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# REPEATS ANNOTATION TOOLS FOR ASSEMBLIES  #


## 1. PROFREP ##
*- **PROF**iles of **REP**eats -* 

The ProfRep main tool engages outputs of RepeatExplorer for repeats annotation in DNA sequences (typically assemblies but not necessarily). Moreover, it provides repetitive profiles of the sequence, pointing out quantitative representation of individual repeats along the sequence as well as the overall repetitiveness.

### DEPENDENCIES ###

* python 3.4 or higher with packages:
	* numpy
	* matplotlib
	* biopython
* [BLAST 2.2.28+](https://www.ncbi.nlm.nih.gov/books/NBK279690/) or higher
* [wigToBigWig](http://hgdownload.cse.ucsc.edu/admin/exe/)
* [cd-hit](http://weizhongli-lab.org/cd-hit/)
* [JBrowse](http://jbrowse.org/install/) - **Only bin needed, does not have to be installed under a web server**
  
* ProfRep Modules:
	* gff.py
	* visualization.py
	* configuration.py 
	* protein_domains.py
	* domains_filtering.py
	
* Profrep databases

There are precompiled profrep annotation dataset for limited number of species. List of species can be find in file [prepared_datasets.txt](tool_data/prepared_datasets). Databases include large files and must be downloaded from our website:

    cd tool_data
    wget http://repeatexplorer.org/repeatexplorer/wp-content/uploads/profrep.tar.gz
    tar xzvf profrep.tar.gz
        
    
#### INPUTS ####

* **DNA sequence(s) to annotate** [multiFASTA]

* **Species specific dataset** available from RepeatExplorer archive consisting of:

	* NGS reads sequences [multiFASTA]
		* In RE archive: *seqclust -> sequences -> sequences.fasta*
	* CLS file of clusters and belonging reads [multiFASTA] 
		* in RE archive: *seqclust -> clustering -> hitsort.cls*
	* Classification table [TSV, CSV] 
		* in RE archive: *PROFREP_CLASSIFICATION_TEMPLATE.csv* (automatic classification)


#### OUTPUTS ####
	
* **HTML summary report,JBrowse Data Directory** showing basic information and repetitive profile graphs as well as protein domains (optional) for individual sequences (up to 50). This output also serves as an data directory for [JBrowse](https://jbrowse.org/) genome browser. You can create a standalone JBrowse instance for further detailed visualization of the output tracks using Galaxy-integrated tool. This output can also be downloaded as an archive containing all relevant data for visualization via locally installed JBrowse server (see more about visualization in OUTPUT VISUALIZATION below)
* **Ns GFF** - reports unspecified (N) bases regions in the sequence
* **Repeats GFF** - reports repetitive regions of a certain length (defaultly **80**) and above hits/copy numbers threshold (defaultly **3**)
* **Domains GFF** - reports protein domains, classification of domain, chain orientation and alignment sequences
* Log file


### Running ProfRep ###

	usage: profrep.py [-h] -q QUERY -rdb READS -a ANN_TBL -c CLS [-id DB_ID]
                  [-bs BIT_SCORE] [-m MAX_ALIGNMENTS] [-e E_VALUE]
                  [-df DUST_FILTER] [-ws WORD_SIZE] [-t TASK] [-n NEW_DB]
                  [-w WINDOW] [-o OVERLAP] [-pd PROTEIN_DOMAINS]
                  [-pdb PROTEIN_DATABASE] [-cs CLASSIFICATION] [-wd WIN_DOM]
                  [-od OVERLAP_DOM] [-thsc THRESHOLD_SCORE]
                  [-thl {float range 0.0..1.0}] [-thi {float range 0.0..1.0}]
                  [-ths {float range 0.0..1.0}] [-ir INTERRUPTIONS]
                  [-mlen MAX_LEN_PROPORTION] [-lg LOG_FILE] [-ouf OUTPUT_GFF]
                  [-oug DOMAIN_GFF] [-oun N_GFF] [-hf HTML_FILE]
                  [-hp HTML_PATH] [-cn COPY_NUMBERS] [-gs GENOME_SIZE]
                  [-thr THRESHOLD_REPEAT] [-thsg THRESHOLD_SEGMENT]
                  [-jb JBROWSE_BIN]
                  

