BioNERO - Biological Network Reconstruction Omnibus

BioNERO aims to integrate all aspects of biological network inference in a single package, including data preprocessing, exploratory analyses, network inference, and analyses for biological interpretations. BioNERO can be used to infer gene coexpression networks (GCNs) and gene regulatory networks (GRNs) from gene expression data. Additionally, it can be used to explore topological properties of protein-protein interaction (PPI) networks. GCN inference relies on the popular WGCNA algorithm. GRN inference is based on the "wisdom of the crowds" principle, which consists in inferring GRNs with multiple algorithms (here, CLR, GENIE3 and ARACNE) and calculating the average rank for each interaction pair. As all steps of network analyses are included in this package, BioNERO makes users avoid having to learn the syntaxes of several packages and how to communicate between them. Finally, users can also identify consensus modules across independent expression sets and calculate intra and interspecies module preservation statistics between different networks.

Last updated 24 days ago

softwaregeneexpressiongeneregulationsystemsbiologygraphandnetworkpreprocessingnetworknetworkinference

7.75 score 24 stars 1 packages 43 scripts 711 downloads

syntenet - Inference And Analysis Of Synteny Networks

syntenet can be used to infer synteny networks from whole-genome protein sequences and analyze them. Anchor pairs are detected with the MCScanX algorithm, which was ported to this package with the Rcpp framework for R and C++ integration. Anchor pairs from synteny analyses are treated as an undirected unweighted graph (i.e., a synteny network), and users can perform: i. network clustering; ii. phylogenomic profiling (by identifying which species contain which clusters) and; iii. microsynteny-based phylogeny reconstruction with maximum likelihood.

Last updated 24 days ago

softwarenetworkinferencefunctionalgenomicscomparativegenomicsphylogeneticssystemsbiologygraphandnetworkwholegenomenetworkcomparative-genomicsevolutionary-genomicsnetwork-sciencephylogenomicssyntenysynteny-network

6.48 score 21 stars 1 packages 12 scripts 210 downloads

doubletrouble - Identification and classification of duplicated genes

doubletrouble aims to identify duplicated genes from whole-genome protein sequences and classify them based on their modes of duplication. The duplication modes are i. segmental duplication (SD); ii. tandem duplication (TD); iii. proximal duplication (PD); iv. transposed duplication (TRD) and; v. dispersed duplication (DD). Transposon-derived duplicates (TRD) can be further subdivided into rTRD (retrotransposon-derived duplication) and dTRD (DNA transposon-derived duplication). If users want a simpler classification scheme, duplicates can also be classified into SD- and SSD-derived (small-scale duplication) gene pairs. Besides classifying gene pairs, users can also classify genes, so that each gene is assigned a unique mode of duplication. Users can also calculate substitution rates per substitution site (i.e., Ka and Ks) from duplicate pairs, find peaks in Ks distributions with Gaussian Mixture Models (GMMs), and classify gene pairs into age groups based on Ks peaks.

Last updated 24 days ago

softwarewholegenomecomparativegenomicsfunctionalgenomicsphylogeneticsnetworkclassificationbioinformaticscomparative-genomicsgene-duplicationmolecular-evolutionwhole-genome-duplication

6.25 score 11 stars 16 scripts 175 downloads

cogeqc - Systematic quality checks on comparative genomics analyses

cogeqc aims to facilitate systematic quality checks on standard comparative genomics analyses to help researchers detect issues and select the most suitable parameters for each data set. cogeqc can be used to asses: i. genome assembly and annotation quality with BUSCOs and comparisons of statistics with publicly available genomes on the NCBI; ii. orthogroup inference using a protein domain-based approach and; iii. synteny detection using synteny network properties. There are also data visualization functions to explore QC summary statistics.

Last updated 24 days ago

softwaregenomeassemblycomparativegenomicsfunctionalgenomicsphylogeneticsqualitycontrolnetworkcomparative-genomicsevolutionary-genomics

6.03 score 8 stars 15 scripts 158 downloads

HybridExpress - Comparative analysis of RNA-seq data for hybrids and their progenitors

HybridExpress can be used to perform comparative transcriptomics analysis of hybrids (or allopolyploids) relative to their progenitor species. The package features functions to perform exploratory analyses of sample grouping, identify differentially expressed genes in hybrids relative to their progenitors, classify genes in expression categories (N = 12) and classes (N = 5), and perform functional analyses. We also provide users with graphical functions for the seamless creation of publication-ready figures that are commonly used in the literature.

Last updated 24 days ago

softwarefunctionalgenomicsgeneexpressiontranscriptomicsrnaseqclassificationdifferentialexpressiongene-expressionhybridpolyploidyrna-seq

5.73 score 12 stars 2 scripts 179 downloads

cageminer - Candidate Gene Miner

This package aims to integrate GWAS-derived SNPs and coexpression networks to mine candidate genes associated with a particular phenotype. For that, users must define a set of guide genes, which are known genes involved in the studied phenotype. Additionally, the mined candidates can be given a score that favor candidates that are hubs and/or transcription factors. The scores can then be used to rank and select the top n most promising genes for downstream experiments.

Last updated 24 days ago

softwaresnpfunctionalpredictiongenomewideassociationgeneexpressionnetworkenrichmentvariantannotationfunctionalgenomicsnetwork

4.30 score 1 stars 2 scripts 139 downloads

planttfhunter - Identification and classification of plant transcription factors

planttfhunter is used to identify plant transcription factors (TFs) from protein sequence data and classify them into families and subfamilies using the classification scheme implemented in PlantTFDB. TFs are identified using pre-built hidden Markov model profiles for DNA-binding domains. Then, auxiliary and forbidden domains are used with DNA-binding domains to classify TFs into families and subfamilies (when applicable). Currently, TFs can be classified in 58 different TF families/subfamilies.

Last updated 24 days ago

softwaretranscriptionfunctionalpredictiongenomeannotationfunctionalgenomicshiddenmarkovmodelsequencingclassificationfunctional-genomicsgene-familieshidden-markov-modelsplant-genomicsplantsprotein-domainstranscription-factors

4.00 score 5 scripts 146 downloads

magrene - Motif Analysis In Gene Regulatory Networks

magrene allows the identification and analysis of graph motifs in (duplicated) gene regulatory networks (GRNs), including lambda, V, PPI V, delta, and bifan motifs. GRNs can be tested for motif enrichment by comparing motif frequencies to a null distribution generated from degree-preserving simulated GRNs. Motif frequencies can be analyzed in the context of gene duplications to explore the impact of small-scale and whole-genome duplications on gene regulatory networks. Finally, users can calculate interaction similarity for gene pairs based on the Sorensen-Dice similarity index.

Last updated 24 days ago

softwaremotifdiscoverynetworkenrichmentsystemsbiologygraphandnetworkgene-regulatory-networkmotif-analysisnetwork-motifsnetwork-science

4.00 score 1 stars 2 scripts 149 downloads