wQFM (version 1.4)

Notice to all the users

Short Description

Execution dependencies

Packages, Programming Languages and Operating Systems Requirements

Files Structure

Input and Output formats for wQFM

Input

Input file containing weighted quartets (default)

((A,B),(C,D)); 34((A,C),(B,D)); 125((B,C),(D,E)); 431((A,B),(E,F)); 256((C,D),(E,F)); 992((A,C),(E,F)); 121

Input file containing gene trees (optional). See-im/--input_mode option as described below.

((3,((11,(10,((5,6),(9,(7,8))))),4)),2,1);(3,(2,(4,(11,(9,((7,8),((5,6),10)))))),1);(((2,(11,((5,6),((7,8),(10,9))))),3),4,1);(2,((11,(10,((8,7),((6,5),9)))),(4,3)),1);((11,((10,((7,6),(9,8))),5)),((4,2),3),1);

Output

- Without branch support (annotation level 0)((D,(B,(A,C))),(E,F));- With branch support measured as the average no of quartets that agree with a branch (annotation level 1)((D,(B,(A,C)123.0)269.3333333333333)456.3333333333333,(E,F)456.3333333333333);- With branch support measured as the proportion of quartets in your gene trees that agree with a branch (annotation level 2)((D,(B,(A,C)0.8930817610062893)1.0)1.0,(E,F)1.0);- With branch support measured as the proportion of quartets in gene trees, weights being normalized by the most dominant topology's weight (annotation level 3)((D,(B,(A,C)1.0)1.0)1.0,(E,F)1.0);

Running the application.

For generating embedded weighted quartets, use the script "quartet-controller.sh".

./quartet-controller.sh"input-gene-tree-file-name""output-quartet-file-name"

To run using weighted quartets as input file, simply use -i and -o flags

# Default mode, uses [s] - [v] as partition score.java -jar wQFM-v1.4.jar -i"input-file-name" -o"output-file-name"

To run directly using gene trees, use -im/--input_mode argument.

# Uses the -im/--input_mode as gene-trees (see Relevant Multiple Options below for details).java -jar wQFM-v1.4.jar -i"input-file-gene-trees" -o"output-file-name" -im gene-trees

To infer branch supports

# Annotate branches with average quartet support (the average weights of quartets in your gene trees that agree with a branch)java -jar wQFM-v1.4.jar -i"input-file-name" -o"output-file-name" -t 1# Annotate branches with normalized average quartet support (the proportion of quartets in your gene trees that agree with a branch)java -jar wQFM-v1.4.jar -i"input-file-name" -o"output-file-name" -t 2# Annotate branches with normalized average quartet support (normalized over the most dominant topology's weight, so this option will provide highest possible branch support if all dominant quartets agree with a branch)java -jar wQFM-v1.4.jar -i"input-file-name" -o"output-file-name" -t 3## Eg. if you have python setup instead of python3. Now, the scripts will be called using "python <script-name.py> [args]"java -jar wQFM-v1.4.jar -i"input-file-name" -o"output-file-name" -t 1 -pe python

# eg. using annotations level of 1 (use -pe python if you have python setup instead of python3)java -jar wQFM-v1.4.jar -i"input-file-weighted-quartets" -st"species-tree-without-annotations" -o"species-tree-with-annotations" -t 1

To infer quartet scores

# Use q = 1 to get only the total weight of quartets that are satisfied by the given produced species tree# Use q = 2 to get total weight of satisfied quartets, total weight of quartets present in the input wqrts file, and proportion of quartets satisfied.# Run wQFM input and output using quartet scoresjava -jar wQFM-v1.4.jar -i"input-file-name" -o"output-file-name" -q 1# just prints quartet score details on console.java -jar wQFM-v1.4.jar -i"input-file-name" -o"output-file-name" -q 1 -qo"qscore-details.txt"# for convenience, dumps to a file.## Eg. if you have python setup instead of python3. Now, the scripts will be called using "python <script-name.py> [args]"java -jar wQFM-v1.4.jar -i"input-file-name" -o"output-file-name" -q 2 -pe python

# Just to get the quartet scores without generating any estimated species treejava -jar wQFM-v1.4.jar -i"input-file-weighted-quartets" -st"species-tree-file" -q 2# to print on consolejava -jar wQFM-v1.4.jar -i"input-file-weighted-quartets" -st"species-tree-file" -q 2 -qo"qscore-details.txt"# to dump to a file

