svdetect.sourceforge.net/Site/Manual.html

Contact Bruno Zeitouni (svdetect@curie.fr) for any questions or concerns about the Galaxy implementation of SVDetect.