Public Projects 2011

Description

Broccoli, a user-friendly pipeline designed to infer with high precision orthologous groups and pairs of proteins using a phylogeny-based approach. Briefly, Broccoli performs ultra-fast phylogenetic analyses on most proteins and builds a network of orthologous relationships. Orthologous groups are then identified from the network using a parameter-free machine learning algorithm (label propagation). Broccoli is also able to detect chimeric proteins resulting from gene-fusion events and to assign these proteins to the corresponding orthologous groups.

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2019-11-26T00:00:00Z

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A database of orthologous groups and functional annotation

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2011-07-07T00:00:00Z

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Orthologous pair predictions from OGs refined by phylogentic trees. Three missing species were mapped to closest homolog available.

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2011-07-07T00:00:00Z

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All-vs-all orthologous pair prediction using the smallest compatible OG in the eggNOG level hierarchy for each pair of reference species. Three missing species were mapped using eggNOG 4.5.

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2011-07-07T00:00:00Z

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Ensembl Compara pipeline (version 81) provides cross-species resources and analyses, at both the sequence level and the gene level, with modifications to only use amino-acid models in treebest

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2011-07-07T00:00:00Z

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Modified version of the vanilla pipeline to build trees with protein sequences only (no nucleotide sequence, no chromosome coordinates).Please be aware that the Xenopus tropicalis genes homologies are mostly wrong due to an error in the species tree used in the pipeline

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2011-07-07T00:00:00Z

Description

Hierarchical Orthologous Groups based on pairwise orthologs infered by OMA. The ideas and methodology are described in here, where as this version 2.0 makes use of the new bottom-up algorithm described in here and computed with OmaStandalone v2.5.

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2011-07-07T00:00:00Z

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Orthology inference method using a hierarchical approach. Hieranoid performs pairwise orthology analysis using InParanoid at each node in a guide tree as it progresses from its leaves to the root. It combines efficient graph-based methodology with aspects of compute-intensive tree-based methods

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2011-07-07T00:00:00Z

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InParanoid is a program for automatic identification of orthologs while differentiating between inparalogs and outparalogs. An InParanoid cluster is seeded by a reciprocally bestmatching ortholog pair, around which inparalogs are gathered independently, while outparalogs are excluded. The InParanoid database is a collection of pairwise ortholog groups aiming to include all 'completely sequenced' eukaryotic genomes. By this we mean above 6X coverage, and less than 1% X letters in the protein sequences. Two variants were tested in this study: this one is the regular InParanoid output containing all predicted pairs of orthologs

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2011-07-07T00:00:00Z

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InParanoid is a program for automatic identification of orthologs while differentiating between inparalogs and outparalogs. An InParanoid cluster is seeded by a reciprocally bestmatching ortholog pair, around which inparalogs are gathered independently, while outparalogs are excluded. The InParanoid database is a collection of pairwise ortholog groups aiming to include all 'completely sequenced' eukaryotic genomes. By this we mean above 6X coverage, and less than 1% X letters in the protein sequences. Two variants were tested in this study: this one is the high-confidence set including only orthologs with InParanoid's maximum confidence score of 1.0

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2011-07-07T00:00:00Z

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MetaPhOrs is a public repository of phylogeny-based orthologs and paralogs that were computed using phylogenetic trees available in twelve public repositories

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2011-07-07T00:00:00Z

Description

OMA is a publicly available resource (http://omabrowser.org/) that provides orthology predictions among thousands of proteomes from all domains of life. OMA uses evolutionary distance estimates from Smith���Waterman alignments to infer orthologs. A distinct feature among graph-based methods is the witness of nonorthology step in its pipeline, where cases of differential gene losses get detected. OMA provides three different groupings of orthologs: Pairs, Groups, and HOGs. Here, we constructed hierarchical orthologous groups (OMA HOGs). These are nested groups that contain genes that descend from a single common ancestral gene within a given taxonomic range using the GETHOGs algorithm.

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2011-07-07T00:00:00Z

Description

OMA is a publicly available resource (http://omabrowser.org/) that provides orthology predictions among thousands of proteomes from all domains of life. OMA uses evolutionary distance estimates from Smith���Waterman alignments to infer orthologs. A distinct feature among graph-based methods is the witness of nonorthology step in its pipeline, where cases of differential gene losses get detected. OMA provides three different groupings of orthologs: Pairs, Groups, and HOGs. OMA Groups consists of groups of genes in which all pairs are orthologs. In a graph representation with genes as nodes and orthology relations as edge, OMA groups correspond to fully connected subgraphs. Due to this definition, each OMA group includes at most one sequence per species. The primary intended application of these groups is to provide input data for phylogenetic inference.

