Datasets

Curated networks and clustering output from the manuscript: Well-Connected Communities in Real-World Networks https://arxiv.org/abs/2303.02813

Provides RNASim-VS2 datasets used in Gillian's Master's thesis.

This is a simulated sequence dataset generated using INDELible and processed via a sequence fragmentation procedure.

This upload contains one additional set of datasets (RNASim10k, ten replicates) used in Experiment 2 of the EMMA paper (appeared in WABI 2023): Shen, Chengze, Baqiao Liu, Kelly P. Williams, and Tandy Warnow. "EMMA: A New Method for Computing Multiple Sequence Alignments given a Constraint Subset Alignment". The zipped file has the following structure: 10k |__R0 |__unaln.fas |__true.fas |__true.tre |__R1 ... # Alignment files: 1. `unaln.fas`: all unaligned sequences. 2. `true.fas`: the reference alignment of all sequences. 3. `true.tre`: the reference tree on all sequences. For other datasets that uniquely appeared in EMMA, please refer to the related dataset (which is linked below): Shen, Chengze; Liu, Baqiao; Williams, Kelly P.; Warnow, Tandy (2022): Datasets for EMMA: A New Method for Computing Multiple Sequence Alignments given a Constraint Subset Alignment. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-2567453_V1

This repository includes datasets for the paper "Re-evaluating Deep Neural Networks for Phylogeny Estimation: The issue of taxon sampling" accepted for RECOMB2021 and submitted to Journal of Computational Biology. Each zipped file contains a README.

This dataset provides the data for Nguyen, Nam-phuong, et al. "TIPP: taxonomic identification and phylogenetic profiling." Bioinformatics 30.24 (2014): 3548-3555.

This dataset provides the data for Mirarab, Siavash, Nam Nguyen, and Tandy Warnow. "SEPP: SATé-enabled phylogenetic placement." Biocomputing 2012. 2012. 247-258.

Datasets used in the study, "TRACTION: Fast non-parametric improvement of estimated gene trees," accepted at the Workshop on Algorithms in Bioinformatics (WABI) 2019.

This dataset contains the data for PASTA and UPP. PASTA data was used in the following articles: Mirarab, Siavash, Nam Nguyen, Sheng Guo, Li-San Wang, Junhyong Kim, and Tandy Warnow. “PASTA: Ultra-Large Multiple Sequence Alignment for Nucleotide and Amino-Acid Sequences.” Journal of Computational Biology 22, no. 5 (2015): 377–86. doi:10.1089/cmb.2014.0156. Mirarab, Siavash, Nam Nguyen, and Tandy Warnow. “PASTA: Ultra-Large Multiple Sequence Alignment.” Edited by Roded Sharan. Research in Computational Molecular Biology, 2014, 177–91. UPP data was used in: Nguyen, Nam-phuong D., Siavash Mirarab, Keerthana Kumar, and Tandy Warnow. “Ultra-Large Alignments Using Phylogeny-Aware Profiles.” Genome Biology 16, no. 1 (December 16, 2015): 124. doi:10.1186/s13059-015-0688-z.

This dataset contains the data for 16S and 23S rRNA alignments including their reference trees. The original alignments are from the Gutell Lab CRW, currently located at https://crw-site.chemistry.gatech.edu/DAT/3C/Alignment/.

This dataset contains the data for SATe-I. SATe-I data was used in the following article: K. Liu, S. Raghavan, S. Nelesen, C. R. Linder, T. Warnow, "Rapid and Accurate Large-Scale Coestimation of Sequence Alignments and Phylogenetic Trees," Science, vol. 324, no. 5934, pp. 1561-1564, 19 June 2009.

This page provides the data for SuperFine, DACTAL, and BeeTLe publications. - Swenson, M. Shel, et al. "SuperFine: fast and accurate supertree estimation." Systematic biology 61.2 (2012): 214. - Nguyen, Nam, Siavash Mirarab, and Tandy Warnow. "MRL and SuperFine+ MRL: new supertree methods." Algorithms for Molecular Biology 7 (2012): 1-13. - Neves, Diogo Telmo, et al. "Parallelizing superfine." Proceedings of the 27th Annual ACM Symposium on Applied Computing. 2012. - Nelesen, Serita, et al. "DACTAL: divide-and-conquer trees (almost) without alignments." Bioinformatics 28.12 (2012): i274-i282. - Liu, Kevin, and Tandy Warnow. "Treelength optimization for phylogeny estimation." PLoS One 7.3 (2012): e33104.

