From 4475bd3be107c2e38050d6d46aea9cebbfae0086 Mon Sep 17 00:00:00 2001
From: "Thulani Hewavithana (qnm481)" <qnm481@mail.usask.ca>
Date: Fri, 7 Jul 2023 10:06:21 -0600
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-SyntenyLink
-===========
-
-Overview
-========
-
-The SyntenyLink package has six major components: the SyntenyLink
-algorithm allows users to handle reconstruct subgenomes of polyploid
-species more conveniently and to separate the set of genes belong to
-each subgenome in the organism with the aid of reference proteomes of
-polyploid species and related ancestor.
-
-All programs are executed using command line options on Linux systems or
-Mac OS. Usage or help information are well built into the programs. To
-show them on the screen, users just need to run the program without
-giving any options:
-
- $python3 ./SyntenyLink.py
-
-All code is copiable, distributable, modifiable, and usable without any
-restrictions. Contact: Thulani Hewavithana, <qnm481@usask.ca>; Chu Shin
-Koh, <kevin.koh@gifs.ca>
-
-The following is the list of executable programs
-------------------------------------------------
-
-**Main programs (in the Scripts folder)**
-
-- SyntenyLink\_bf.pl
-- SyntenyLink\_st.pl
-- SyntenyLink\_mbp.py
-- SyntenyLink\_wg.py
-- SyntenyLink\_sb.py
-- SyntenyLink\_mn.py
-- main\_script.py
-- SyntenyLink\_acc.py
-- gap\_threshold\_selection.py
-- minimum\_block\_length\_selection.py
-
-Main programs
-=============
-
-SyntenyLink\_bf
-===============
-
-This program, detects homologs between two species with blastp and
-involves a filtering step focusing on bit score and e-value to remove
-noise following two criteria: an e-value threshold of less than 1e-20
-and a ratio between the bit score and the highest bit score greater than
-0.6.
-
-\- Usage Reads in a data file: abc.blast. The abc.blast file holds blast
-hits after running blastp between baseline species and polyploid species
-of interest:
-
- BraA01g000010.3C AT1G43860.1 74.194 124 14 3 80 186 231 353 9.61e-56 188
-
-Here is a typical parameter setting for generating the abc.blast file:
-
- $ makeblastdb -in ref_pep.fa -dbtype prot -out ref_pep
-
- $ blastall -i query_pep.fasta -p blastp -d ref_pep -m 8 -e 1e-5 -F F -v 5 -b 5 -o abc.blast -a 4
-
-Note: for blastp you need to use protein fasta files of baseline model
-and polyploid species of interest. After getting the output blast result
-update gene start loci and end loci adding row start values from the bed
-file of each species before using SyntenyLink\_bf.py.
-
-It is advised that to make SyntenyLink\_bf generate more reasonable
-results, the number of BLASTP hits for a gene should be restricted to
-around top 5. When you have abc.blast ready, put them in the same
-folder. Then you can simply use:
-
- $ ./SyntenyLink_bf.pl dir/abc.blast
-
-\- Output The execution of SyntenyLink\_bf outputs one blast file
-abc\_blast\_filtered.txt, containing filtered blast hits as follows:
-
- BraA01g000010.3C AT1G43860.1 74.194 124 14 3 80 186 231 353 9.61e-56 188
- BraA01g000010.3C AT3G04630.1 66.087 115 21 4 194 297 165 272 7.06e-33 125
- BraA01g000010.3C AT3G04630.3 66.087 115 21 4 194 297 164 271 7.88e-33 125
-
-SyntenyLink\_st
----------------
-
-This program uses the output after performing synteny analysis using
-DAGchainer to build a chain of syntenic genes and compute the score of
-each chain. The modified version of filtered results from blastp
-(abc\_blast\_filtered\_modified.txt) and DAGchainer
-(abc\_synteny.aligncoords) are used to generate a syntelog table in
-which the gene chains are incorporated into their corresponding
-chromosomes with redundant chains (likely due to gene duplications or
-tandem or segmental duplications in the polyploid genome) placed in the
-"overlap" column in the syntelog table.
-
-Reads in data file for DAGchainer: abc\_blast\_filtered\_modified.txt.