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2011-07-07T00:00:00Z

Description

OMA is a publicly available resource (http://omabrowser.org/) that provides orthology predictions among thousands of proteomes from all domains of life. OMA uses evolutionary distance estimates from Smith���Waterman alignments to infer orthologs. A distinct feature among graph-based methods is the witness of nonorthology step in its pipeline, where cases of differential gene losses get detected. OMA provides three different groupings of orthologs: Pairs, Groups, and HOGs. The raw pairwise ortholog relationships form the OMA Pairs, a gene-centric view that lists all the orthologs for a given gene. The OMA Pairs are the primary product of the OMA pipeline. It is a list of high-confidence pairs of orthologous genes. OMA is based on an algorithm that compares genes on the basis of evolutionary distances, considers distance inference uncertainty, and accounts for differential gene losses.

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2011-07-07T00:00:00Z

Description

OMA Groups consists of groups of genes in which all pairs are orthologs. In a graph representation with genes as nodes and orthology relations as edge, OMA groups correspond to fully connected subgraphs. Due to this definition, each OMA group includes at most one sequence per species. The primary intended application of these groups is to provide input data for phylogenetic inference. In this instance of OMA Groups, the pairwise orthologs are based on the relations obtained with the refinements described in OMA 2.0 and computed with OmaStandalone v2.5. Additionally, the quasi-cliques that are compatible (no overlapping species) and where at least 50% of the maximal possible edges among the clusters are present, have been merged.

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2011-07-07T00:00:00Z

Description

The OMA Pairs are the primary product of the OMA pipeline. It is a list of high-confidence pairs of orthologous genes.OMA is based on an algorithm that compares genes on the basis of evolutionary distances, considers distance inference uncertainty, and accounts for differential gene losses.The version 2.0 has better support for fast evolving inparalogs, and it is computed with OmaStandalone v2.5. The changes are described in here.

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2011-07-07T00:00:00Z

Description

OrthoFinder 2.0 using BLAST and with default options. Command: "orthofinder -S blast -f 2011_04_reference_proteomes/" (defaults: DendroBLAST trees, species tree rooted by STRIDE, new OrthoFinder 2 orthologue inference from gene trees)

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2011-07-07T00:00:00Z

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OrthoFinder 2.0 using DIAMOND and with default options. Command: "orthofinder -S diamond_more_sensitive -f 2011_04_reference_proteomes/" (defaults: DendroBLAST trees, species tree rooted by STRIDE, new OrthoFinder 2 orthologue inference method from gene trees)

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2011-07-07T00:00:00Z

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OrthoFinder 2.0 using BLAST and multiple sequence alignment tree.Command: "orthofinder -S blast -f -M msa 2011_04_reference_proteomes/"

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2011-07-07T00:00:00Z

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OrthoInspector30 is a database of precomputed orthology and inparalogy relationships and a stand-alone package allowing large-scale predictions of orthology between thousands of proteomes (http://lbgi.fr/orthoinspector/) The specific version (v1.30) for the Quest for orthologs benchmark used a 1.10-9 blast Evalue threshold. The resource has recently undergone a major new release (2.0), with improved speed and visualisation tools, but the inference algorithm is unchanged from the initial graph-based method.

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2011-07-07T00:00:00Z

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The PANTHER (Protein ANalysis THrough Evolutionary Relationships) Classification System was designed to classify proteins (and their genes) in order to facilitate high-throughput analysis. PANTHER ALL will return all orthologs if more than one

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2011-07-07T00:00:00Z

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The PANTHER (Protein ANalysis THrough Evolutionary Relationships) Classification System was designed to classify proteins (and their genes) in order to facilitate high-throughput analysis. PANTHER LDO will return only least diverged ortholog for each gene (single best ortholog)

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2011-07-07T00:00:00Z

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PhylomeDB is a public database for complete catalogs of gene phylogenies (phylomes).

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2011-07-07T00:00:00Z

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Proteinortho is a tool to detect orthologous genes within different species. For doing so, it compares similarities of given gene sequences and clusters them to find significant groups. The algorithm was designed to handle large-scale data and can be applied to hundreds of species at one. Details can be found in Lechner et al., BMC Bioinformatics. 2011 Apr 28;12:124.

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2020-01-30T00:00:00Z

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Reciprocal best hits. Classic method consisting of identifying the pairs of genes with mutually highest alignment score between every pair of species. Use reciprocal blastp hits as orthologs, with minimum E-value of 1e���2, keep all hits that are ���99% of the highest score.

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2011-07-07T00:00:00Z

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Roundup is a large-scale orthology database. The orthologs are computed using the Reciprocal Smallest Distance (RSD) algorithm. Reciprocal Smallest Distance (RSD) is a pairwise orthology algorithm that uses global sequence alignment and maximum likelihood evolutionary distance between sequences to accurately detects orthologs between genomes. This dataset is computed using a divergence parameter of 0.8 and an E-value cutoff of 1e-5.

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2011-07-07T00:00:00Z

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version: 1.0.9 mode: sensitive Length difference threshold = 0.5

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2011-07-07T00:00:00Z

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version: 1.0.9 mode: sensitive Length difference threshold = 0.5

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2011-07-07T00:00:00Z

Description

version: 1.0.9 mode: sensitive Length difference threshold = 0.5

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2011-07-07T00:00:00Z