	optional arguments:
	  -h, --help            show this help message and exit

	required arguments:
	  -q QUERY, --query QUERY
							input DNA sequence in (multi)fasta format (default:
							None)
	  -rdb READS, --reads READS
							blast database of all sequencing reads (default: None)
	  -a ANN_TBL, --ann_tbl ANN_TBL
							clusters annotation table, tab-separated number of
							cluster and its classification (default: None)
	  -c CLS, --cls CLS     cls file containing reads assigned to clusters
							(hitsort.cls) (default: None)

	alternative required arguments - prepared datasets:
	  -id DB_ID, --db_id DB_ID
							annotation dataset ID (first column of datasets table)
							(default: None)

	optional arguments - BLAST Search:
	  -bs BIT_SCORE, --bit_score BIT_SCORE
							bitscore threshold (default: 50)
	  -m MAX_ALIGNMENTS, --max_alignments MAX_ALIGNMENTS
							blast filtering option: maximal number of alignments
							in the output (default: 10000000)
	  -e E_VALUE, --e_value E_VALUE
							blast setting option: e-value (default: 0.1)
	  -df DUST_FILTER, --dust_filter DUST_FILTER
							dust filters low-complexity regions during BLAST
							search (default: '20 64 1')
	  -ws WORD_SIZE, --word_size WORD_SIZE
							blast search option: initial word size for alignment
							(default: 11)
	  -t TASK, --task TASK  type of blast to be triggered (default: blastn)
	  -n NEW_DB, --new_db NEW_DB
							create a new blast database, USE THIS OPTION IF YOU
							RUN PROFREP WITH NEW DATABASE FOR THE FIRST TIME
							(default: True)

	optional arguments - Parallel Processing:
	  -w WINDOW, --window WINDOW
							sliding window size for parallel processing (default:
							5000)
	  -o OVERLAP, --overlap OVERLAP
							overlap for parallely processed regions, set greater
							than a read size (default: 150)

	optional arguments - Protein Domains:
	  -pd PROTEIN_DOMAINS, --protein_domains PROTEIN_DOMAINS
							use module for protein domains (default: False)
	  -pdb PROTEIN_DATABASE, --protein_database PROTEIN_DATABASE
							protein domains database (default: None)
	  -cs CLASSIFICATION, --classification CLASSIFICATION
							protein domains classification file (default: None)
	  -wd WIN_DOM, --win_dom WIN_DOM
							protein domains module: sliding window to process
							large input sequences sequentially (default: 10000000)
	  -od OVERLAP_DOM, --overlap_dom OVERLAP_DOM
							protein domains module: overlap of sequences in two
							consecutive windows (default: 10000)
	  -thsc THRESHOLD_SCORE, --threshold_score THRESHOLD_SCORE
							protein domains module: percentage of the best score
							within the cluster to significant domains (default:
							80)
	  -thl {float range 0.0..1.0}, --th_length {float range 0.0..1.0}
							proportion of alignment length threshold (default:
							0.8)
	  -thi {float range 0.0..1.0}, --th_identity {float range 0.0..1.0}
							proportion of alignment identity threshold (default:
							0.35)
	  -ths {float range 0.0..1.0}, --th_similarity {float range 0.0..1.0}
							threshold for alignment proportional similarity
							(default: 0.45)
	  -ir INTERRUPTIONS, --interruptions INTERRUPTIONS
							interruptions (frameshifts + stop codons) tolerance
							threshold per 100 AA (default: 3)
	  -mlen MAX_LEN_PROPORTION, --max_len_proportion MAX_LEN_PROPORTION
							maximal proportion of alignment length to the original
							length of protein domain from database (default: 1.2)