This repository includes scripts and datasets for the paper, "TreeMerge: A new method for improving the scalability of species tree estimation methods." The latest version of TreeMerge can be downloaded from Github (https://github.com/ekmolloy/treemerge).

This repository includes scripts and datasets for the paper, "Statistically consistent divide-and-conquer pipelines for phylogeny estimation using NJMerge." All data files in this repository are for analyses using the logdet distance matrix computed on the concatenated alignment. Data files for analyses using the average gene-tree internode distance matrix can be downloaded from the Illinois Data Bank (https://doi.org/10.13012/B2IDB-1424746_V1). The latest version of NJMerge can be downloaded from Github (https://github.com/ekmolloy/njmerge).<br /> <strong>List of Changes:</strong> &bull; Updated timings for NJMerge pipelines to include the time required to estimate distance matrices; this impacted files in the following folder: <strong>data.zip</strong> &bull; Replaced "Robinson-Foulds" distance with "Symmetric Difference"; this impacted files in the following folders: <strong> tools.zip; data.zip; scripts.zip</strong> &bull; Added some additional information about the java command used to run ASTRAL-III; this impacted files in the following folders: <strong>data.zip; astral64-trees.tar.gz (new)</strong>

HGT+ILS datasets from Davidson, R., Vachaspati, P., Mirarab, S., & Warnow, T. (2015). Phylogenomic species tree estimation in the presence of incomplete lineage sorting and horizontal gene transfer. BMC genomics, 16(10), 1-12. Contains model species trees, true and estimated gene trees, and simulated alignments.

This upload contains all datasets used in Experiment 2 of the EMMA paper (appeared in WABI 2023): Shen, Chengze, Baqiao Liu, Kelly P. Williams, and Tandy Warnow. "EMMA: A New Method for Computing Multiple Sequence Alignments given a Constraint Subset Alignment". The zip file has the following structure (presented as an example): salma_paper_datasets/ |_README.md |_10aa/ |_crw/ |_homfam/ |_aat/ | |_... |_... |_het/ |_5000M2-het/ | |_... |_5000M3-het/ ... |_rec_res/ Generally, the structure can be viewed as: [category]/[dataset]/[replicate]/[alignment files] # Categories: 1. 10aa: There are 10 small biological protein datasets within the `10aa` directory, each with just one replicate. 2. crw: There are 5 selected CRW datasets, namely 5S.3, 5S.E, 5S.T, 16S.3, and 16S.T, each with one replicate. These are the cleaned version from Shen et. al. 2022 (MAGUS+eHMM). 3. homfam: There are the 10 largest Homfam datasets, each with one replicate. 4. het: There are three newly simulated nucleotide datasets from this study, 5000M2-het, 5000M3-het, and 5000M4-het, each with 10 replicates. 5. rec\_res: It contains the Rec and Res datasets. Detailed dataset generation can be found in the supplementary materials of the paper. # Alignment files There are at most 6 `.fasta` files in each sub-directory: 1. `all.unaln.fasta`: All unaligned sequences. 2. `all.aln.fasta`: Reference alignments of all sequences. If not all sequences have reference alignments, only the sequences that have will be included. 3. `all-queries.unaln.fasta`: All unaligned query sequences. Query sequences are sequences that do not have lengths within 25% of the median length (i.e., not full-length sequences). 4. `all-queries.aln.fasta`: Reference alignments of query sequences. If not all queries have reference alignments, only the sequences that have will be included. 5. `backbone.unaln.fasta`: All unaligned backbone sequences. Backbone sequences are sequences that have lengths within 25% of the median length (i.e., full-length sequences). 6. `backbone.aln.fasta`: Reference alignments of backbone sequences. If not all backbone sequences have reference alignments, only the sequences that have will be included. >If all sequences are full-length sequences, then `all-queries.unaln.fasta` will be missing. >If fewer than two query sequences have reference alignments, then `all-queries.aln.fasta` will be missing. >If fewer than two backbone sequences have reference alignments, then `backbone.aln.fasta` will be missing. # Additional file(s) 1. `350378genomes.txt`: the file contains all 350,378 bacterial and archaeal genome names that were used by Prodigal (Hyatt et. al. 2010) to search for protein sequences.