-The abc\_blast\_filtered\_modified.txt file holds the modified
-abc\_blast\_filtered.txt file matching the input file format of
-DAGchainer:
-
- A1 BraA01g000010.3C 2944 3050 Chr1 AT1G43860.1 16622247 16622597 9.61E-56 188
- A1 BraA01g000010.3C 3058 3161 Chr3 AT3G04630.1 1259234 1259503 7.06E-33 125
-
-Note: After getting the abc\_blast\_filtered.txt file update query
-start, query end, subject start and subject end values incoorperating
-gene locus data from bed files of baseline species and polyploid species
-of interest. Then add chromosome which each gene belongs to in the bed
-file of each species before using DAGchainer.
-
-Here is a typical parameter setting for generating the
-abc\_synteny.aligncoords file:
-
- $ ./run_DAG_chainer.pl -i dir/abc_blast_filtered_modified.txt -s -I
-
-The abc\_synteny.aligncoords file holds pairwise synteny blocks after
-running DAGchainer :
-
- ## alignment A1 vs. Chr1 Alignment #1 score = 5177.6 (num aligned pairs: 121):
- A1 BraA01g026830.3C 17161339 17161504 Chr1 AT1G56580.1 21198405 21198568 2.180000e-109 50
- A1 BraA01g026890.3C 17191267 17191318 Chr1 AT1G57550.1 21312544 21312593 3.270000e-24 40
- A1 BraA01g026900.3C 17196325 17196618 Chr1 AT1G57610.3 21337612 21337818 8.840000e-106 84
-
-\- Usage Reads in two data files: abc\_blast\_filtered\_modified.txt &
-ref\_genelist.txt. The ref\_genelist.txt file holds gff file like
-details of baseline species :
-
- AT1G01010 AT1G01010.1 429 Chr1_1 Chr1 1 3631 5899 AT1G01010.1 NAC domain containing protein 1
- AT1G01020 AT1G01020.1 245 Chr1_2 Chr1 2 5928 8737 AT1G01020.1 Arv1-like protein
- AT1G01030 AT1G01030.1 358 Chr1_4 Chr1 4 11649 13714 AT1G01030.1 AP2/B3-like transcriptional factor family protein
-
-To run SyntenyLink\_st.pl you can simply use:
-
- $ perl SyntenyLink_st.pl -d abc_synteny.aligncoords -g ref_genelist.txt
-
-\- Output The execution of SyntenyLink\_st outputs four output files:
-abc\_synteny.success.colinear, abc\_synteny.failed.colinear,
-abc\_synteny.chains.passed & abc\_synteny.all.chains.
-
-The abc\_synteny.success.colinear file holds the main output file with
-the generated syntelog table in which the gene chains are incorporated
-into their corresponding chromosomes with redundant chains (likely due
-to gene duplications or tandem or segmental duplications in the
-polyploid genome) placed in the "overlap" column in the syntelog table:
-
- BraA01g000010.3C AT1G43860.1 74.194 124 14 3 80 186 231 353 9.61e-56 188
- BraA01g000010.3C AT3G04630.1 66.087 115 21 4 194 297 165 272 7.06e-33 125
- BraA01g000010.3C AT3G04630.3 66.087 115 21 4 194 297 164 271 7.88e-33 125
-
-The abc\_synteny.failed.colinear file holds the removed chains following
-the condition if the number of remaining colinear pairs are less than 6:
-
- A6_Chr1_4 Chr1 AT1G14070 BraA06g010220.3C
- A6_Chr1_4 Chr1 AT1G14080 BraA06g010230.3C
- A6_Chr1_4 Chr1 AT1G14100 x
- A6_Chr1_4 Chr1 AT1G14110 x
- A6_Chr1_4 Chr1 AT1G14120 x
- A6_Chr1_4 Chr1 AT1G14130 BraA06g010280.3C
- A6_Chr1_4 Chr1 AT1G14140 x
- A6_Chr1_4 Chr1 AT1G14150 x
- A6_Chr1_4 Chr1 AT1G14160 x
- A6_Chr1_4 Chr1 AT1G14170 x
- A6_Chr1_4 Chr1 AT1G14180 x
- A6_Chr1_4 Chr1 AT1G14185 x
-
-The abc\_synteny.chains.passed file holds the ids of set of passed
-chains with collinear pairs greater than 6:
-
- A7_Chr1_1
- A8.r_Chr1_1
- A9.r_Chr1_1
- A2_Chr1_1
- A6_Chr1_1
- A7.r_Chr1_1
-
-The abc\_synteny.all.chains file holds the all chains identified from
-DAGchainer:
-
- A1_Chr1_1 A1 BraA01g026830.3C 17161339 17161504 Chr1 AT1G56580.1 21198405 21198568 2.180000e-109 50
- A1_Chr1_1 A1 BraA01g026890.3C 17191267 17191318 Chr1 AT1G57550.1 21312544 21312593 3.270000e-24 40
- A1_Chr1_1 A1 BraA01g026900.3C 17196325 17196618 Chr1 AT1G57610.3 21337612 21337818 8.840000e-106 84
-
-SyntenyLink\_mbp
-----------------
-