	optional arguments - Output Paths:
	  -lg LOG_FILE, --log_file LOG_FILE
							path to log file (default: log.txt)
	  -ouf OUTPUT_GFF, --output_gff OUTPUT_GFF
							path to output gff of repetitive regions (default:
							output_repeats.gff)
	  -oug DOMAIN_GFF, --domain_gff DOMAIN_GFF
							path to output gff of protein domains (default:
							output_domains.gff)
	  -oun N_GFF, --n_gff N_GFF
							path to output gff of N regions (default:
							N_regions.gff)
	  -hf HTML_FILE, --html_file HTML_FILE
							path to output html file (default: output.html)
	  -hp HTML_PATH, --html_path HTML_PATH
							path to html extra files (default: profrep_output_dir)

	optional arguments - Copy Numbers/Hits :
	  -cn COPY_NUMBERS, --copy_numbers COPY_NUMBERS
							convert hits to copy numbers (default: False)
	  -gs GENOME_SIZE, --genome_size GENOME_SIZE
							genome size is required when converting hits to copy
							numbers and you use custom data (default: None)
	  -thr THRESHOLD_REPEAT, --threshold_repeat THRESHOLD_REPEAT
							threshold for hits/copy numbers per position to be
							considered repetitive (default: 3)
	  -thsg THRESHOLD_SEGMENT, --threshold_segment THRESHOLD_SEGMENT
							threshold for the length of repetitive segment to be
							reported (default: 80)

	optional arguments - Enviroment Variables:
	  -jb JBROWSE_BIN, --jbrowse_bin JBROWSE_BIN
							path to JBrowse bin directory (default: None)

							
#### HOW TO RUN EXAMPLE ####

		./protein.py --query PATH_TO_DNA_SEQ --reads PATH_TO_READS --ann_tbl PATH_TO_CLUSTERS_CLASSIFICATION  --cls PATH_TO_hitsort.cls 
		
	 When running for the first time with a new reads database use:
		
		--new_db True

							
### ProfRep Data Preparation ###

In case of using custom input datasets these tools can be used for easy obtaining the correct files and to prepare the reduced datasets to speed up the main ProfRep analysis:

* Extract Data For ProfRep (extract_data_for_profrep.py)
* ProfRep DB Reducing (profrep_db_reducing.py)

### ProfRep Supplementary Tools ###

These additional tools can be used for further work with the ProfRep outputs: 

* ProfRep Refiner (profrep_refining.py) 
* ProfRep Masker (profrep_masking.py)
* GFF Region Selector (gff_selection.py)

### FOR MORE INFO ABOUT PREPARATION AND SUPPLEMENTARY TOOLS PLEASE READ PROFREP WIKI ###

## 2. DANTE ##
*- **D**omain based **AN**notation of **T**ransposable **E**lements -* 


* Protein Domains Finder [protein_domains.py]
	* Script performs scanning of given DNA sequence(s) in (multi)fasta format in order to discover protein domains using our protein domains database.
	* Domains searching is accomplished engaging LASTAL alignment tool.
	* Domains are subsequently annotated and classified - in case certain domain has multiple annotations assigned, classifation is derived from the common classification level of all of them. 	
			
* Proteins Domains Filter [domains_filtering.py]
	* filters GFF3 output from previous step to obtain certain kind of domain and/or allows to adjust quality filtering  

        
### DEPENDENCIES ###

* python3.4 or higher with packages:	
	* numpy
	* biopython
* [lastal](http://last.cbrc.jp/doc/last.html) 744 or higher
* ProfRep/DANTE modules:
	* configuration.py 


### Protein Domains Finder ###

This tool provides **preliminary** output of all domains types which are not filtered for quality.

