BilkentCompGen/repeatnet

Name: repeatnet

Owner: Bilkent Bioinformatics and Computational Genomics Group

Description: RepeatNet: an ab initio centromeric sequence detection algorithm

Created: 2014-10-31 10:01:06.0

Updated: 2017-08-04 08:47:26.0

Pushed: 2017-08-04 08:47:43.0

Homepage: null

Size: 21

Language: C

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README

repeatnet

RepeatNet: an ab initio centromeric sequence detection algorithm

Additional tools that should be installed

• PHRAP for the assembly step
• TRF for calculating the consensus
• Graphviz for visualization [ OPTIONAL ]

Compilation:

gcc repeatnet.c -o repeatnet -O3 -lm

input: FASTA format only. The pairs of reads (preferably fosmid; if not plasmid) should be named as:

pair1.FORWARD.1 pair1.REVERSE.1

pair2.FORWARD.1 pair2.REVERSE.1

the “pair1/pair2” part doesn't matter, but FORWARD/REVERSE part is used to mark the pairs; of course the “pair1/pair2” part of the pairs must match.

then run : repeatnet -i test

this will generate a bunch of files: test.h11.dump, test.h11.names, test.h11.winlog

then

repeatnet -loadwin test.h11.winlog -m -a 100 -c 100 -compare

-a 100 and -c 100 removes the vertices with less than 100 occurances in the graph, the edges with <100 weight value (co-occurance frequency between pairs of vertics). Lower values will give more connected and noisy graphs, higher values will “clean up” the graph more.

this will generate a matrix and viz file. To visualize the graph, use the graphviz package:

neato -Tps -o test.h11.winlog.h11.cut100.e10000.merged.eps test.h11.winlog.h11.cut100.e10000.merged.viz

then to divide into connected components:

repeatnet -loadmatrix test.h11.winlog.h11.cut100.e10000.merged.matrix -loadnames test.h11.names -components

pick the largest component first (by file size; or any other interesting-looking one from the graph). in my test, it is component-30. then “encode” the kmers back into numbers:

for i in cut -f 1 component-30.txt; do repeatnet -encode $i; done > component-30.ids

this will calculate the hash values (or vertex id's) for the kmers.

then:

repeatnet -loadwin test.h11.winlog -loadnames test.h11.names -clones component-30.id

will generate a file component-30.ids.clones that will have names of the sequences (pairs) that are likely to contain satellite. This file might be redundant, so run a “sort -u " on it. Fetch the sequences back from your original fasta file, and run phrap first; then run TRF on the contigs.