-This program identifies the main breakpoints of translocations in the
-abc\_synteny.success.colinear file. It is is designed to detect
-fractionation gaps larger than a gap threshold. Synteny blocks capped by
-two breakpoints are grouped as a "super-synteny block" where gaps
-smaller than the gap threshold could exist within the super block. The
-input to this algorithm includes two parameters gap threshold, a minimum
-block length, and a data file syntelog table generated from Step 2,
-where collinear blocks are placed into the chromosomes of the organism.
-Next, the gene density of super-synteny blocks in each chromosome is
-calculated. This algorithm disregards densities below threshold density
-value. We selected a threshold density value of 0.1 in here. The
-chromosomes with gene density greater than 0.1 are ranked by the density
-of the blocks within the chromosome and assigned into candidate ð‘š
-subgenomes, where ð‘š denotes the ploidy level or the number of subgenomes
-to be reconstructed.
-
-\- Usage No input parameters or read in data files.
-
-Note: You need to select the most suitable gap threshold and minimum
-block length for your data by running the gap\_threshold\_selection.py
-and minimum\_block\_length\_selection.py scripts.
-
-Here is a typical parameter setting for obtaining optimal gap threshold
-and block length values for you data:
-
- $ python3 gap_threshold_selection.py -i abc_synteny.success.colinear
-
-Then get the optimal gap threshold value from the console and run the
-following command:
-
- $ python3 minimum_block_length_selection.py -i abc_synteny.success.colinear -g <output gap threshold value>
-
-\- Output Optimal gap threshold and block length values are printed to
-the console.
-
-\- Output The execution of SyntenyLink\_mbp outputs two output files:
-Super\_synteny\_block\_output.xlsx and
-Super\_synteny\_bl\_sub\_placement\_density.xlsx.
-
-The Super\_synteny\_block\_output.xlsx file holds the generated
-super-synteny blocks before removing the noise taking density threshold
-into account:
-
- Block no. Block_start Block_end Row start # Row end # # genes in block N1 N1.r N2 N2.r N3 N3.r N4 N4.r N5 N5.r N6 N6.r N7 N7.r N8 N8.r
- 1 AT1G01010 AT1G01560 0 57 58 0.0 0.0 0.0 0.3684210526315789 0.0 0.6666666666666666 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
- 2 AT1G01570 AT1G02205 58 123 66 0.0 0.0 0.43283582089552236 0.0 0.0 0.4626865671641791 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
- 3 AT1G02210 AT1G14900 124 1491 1368 0.005113221329437546 0.0 0.3951789627465303 0.005843681519357195 0.3915266617969321 0.0 0.0577063550036523 0.1891891891891892 0.0 0.0 0.07596785975164354 0.26004382761139516 0.0 0.0 0.0 0.0
-
-The Super\_synteny\_bl\_sub\_placement\_density.xlsx file holds the
-subgenome placements of super-synteny blocks based on gene density,
-after removing the noise taking density threshold into account:
-
- Block no. Block_start Block_end Row start # Row end # # genes in block N1 N1.r N2 N2.r N3 N3.r N4 N4.r N5 N5.r N6 N6.r N7 N7.r N8 N8.r N9 N9.r Non_zero subgenome1 subgenome2 subgenome3
- 1 AT1G01010 AT1G11860 0 1161 1162 0 0 0 0 0 0 0 0 0.544358312 0 0 0 0 0 0.354005168 0.308354866 0 0 3 N5 N8 N8.r
- 2 AT1G11870 AT1G13420 1162 1328 167 0 0 0 0 0 0 0 0 0 0.523809524 0 0 0 0 0.386904762 0.43452381 0 0 3 N5.r N8.r N8
- 3 AT1G13430 AT1G19470 1329 1957 629 0 0 0 0 0 0 0 0 0.598412698 0 0 0 0 0 0.33968254 0.422222222 0 0 3 N5 N8.r N8
-
-SyntenyLink\_wg
----------------
-
-This program uses a weighted direct graph to dynamically link blocks
-produced from Step 3 that are most likely to be in a subgenome using a
-combined information of fractionation and substitution patterns as well
-as continuity of gene chains. This algorithm takes two input parameters
-a1 and a2.