#### INPUTS ####

* DNA sequence [multiFasta]
		
#### OUTPUTS ####
		
* **All protein domains GFF3** - individual domains are reported per line as regions (start-end) on the original DNA sequence including the seq ID and strand orientation. The last "Attributes" column contains several comma-separated information related to the domain annotation, alignment and its quality. This file can undergo further filtering using Protein Domain Filter tool.		

#### USAGE ####
		usage: protein_domains.py [-h] -q QUERY -pdb PROTEIN_DATABASE -cs
								  CLASSIFICATION [-oug DOMAIN_GFF] [-nld NEW_LDB]
								  [-dir OUTPUT_DIR] [-thsc THRESHOLD_SCORE]
								  [-wd WIN_DOM] [-od OVERLAP_DOM]
								  
		optional arguments:
		  -h, --help            show this help message and exit
		  -oug DOMAIN_GFF, --domain_gff DOMAIN_GFF
								output domains gff format (default: None)
		  -nld NEW_LDB, --new_ldb NEW_LDB
								create indexed database files for lastal in case of
								working with new protein db (default: False)
		  -dir OUTPUT_DIR, --output_dir OUTPUT_DIR
								specify if you want to change the output directory
								(default: None)
		  -thsc THRESHOLD_SCORE, --threshold_score THRESHOLD_SCORE
								percentage of the best score in the cluster to be
								tolerated when assigning annotations per base
								(default: 80)
		  -wd WIN_DOM, --win_dom WIN_DOM
								window to process large input sequences sequentially
								(default: 10000000)
		  -od OVERLAP_DOM, --overlap_dom OVERLAP_DOM
								overlap of sequences in two consecutive windows
								(default: 10000)

		required named arguments:
		  -q QUERY, --query QUERY
								input DNA sequence to search for protein domains in a
								fasta format. Multifasta format allowed. (default:
								None)
		  -pdb PROTEIN_DATABASE, --protein_database PROTEIN_DATABASE
								protein domains database file (default: None)
		  -cs CLASSIFICATION, --classification CLASSIFICATION
								protein domains classification file (default: None)


		
#### HOW TO RUN EXAMPLE ####
		./protein_domains.py -q PATH_TO_INPUT_SEQ -pdb PATH_TO_PROTEIN_DB -cs PATH_TO_CLASSIFICATION_FILE
		
	 When running for the first time with a new database use -nld option allowing lastal to create indexed database files:

         -nld True

	use other arguments if you wish to rename your outputs or they will be created automatically with standard names 
	
### Protein Domains Filter ###
		
The script performs Protein Domains Finder output filtering for quality and/or extracting specific type of protein domain or mobile elements of origin. For the filtered domains it reports their translated protein sequence of original DNA.

WHEN NO PARAMETERS GIVEN, IT PERFORMS QUALITY FILTERING USING THE DEFAULT PARAMETRES (optimized for Viridiplantae species)

#### INPUTS ####
* GFF3 file produced by protein_domains.py OR already filtered GFF3
	
#### Filtering options ####
* QUALITY: 
	- Min relative length of alignemnt to the protein domain from DB (without gaps)
	- Identity 
	- Similarity (scoring matrix: BLOSUM80)
	- Interruption in the reading frame (frameshifts + stop codons) per every starting 100 AA
	- Max alignment proportion to the original length of database domain sequence
* DOMAIN TYPE: 'Name' attribute in GFF - see choices bellow
Records for ambiguous domain type (e.g. INT/RH) are filtered out automatically

* MOBILE ELEMENT TYPE:
arbitrary substring of the element classification ('Final_Classification' attribute in GFF)
		
#### OUTPUTS ####
* filtered GFF3 file
* fasta file of translated protein sequences for the aligned domains that match the filtering criteria 
	! as it is taken from the best hit alignment reported by LAST, it does not neccessary cover the whole region reported as domain in GFF
	
