Collection of tools that I've used in analysing transposable elements. Not all scripts are transposable element specific but I decided to group them all in this repository.
Script that extracts columns from a TAB separated file (tsv) that has been sorted for Chrom and Start position and will produce a BED3 or BED6 file.
If a threshold is given, the output will merge consecutive lines that are greater or equal to the threshold (Important: files have to be sorted). Otherwise all lines will be returned.
The column positions are given in a specific order corresponding to a BED3 or BED6 file depending on the data available and the output that you want.
The order is chrom,start,end[,name,score,strand] and, as illustrated, should not have spaces i.e. -p 2,4,5 or -p 2,4,5,6,8,10. Be sure to give either 3 or 6 column numbers.
The numerical column that is used to filter the output does not need to be one of the output columns. The program will merge contiguous reported region that are above the given threshold.
This script will produce a BED with Chromosome, star and end position or a BED6 which will include the name, score and strand position.
After a bedtools multicov using a RepeatMasker gff annotation file and several bam files I used this script to identify genomic regions enriched in expressed Transposable elements.
python3 getregions.py -i repeats-rnaseq2.csv -p "1,4,5" -c 10 -t 50 -o repeats-expressed-50.bedTake a RepeatMasker .out file and extract all loci for a given family with a given flanking region, merge overlapping regions, extract the sequences, align and produce a cleaned alignment.
Usage: evalfamily.sh OPTIONS
OPTIONS:
-g|--genome FILE Fasta genome file
-a|--annot FILE Annotation gff file
-n|--name TEXT TE Family name
-f|--flank NUM Flanking bases
-t|--thread NUM Number of threads
[-m|--mafft] Align with Mafft
[-e|--erode] Erode the borders of the alignment
It produces:
- Fasta File with the elements and flanking regions
- Alignment file in fasta format (*.mft)
- Alignment file without the unaligned beginning and end.
Use the fasta file to inspect with a dotplot program like Gepard (ref here). Inspect the correct borders and produce a consensus sequence by inspecting the alignment files.
evalfamily.sh -g mygenome.fa -n rnd-1_family-1 -a mygenome.fa.out -f 500 -t 10 -m -eThe script takes a one_code_to_find_them_all.pl output file and will rename LTR elements according to the internal part that was identified. If no internal part is found the name will be taken from the LTR part. The name is stripped of _I and _LTR parts so that the LTR family name is used. It also eliminates duplicate lines identified as different parts of non autonomous elements. This helps with downstream processing.
usage: correct_one-code_with-name.py [-h] [-i I] [-o O]
Parse one-code output and eliminate lines that are contained in previously identified loci
optional arguments:
-h, --help show this help message and exit
-i I One code output file
-o O Output file name
The output file resembles the one_code_to_find_them_all output but has the names of LTR elements changed to the family name without the _I or _LTR suffixes and the duplicated lines deleted.
python3 correct_one-code_with-name.py -i one_code_output.csv -o one_code_output-corrected.csvGraphs the 3d histogram of percentage of divergence and percentage of completeness with respect to the representative element of the family.
usage: graphbyage3d.py [-h] [-i I] [-b B] [-s S] [-f F] [-o O]
Parse RepeatMasker .out file and graph percent similarity by repeat family
optional arguments:
-h, --help show this help message and exit
-i I Onecode .elem_sorted.csv file
-b B Number of bins
-s S Size of image in WxH in inches
-f F Class to filter
-o O Filename for graph
Creates a PNG image of the TE element given in the command line (-f)
python3 graphbyage3d.py -i onecode-corrected-output.csv -b 20 -s 9x9 -f SACI5 -o saci5.pngGraphs a 2d histogram of percentage of divergence and percentage of completeness with respect to the representative element of the family with the histogram values being color coded.
usage: graphbycontour.py [-h] [-i I] [-b B] [-s S] [-f F] [-o O]
Parse RepeatMasker .out file and graph percent similarity by repeat family
optional arguments:
-h, --help show this help message and exit
-i I Onecode .elem_sorted.csv file
-b B Number of bins
-s S Size of image in WxH format (inches)
-f F Class to filter
-o O Filename for graph
Creates a PNG image of the TE element given in the command line (-f)
python3 graphbycontour.py -i onecode-corrected-output.csv -b 20 -s 9x9 -f SACI5 -o saci5.png