-
-\- Usage Reads in two data files: abc\_synteny.all.chains and
-abc\_blastn.blast. Two input parameters:a1 and a2.
-
-Note: You need to generate abc\_blastn.blast file by running nucleotide
-blast using cds fasta files of baseline species and polyploid species of
-interest.
-
-The abc\_blastn.blast file holds blast hits after running blastn between
-baseline species and polyploid species of interest:
-
- BraA01g000010.3C AT1G43860.1 78.706 371 25 6 239 558 692 1059 7.94e-91 335
-
-Here is a typical parameter setting for generating the abc\_blastn.blast
-file:
-
- $ makeblastdb -in ref_cds.fa -dbtype prot -out ref_cds
-
- $ blastall -i query_cds.fasta -p blastn -d ref_cds -m 8 -e 1e-5 -F F -v 5 -b 5 -o abc_blastn.blast -a 4
-
-Note: You need to select the most suitable a1 and a2 parameter values
-for your data, which accounts for adjusting weights of the graph.
-
-\- Output The execution of SyntenyLink\_wg outputs number of output
-files matching the number of subgenomes in the species of interest:
-Super\_synteny\_graph\_nodes\_sub{k}.xlsx. There will be m number of
-files. k represents the corresponding subgenome number.
-
-The Super\_synteny\_graph\_nodes\_sub{k}.xlsx file holds the nodes
-belong to each subgenome after traversing the graph:
-
- Row start # Row end # subgenome1 subgenome2 subgenome3
- 0 123 N10.r N9 N8.r
- 124 698 N10 N8.r N9.r
- 699 1029 N6 N9.r N8.r
-
-SyntenyLink\_sb
----------------
-
-This program retrieves genes "hidden" in small blocks that are missed in
-previous steps. Speciï¿¿cally, we consider the chromosome blocks with
-densities lower than d\<8= that are removed in previous steps in the
-generation of small blocks because these blocks may be more likely to
-exhibit ï¿¿ipping of synteny blocks between the forward and reverse
-strands resulting from segmental duplication. Following the generation
-of small blocks, small synteny blocks are incorporated into the
-corresponding super-synteny blocks, taking into account the subgenome
-placement of the super-synteny blocks as a reference.
-
-\- Usage No read in files Three input parameters: ws1, ws2 and ws3.
-
-Note: You need to select the most suitable window size parameters for
-subgenome1, subgenome2 and subgenome3.
-
-\- Output The execution of SyntenyLink\_sb outputs number of output
-files: abc\_synteny\_chromosome\_names.success.colinear.xlsx,
-subgenome\_placement\_blocks.all.xlsx and
-subgenome\_placement\_blocks.all\_sub{k}.xlsx; There will be m number of
-files. k represents the corresponding subgenome number.
-
-The abc\_synteny\_chromosome\_names.success.colinear.xlsx file holds the
-replaced gene id\'s with there corresponding chromosome names which they
-bellong to:
-
- Row start # Row end # subgenome1 subgenome2 subgenome3
- 0 123 N10.r N9 N8.r
- 124 698 N10 N8.r N9.r
- 699 1029 N6 N9.r N8.r
-
-The subgenome\_placement\_blocks.all.xlsx file holds the final placement
-of genes in subgenomes in step 5:
-
- Row start # Row end # subgenome1 subgenome2 subgenome3
- 0 123 N10.r N9 N8.r
- 124 698 N10 N8.r N9.r
- 699 1029 N6 N9.r N8.r
-
-The subgenome\_placement\_blocks.all\_sub{k}.xlsx file holds the optimal placement of genes in subgenomes for each subgenome. Ex: subgenome\_placement\_blocks.all\_sub1.xlsx::
-
-: Row start \# Row end \# subgenome1 subgenome2 subgenome3 0 75 N10.r
- N9 N8.r 76 78 N10.r N9.r N8.r 79 123 N10.r N9 N8.r 124 698 N10 N9.r
- N8.r
-
-SyntenyLink\_mn
----------------
-
-Aimed to optimize the subgenome placements for each block (a row in the
-subgenome matrix) based on neighbourhood considerations in a subgenome,
-maximize the number of continuous blocks/rows from the same chromosome.