#### USAGE ####		
		usage: domains_filtering.py [-h] -dg DOM_GFF [-ouf DOMAINS_FILTERED]
                            [-dps DOMAINS_PROT_SEQ]
                            [-thl {float range 0.0..1.0}]
                            [-thi {float range 0.0..1.0}]
                            [-ths {float range 0.0..1.0}] [-ir INTERRUPTIONS]
                            [-mlen MAX_LEN_PROPORTION]
                            [-sd {All,GAG,INT,PROT,RH,RT,aRH,CHDCR,CHDII,TPase,YR,HEL1,HEL2,ENDO}]
                            [-el ELEMENT_TYPE] [-dir OUTPUT_DIR]



		optional arguments:
		  -h, --help            show this help message and exit
		  -ouf DOMAINS_FILTERED, --domains_filtered DOMAINS_FILTERED
								output filtered domains gff file (default: None)
		  -dps DOMAINS_PROT_SEQ, --domains_prot_seq DOMAINS_PROT_SEQ
								output file containg domains protein sequences
								(default: None)
		  -thl {float range 0.0..1.0}, --th_length {float range 0.0..1.0}
								proportion of alignment length threshold (default:
								0.8)
		  -thi {float range 0.0..1.0}, --th_identity {float range 0.0..1.0}
								proportion of alignment identity threshold (default:
								0.35)
		  -ths {float range 0.0..1.0}, --th_similarity {float range 0.0..1.0}
								threshold for alignment proportional similarity
								(default: 0.45)
		  -ir INTERRUPTIONS, --interruptions INTERRUPTIONS
								interruptions (frameshifts + stop codons) tolerance
								threshold per 100 AA (default: 3)
		  -mlen MAX_LEN_PROPORTION, --max_len_proportion MAX_LEN_PROPORTION
								maximal proportion of alignment length to the original
								length of protein domain from database (default: 1.2)
		  -sd {All,GAG,INT,PROT,RH,RT,aRH,CHDCR,CHDII,TPase,YR,HEL1,HEL2,ENDO}, --selected_dom {All,GAG,INT,PROT,RH,RT,aRH,CHDCR,CHDII,TPase,YR,HEL1,HEL2,ENDO}
								filter output domains based on the domain type
								(default: All)
		  -el ELEMENT_TYPE, --element_type ELEMENT_TYPE
								filter output domains by typing substring from
								classification (default: )
		  -dir OUTPUT_DIR, --output_dir OUTPUT_DIR
								specify if you want to change the output directory
								(default: None)

		required named arguments:
		  -dg DOM_GFF, --dom_gff DOM_GFF
								basic unfiltered gff file of all domains (default:
								None)



#### HOW TO RUN EXAMPLE ####
e.g. getting quality filtered integrase(INT) domains of all gypsy transposable elements:
	
	./domains_filtering.py -dom_gff PATH_TO_INPUT_GFF -pdb PATH_TO_PROTEIN_DB -cs PATH_TO_CLASSIFICATION_FILE --selected_dom INT --element_type Ty3/gypsy 


### Extract Domains Nucleotide Sequences ###

This tool extracts nucleotide sequences of protein domains from reference DNA based on DANTE's output. It can be used e.g. for deriving phylogenetic relations of individual mobile elements classes within a species. 

#### INPUTS ####

* original DNA sequence in multifasta format to extract the domains from 
* GFF3 file of protein domains (**DANTE's output** - preferably filtered for quality and specific domain type)
* Domains database classification table (to check the classification level)

#### OUTPUTS ####

* fasta files of domains nucleotide sequences for individual transposons lineages
* txt file of domains counts extracted for individual lineages

