Code of Conduct

May 17, 2021 Announcement

Contributor Covenant Code of Conduct

Our Pledge

We as members, contributors, and leaders pledge to make participation in our community a harassment-free experience for everyone, regardless of age, body size, visible or invisible disability, ethnicity, sex characteristics, gender identity and expression, level of experience, education, socio-economic status, nationality, personal appearance, race, religion, or sexual identity and orientation.

We pledge to act and interact in ways that contribute to an open, welcoming, diverse, inclusive, and healthy community.

Our Standards

Examples of behavior that contributes to a positive environment for our community include:

• Demonstrating empathy and kindness toward other people
• Being respectful of differing opinions, viewpoints, and experiences
• Giving and gracefully accepting constructive feedback
• Accepting responsibility and apologizing to those affected by our mistakes, and learning from the experience
• Focusing on what is best not just for us as individuals, but for the overall community

Examples of unacceptable behavior include:

• The use of sexualized language or imagery, and sexual attention or advances of any kind
• Trolling, insulting or derogatory comments, and personal or political attacks
• Public or private harassment
• Publishing others’ private information, such as a physical or email address, without their explicit permission
• Other conduct which could reasonably be considered inappropriate in a professional setting

Enforcement Responsibilities

Community leaders are responsible for clarifying and enforcing our standards of acceptable behavior and will take appropriate and fair corrective action in response to any behavior that they deem inappropriate, threatening, offensive, or harmful.

Community leaders have the right and responsibility to remove, edit, or reject comments, commits, code, wiki edits, issues, and other contributions that are not aligned to this Code of Conduct, and will communicate reasons for moderation decisions when appropriate.

Scope

This Code of Conduct applies within all community spaces, and also applies when an individual is officially representing the community in public spaces. Examples of representing our community include using an official e-mail address, posting via an official social media account, or acting as an appointed representative at an online or offline event.

Enforcement

Instances of abusive, harassing, or otherwise unacceptable behavior may be reported to the community leaders responsible for enforcement at m.bui(at)anu.edu.au. All complaints will be reviewed and investigated promptly and fairly.

All community leaders are obligated to respect the privacy and security of the reporter of any incident.

Enforcement Guidelines

Community leaders will follow these Community Impact Guidelines in determining the consequences for any action they deem in violation of this Code of Conduct:

1. Correction

Community Impact: Use of inappropriate language or other behavior deemed unprofessional or unwelcome in the community.

Consequence: A private, written warning from community leaders, providing clarity around the nature of the violation and an explanation of why the behavior was inappropriate. A public apology may be requested.

2. Warning

Community Impact: A violation through a single incident or series of actions.

Consequence: A warning with consequences for continued behavior. No interaction with the people involved, including unsolicited interaction with those enforcing the Code of Conduct, for a specified period of time. This includes avoiding interactions in community spaces as well as external channels like social media. Violating these terms may lead to a temporary or permanent ban.

3. Temporary Ban

Community Impact: A serious violation of community standards, including sustained inappropriate behavior.

Consequence: A temporary ban from any sort of interaction or public communication with the community for a specified period of time. No public or private interaction with the people involved, including unsolicited interaction with those enforcing the Code of Conduct, is allowed during this period. Violating these terms may lead to a permanent ban.

4. Permanent Ban

Community Impact: Demonstrating a pattern of violation of community standards, including sustained inappropriate behavior, harassment of an individual, or aggression toward or disparagement of classes of individuals.

Consequence: A permanent ban from any sort of public interaction within the community.

Attribution

This Code of Conduct is adapted from the Contributor Covenant, version 2.0, available at https://www.contributor-covenant.org/version/2/0/code_of_conduct.html.

Community Impact Guidelines were inspired by Mozilla’s code of conduct enforcement ladder.

For answers to common questions about this code of conduct, see the FAQ at https://www.contributor-covenant.org/faq. Translations are available at https://www.contributor-covenant.org/translations.

PhD position in phylogenomic inference

Dec 12, 2019 Phd position

A PhD position is available in the lab of Dr. Minh Bui, https://researchers.anu.edu.au/researchers/bui-m, at the Research School of Computer Science, Australian National University (ANU). We are looking for a highly motivated student, who will work on the next generation of models and methods for phylogenetic analysis in the genomic era. There are a large number of potential directions that the research could take, and the details will depend on your interests and experience. Potential directions include: developing efficient algorithms for tree search; new approaches to phylogenetic model selection; co-estimating multiple trees. The student will implement new models and methods in the widely used IQ-TREE software (http://www.iqtree.org).

The ANU campus is situated in the heart of Australia’s capital city, Canberra, which is ranked as the third best city in the world according to Lonely Planet (2018) and is Australia’s most liveable city (Life in Australia Report 2019). The ANU has an international reputation for research excellence and is ranked among the best universities in the world (QS World University Ranking 2019).

Candidates: ANU scholarships are highly competitive, and cover all fees and a ~$27K stipend. In order to be put forward, you will need outstanding undergraduate marks and a first class honours or Masters by research (or be expecting to gain one by the middle of 2020) or equivalent research experience.

To apply, please send to m.bui (at) anu.edu.au a detailed CV, full academic transcripts, and a brief description of your research interests and how they intersect with this project.

The deadline is January 31, 2020.