-The algorithm utilizes two window sizes, up and down, which determine
-the number of blocks above and below a given block, to define a
-neighbourhood.
-
-\- Usage No read in files Two input parameters: wup wdwn.
-
-Note: You need to select the most suitable window up and window down
-parameters.
-
-\- Output The execution of SyntenyLink\_sb outputs number of output
-files: Final\_subgenome\_placement\_result.xlsx, Final\_result.xlsx.
-
-The Final\_subgenome\_placement\_result.xlsx file holds the final
-placement of chromosome blocks in subgenomes:
-
- Row start # Row end # subgenome1 subgenome2 subgenome3
- 0 75 N10.r N9 N8.r
- 76 78 N10.r N9.r N8.r
- 79 123 N10.r N9 N8.r
- 124 698 N10 N9.r N8.r
- 699 1035 N6 N9.r N8.r
- 1036 1036 N6 N9 N8.r
-
-The Final\_result.xlsx file holds the final placement of genes inside
-blocks in subgenomes:
-
- subgenome1 subgenome2 subgenome3
- BraA10g000880.3C x x
- BraA10g000870.3C x x
- BraA10g000860.3C x x
- BraA10g000850.3C x x
- BraA10g000830.3C BraA09g065940.3C x
- BraA10g000820.3C x x
- x BraA09g065960.3C x
- BraA10g000790.3C x x
- BraA10g000780.3C BraA09g065970.3C x
- BraA10g000770.3C BraA09g065980.3C x
-
-main\_script
-------------
-
-This holds the main script that runs all the above scripts in order. It
-takes in the following parameters: -i input\_file -g gap\_threshold -m
-minimum\_block\_length -n number\_of\_subgenomes -gt ground\_truth\_file
--c chains\_file -bl blastn\_file -a1 adjusment1 -a2 adjusment2 -ws1
-window\_size\_subgenome1 -ws2 window\_size\_subgenome2 -ws3
-window\_size\_subgenome3 -wup window\_up -wdwn window\_down
-
-Note: Before running main\_script.py, you need to run the
-SyntenyLink\_bf.pl and SyntenyLink\_st.pl scripts
-
-To run SyntenyLink\_sb.py you can simply use:
-
- $ python3 main_script.py -i abc_synteny.success.colinear -g -m -n -gt abc_groundtruth.xlsx -c abc_synteny.all.chains -bl abc_blastn.blast -a1 -a1 -a1 -a2 -a2 -a2 -ws1 -ws2 -ws3 -wup -wdwn
-
-\- Output The execution of main\_script outputs all the output files of
-the above scripts in the same directory as the input file.
-
-SyntenyLink\_acc
-----------------
-
-This holds the script that calculates the accuracy of the final
-placement of genes in subgenomes when there is a ground truth file.
-
-\- Usage One read in file: abc\_groundtruth.xlsx
-
-To run SyntenyLink\_sb.py you can simply use:
-
- $ python3 SyntenyLink_acc.py abc_groundtruth.xlsx
-
-\- Output The execution of SyntenyLink\_sb prints the subgenome
-placemnet accuracy of each subgenome:
-
- Exact match percentage for subgenome1: 84.15%
- Exact match number for subgenome1: 11490
- Missing genes for subgenome1: 2164
- Exact match percentage for subgenome2: 61.61%
- Exact match number for subgenome2: 6062
- Missing genes for subgenome2: 3778
- Exact match percentage for subgenome3: 65.30%
- Exact match number for subgenome3: 5635
- Missing genes for subgenome3: 2995
-
-Example
-=======
--
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