Relevant Multiple Options

-i, --input_file=<inputFileName>The input file name/path(default:for weighted quartets, see option -im/--input_modefor details)-o, --output_file=<outputFileNameSpeciesTree>The output file name/pathfor (estimated) species tree-im, --input_mode=<inputFileMode>                  im=<weighted-quartets> (default)                  im=<gene-trees> when input file consists of gene trees-t, --annotations_level=<annotationsLevel>t=0for none (default)t=1for annotations using quartet supportt=2for annotations using quartet support normalized by sumt=3for annotations using quartet support nomralized by max-st, --species_tree=<speciesTreeFileName>If given, will run annotations and provide to output file(will NOT run wQFM)-beta, --partition_score_beta=<beta>(default)then beta = 1, hence [s]-[v] usedbeta=<BETA>for 1[ws] -<BETA>[wv] partition scorebeta="dyanmic"then dynamic bin heuristic is used.-q, --quartet_score_level=<quartetScoreLevel>q=0:do not show quartet score(default)q=1: show quartet score onlyq=2: show quartet score, total weight of quartets, proportion of quartets satisfied-qo, --quartet_score_output_file=<quartetScoreOutputFile>    (default) null    If given, quartet scores will be output here.-pe, --python_engine=<pythonEngine>(default) python3(otherwise) pythoni.e. If you have"python" setupin your O.S.,then scripts will be run using"python <script.py> [args]"-h, --help      Show thishelp message and exit.-V, --version   Print version information and exit.

For large number of taxa, increasing the memory available to Java is recommended.

# Example: To supply 8GB of free memory.java -Xmx8000M -jar wQFM-v1.4.jar -i"input-file-name" -o"output-file-name"

For now, wQFM cannot handlestars which is induced due to polytomy in gene trees.

eg. (a,b,c,d); 10This will be produced as a "quartet" if a star is present in the initial gene tree.If wQFM is run and the input weighted quartets file contains such a star, then wQFM will terminate giving a prompt.

Datasets

Acknowledgements

License

Citation (BibTeX)

@article{10.1093/bioinformatics/btab428,    author = {Mahbub, Mahim and Wahab, Zahin and Reaz, Rezwana and Rahman, M Saifur and Bayzid, Md. Shamsuzzoha},    title = "{wQFM: Highly Accurate Genome-scale Species Tree Estimation from Weighted Quartets}",    journal = {Bioinformatics},    year = {2021},    month = {06},    abstract = "{Species tree estimation from genes sampled from throughout the whole genome is complicated due to the gene tree-species tree discordance. Incomplete lineage sorting (ILS) is one of the most frequent causes for this discordance, where alleles can coexist in populations for periods that may span several speciation events. Quartet-based summary methods for estimating species trees from a collection of gene trees are becoming popular due to their high accuracy and statistical guarantee under ILS. Generating quartets with appropriate weights, where weights correspond to the relative importance of quartets, and subsequently amalgamating the weighted quartets to infer a single coherent species tree can allow for a statistically consistent way of estimating species trees. However, handling weighted quartets is challenging.We propose wQFM, a highly accurate method for species tree estimation from multi-locus data, by extending the quartet FM (QFM) algorithm to a weighted setting. wQFM was assessed on a collection of simulated and real biological datasets, including the avian phylogenomic dataset which is one of the largest phylogenomic datasets to date. We compared wQFM with wQMC, which is the best alternate method for weighted quartet amalgamation, and with ASTRAL, which is one of the most accurate and widely used coalescent-based species tree estimation methods. Our results suggest that wQFM matches or improves upon the accuracy of wQMC and ASTRAL.wQFM is available in open source form at https://github.com/Mahim1997/wQFM-2020Supplementary data are available at Bioinformatics online.}",    issn = {1367-4803},    doi = {10.1093/bioinformatics/btab428},    url = {https://doi.org/10.1093/bioinformatics/btab428},    note = {btab428},    eprint = {https://academic.oup.com/bioinformatics/advance-article-pdf/doi/10.1093/bioinformatics/btab428/38489242/btab428.pdf},}

Bug Report