IQ-TREE version 1.6.12

Aug 15, 2019 Release

Bugfixes:

• Incorrect pairwise distance (.mldist file) with +I or +R rate models (reported by Sishuo Wang).
• Crash with -o option when the outgroup is identical to another sequence (reported by Yang Song).
• Crash in ModelFinder for mixed data types with edge-linked partition models -spp option (reported by Bernardo Santos).
• Report error with -sup when target tree is not as “rooted/unrooted” as tree set (reported by Christian Rinke).
• Crash with multi-threading (-nt option) in Windows due to Clang compiler flag (reported by Wo Niu and others).

IQ-TREE version 1.6.11

Jun 6, 2019 Release

Important changes:

• Amino-acid frequencies of DAYHOFF, DCMUT, JTT, MTREV, WAG, CPREV, LG, MTZOA, PMB, JTTDCMUT, FLU are modified with higher precision and normalised to 1 (thanks Ben Redelings). This may lead to tiny change in log-likelihood (i.e. from 3 digit after comma) but does not affect +F model.

New features:

• Support ‘.’ syntax for alignment length in partition file (requested by Teofil Nakov).

Bugfixes:

• Crash with -bnni option and GENE/GENESITE resampling (reported by Emmanuel Cantu).
• Incorrect WARNING about bootstrap convergence with -bnni option (reported by Max_IT).
• Numerical issue with likelihood scaling for gcc under -O3 optimisation.
• Handling fixed substitution rates (reported by @bbuchfink).

IQ-TREE version 1.6.10

Feb 19, 2019 Release

Bugfixes:

• Crash with edge-unlinked model (-sp) and -bnni option (reported by Mark Miller).

IQ-TREE version 1.6.9

Dec 20, 2018 Release

Bugfixes:

• IMPORTANT: Incorrect AU test p-values with partition models, introduced in v1.6.8 (reported by Ales Bucek).
• Crash in ModelFinder when having codon partitions with different genetic codes (reported by Morgan Jackson).
• Crash with multiple runs option (--runs) and -bnni (reported by Vanessa Vera Fain).

Other changes:

• Better error checking for nexus partition file to prevent mis-specifying comma and semi-colon (reported by Denis Jacob Machado).
• Safe writing checkpoint file via a temporary file (reported by Giuseppe Aprea and thanks Heiko).
• -rcluster-max activates relaxed clustering algorithm without having to specify -rcluster.
• --no-outfiles suppress .treefile as expected (reported by Cecile Ane).

IQ-TREE version 1.6.8

Oct 28, 2018 Release

Important change:

• AU test is now available again using maximum likelihood estimates of p-values. See https://github.com/Cibiv/IQ-TREE/issues/86 for full details.

Bugfixes:

• Crash with model selection for mixed data type (reported by Paul Frandsen).
• Crash with model selection when partitions <= 2 (reported by Michele Leocadio).
• Reading non-reversible models from file.
• Error message “A taxon has no name” to “Redundant double-bracket”.

IQ-TREE version 1.6.7.1

Sep 7, 2018 Release

• Show more precision in log likelihood with --show-lh (thanks Benjamin Redelings)
• Reimplement -tina and -st MULTI option (requested by Ingo Ebersberger)

Bugfixes:

• Crash at the end with --runs and partition model (reported by David Maddison)

IQ-TREE version 1.6.7

Aug 23, 2018 Release

Important changes:

• Temporarily disable AU test due to unresolved numerical issue when bp-rell are all zeros.

Bugfixes:

• Checkpointing issue in ModelFinder for mixture models causing incorrect likelihoods with e.g. -madd C10 (reported by Juergen Strassert).
• Checkpointing Lie Markov models.
• (v1.6.6) Incomplete parsing of site positions of partition file (reported by Alexey Kozlov).
• Parsing polymorphic states from NEXUS file (reported by Steven Heritage).
• Use of only 1 thread when #partitions < #cores (reported by Alexey Kozlov).
• Double RAM usage for -bnni option (reported by Juergen Strassert).
• Over-bound for optimizeTreeLengthScaling causing too long branch lengths in extreme cases (reported by vikaszsi77).
• Exclude ORDERED model by default for morphological data due to frequent numerical underflow.
• (v1.6) -m ..MERGE.. wrong concatenateAlignments with missing data (reported by David Dunchene).
• Error message instead of crash when using -bsam with non-partition model (reported by Sarah Jensen).

IQ-TREE version 1.6.6

Jul 1, 2018 Release

This version contains a number of bugfixes and is highly recommended for all users.

Bugfixes:

• Issue with internal tree node names changed from slash to underscore (reported by JP Flandrois).
• Wrong FREQ_UNKNOWN assertion with protein mixture models, e.g. LG4X (reported by Giddy Landan).
• Disallow specifying both --runs with -lmap option (reported by Giap Nguyen).
• Reading nexus polymorphic characters for non-DNA data (reported by a web user).
• Amino-acid O (22nd amino-acid) is accepted as missing data (reported by Cuong Dang).
• Negative initial free-rates in rare cases (reported by Paul Frandsen).
• Memory leak in reading NEXUS alignment.
• Crash with resampling strategy (-bsam) for standard bootstrap (-b) and jackknife (-j option).
• Crash with standard bootstrap and partition merging (-m ...MERGE) (reported by Guoqing Li).
• Wrong error with codon models and -t RANDOM (reported by Karen Meusemann).
• Parsing error with blank chars in partition file (reported by David Maddison).
• Freezing caused by old Intel OpenMP library (reported by David Maddison).
• Too strict assertion about one applied NNI (reported by Karen Meusemann).
• Error message when specifying mixture with GHOST model (reported by Anja Spang).