Data sets from "DISCO+QR: Rooting Species Trees in the Presence of GDL and ILS." It contains trees and sequences simulated with gene duplication and loss under a variety of different conditions. Note: - trees.tar.gz contains the simulated gene-family trees used in our experiments (both true trees from SimPhy as well as trees estimated from alignments). - alignments.tar.gz contains simulated sequence data used for estimating the gene-family trees

Simulated sequences provide a way to evaluate multiple sequence alignment (MSA) methods where the ground truth is exactly known. However, the realism of such simulated conditions often comes under question compared to empirical datasets. In particular, simulated data often does not display heterogeneity in the sequence lengths, a common feature in biological datasets. In order to imitate sequence length heterogeneity, we here present a set of data that are evolved under a mixture model of indel lengths, where indels have an occasional chance of being promoted to long indels (emulating large insertion/deletion events, e.g., domain-level gain/loss). This dataset is otherwise (e.g., in GTR parameters) analogous to the 1000M condition as presented in the SATe paper (doi: 10.1126/science.1171243) but with 5000 sequences and simulated with INDELible (http://abacus.gene.ucl.ac.uk/software/indelible/). For more information, see README.txt. For the INDELible control files, see https://github.com/ThisBioLife/5000M-234-het.

This upload includes the 16S.B.ALL in 100-HF condition (referred to as 16S.B.ALL-100-HF) used in Experiment 3 of the WITCH paper (currently accepted in principle by the Journal of Computational Biology). 100-HF condition refers to making sequences fragmentary with an average length of 100 bp and a standard deviation of 60 bp. Additionally, we enforced that all fragmentary sequences to have lengths > 50 bp. Thus, the final average length of the fragments is slightly higher than 100 bp (~120 bp). In this case (i.e., 16S.B.ALL-100-HF), 1,000 sequences with lengths 25% around the median length are retained as "backbone sequences", while the remaining sequences are considered "query sequences" and made fragmentary using the "100-HF" procedure. Backbone sequences are aligned using MAGUS (or we extract their reference alignment). Then, the fragmentary versions of the query sequences are added back to the backbone alignment using either MAGUS+UPP or WITCH. More details of the tar.gz file are described in README.txt.

Thank you for using these datasets! These files contain trees and reference alignments, as well as the selected query sequences for testing phylogenetic placement methods against and within the SCAMPP framework. There are four datasets from three different sources, each containing their source alignment and "true" tree, any estimated trees that may have been generated, and any re-estimated branch lengths that were created to be used with their requisite phylogenetic placement method. Three biological datasets (16S.B.ALL, PEWO/LTP_s128_SSU, and PEWO/green85) and one simulated dataset (nt78) is contained. See README.txt in each file for more information.

This is a general description of the datasets included in this upload; details of each dataset can be found in the individual README.txt in each compressed folder. We have: 1. ROSE-HF.tar.gz 2. ROSE-LF.tar.gz HF (high fragmentary): 50% of the sequences are made fragmentary, which have average lengths of 25% of the original lengths with a standard deviation of 60 bp. LF (low fragmentary): 25% of the sequences are made fragmentary, which have average lengths of 50% of the original lengths with a standard deviation of 60 bp. The seven ROSE datasets made fragmentary are: 1000L1, 1000L3, 1000L4, 1000M3, 1000S1, 1000S2 and 1000S4. "ROSE-HF.tar.gz" contains HF versions of the seven ROSE datasets. "ROSE-LF.tar.gz" contains LF versions of the seven ROSE datasets.

This dataset contains re-estimated gene trees from the ASTRAL-II [1] simulated datasets. The re-estimated variants of the datasets are called MC6H and MC11H -- they are derived from the MC6 and MC11 conditions from the original data (the MC6 and MC11 names are given by ASTRID [2]). The uploaded files contain the sequence alignments (half-length their original alignments), and the re-estimated species trees using FastTree2. Note: - "mc6h.tar.gz" and "mc11h.tar.gz" contain the sequence alignments and the re-estimated gene trees for the two conditions - the sequence alignments are in the format "all-genes.phylip.splitted.[i].half" where i means that this alignment is for the i-th alignment of the original dataset, but truncating the alignment halving its length - "g1000.trees" under each replicate contains the newline-separated re-estimated gene trees. The gene trees were estimated from the above described alignments using FastTree2 (version 2.1.11) command "FastTree -nt -gtr" [1]: Mirarab, S., & Warnow, T. (2015). ASTRAL-II: coalescent-based species tree estimation with many hundreds of taxa and thousands of genes. Bioinformatics, 31(12), i44-i52. [2]: Vachaspati, P., & Warnow, T. (2015). ASTRID: accurate species trees from internode distances. BMC genomics, 16(10), 1-13.

This dataset contains 1) the cleaned version of 11 CRW datasets, 2) RNASim10k dataset in high fragmentation and 3) three CRW datasets (16S.3, 16S.T, 16S.B.ALL) in high fragmentation.