**- For GALAXY usage all concatenated in a single fasta file**

#### USAGE ####	
		usage: extract_domains_seqs.py [-h] -i INPUT_DNA -d DOMAINS_GFF -cs
			CLASSIFICATION [-out OUT_DIR] [-ex EXTENDED]

		optional arguments:
		  -h, --help            show this help message and exit
		  -i INPUT_DNA, --input_dna INPUT_DNA
								path to input DNA sequence
		  -d DOMAINS_GFF, --domains_gff DOMAINS_GFF
								GFF file of protein domains
		  -cs CLASSIFICATION, --classification CLASSIFICATION
								protein domains classification file
		  -out OUT_DIR, --out_dir OUT_DIR
								output directory
		  -ex EXTENDED, --extended EXTENDED
								extend the domains edges if not the whole datatabase
								sequence was aligned

#### HOW TO RUN EXAMPLE ####
	./extract_domains_seqs.py --domains_gff PATH_PROTEIN_DOMAINS_GFF --input_dna PATH_TO_INPUT_DNA  --classification PROTEIN_DOMAINS_DB_CLASS_TBL --extended True

### GALAXY implementation ###

#### Dependencies ####

* python3.4 or higher with packages:	
	* numpy
	* matplotlib
	* biopython
* [BLAST 2.2.28+](https://www.ncbi.nlm.nih.gov/books/NBK279671/) or higher
* [LAST](http://last.cbrc.jp/doc/last.html) 744 or higher:
	* [download](http://last.cbrc.jp/)
	* [install](http://last.cbrc.jp/doc/last.html)
* [wigToBigWig](http://hgdownload.cse.ucsc.edu/admin/exe/)
* [cd-hit](http://weizhongli-lab.org/cd-hit/)
* [JBrowse](http://jbrowse.org/install/) - **Only bin needed, does not have to be installed under a web server**

#### Source ######

https://[e-mail]/nina_h/profrep.git

branch "cerit" --> only Pisum Sativum Terno in preparad annotation datasets

branch "develop"/"master" --> extended internal database of species (not published, or for internal purposes)

#### Configuration #####

Add tools

	<section name="Assembly annotation" id="annotation">
		<label id="profrep_prepare" text="ProfRep Data Preparation" />
			<tool file="profrep/extract_data_for_profrep.xml" />
			<tool file="profrep/db_reducing.xml" />
		<label id="profrep_main" text="Profrep" />
			<tool file="profrep/profrep.xml" />
		<label id="profrep_supplementary" text="Profrep Supplementary" />
			<tool file="profrep/profrep_refine.xml" />
			<tool file="profrep/profrep_masking.xml" />
			<tool file="profrep/gff_select_region.xml" />
		<label id="domains" text="DANTE" />
			<tool file="profrep/protein_domains.xml" />
			<tool file="profrep/domains_filtering.xml" />
			<tool file="profrep/extract_domains_seqs.xml" />
  </section>

	
to 

	$__root_dir__/config/tool_conf.xml
	
------------------------------------------------------------------------

Place PROFREP_DB files to

	$__tool_data_path__/profrep

*REMARK* PROFREP_DB files contain prepared annotation data for species in the roll-up menu:
	
	* sequences.fasta - including BLAST database files which was created by:
		 makeblastdb -in >sequences.fasta -dbtype nucl
	* hitosort.cls file
	* classification table table

Place DANTE_DB files to

	$__tool_data_path__/protein_domains
	
*REMARK* DANTE_DB files contain protein domains database files:
	* protein domains database including LASTAL database files which was created by:
		lastdb -p -cR01 >database_name< >database_name<
		(lastal database files are actually enough, original datatabse table does not have to be present)
	* classification table
	
------------------------------------------------------------------------	
	
Create
	
	$__root_dir__/database/dependencies/profrep/1.0.0/env.sh
	
containing:
	
	export JBROWSE_BIN=PATH_TO_JBROWSE_DIR/bin

------------------------------------------------------------------------	
	
Link the following files into galaxy tool-data dir

	ln -s $__tool_directory__/profrep/domains_data/select_domain.txt $__tool_data_path__
	ln -s $__tool_directory__/profrep/profrep_data/prepared_datasets.txt $__tool_data_path__