AMPtk / Amplicon ToolKit
Produces improved results of variable length amplicons from HTAS. AMPtk is a bioinformatic pipeline developed to specifically address the quality issues identified by using spike-in mock communities. It analyzes variable length amplicon studies such as the fungal ITS1 or ITS2 molecular barcodes. This method provides the scientific community with a necessary tool to study fungal community diversity.
Provides a free volume (3D image) viewer and segmentation tool. BrainSeg3D is a graphic application that make segmentation of volumes more accurate by providing tools for semi-automated segmentation combined with a user friendly graphic interface. This application is based on Seg3D, a free volume segmentation and processing tool. It was developed for medical professionals who need to perform image analysis as part of their research or for researchers working in the field of image analysis.
Evaluation of similarity measures
Provides a protocol that enables a thorough, optimization-independent, and systematic statistical evaluation of important similarity measure properties. Evaluation of similarity measures includes Accuracy (ACC), Distinctiveness of the Optimum (DO), Capture Range (CR), Number of Local Minima (NOM), Risk of Non-convergence (RON). The evaluation consists of three steps: (i) sampling of the parametrical space, (ii) computation of similarity measure values and (iii) computation of similarity measure properties.
TiDAL / Time-Dependent Activity Linker
Provides an integrative, time-centric method for antiviral network inference. TIDAL is a web application that creates a global view of the transcriptional network from a gene-expression time-series, identifies the transcriptions factors (TF) and relies them into a unified temporally-aware transcriptional cascade. It was applied to study data from influenza and measles.
Allows users to estimate Germinal Center (GC) volumes from standard multidimensional image data. pyBioImage is a cross-platform bioimaging application which supports several data formats and provides a way for visualization and analysis. The application includes a module: ExtractGC, based on a pseudo-recursive segmentation algorithm, which allows users to visualize the GC volumes in 3D while providing GC size and volume statistics.
Allows users to simulate the effect of peptide vaccination in cancer therapy. VaccImm provides a web platform allowing three kinds of analysis: prostate, kidney or a personalized simulation based on user-defined inputs. The application is able to model cancer immunotherapy based on cancer epitope sequences and major histocompatibility complex (MHC) genotypes. It includes a personal workspace for saving the simulations and an exchange forum.
GeVaDSs / Genetic Vaccine Decision Support system
Provides a platform for handle experimental results. GeVADSs is composed of modules that can be separated into two groups: (i) vaccine related modules, to process the biological data such as B-cell or t-cell module, and (ii) support modules, which manage data entry, report generation and data access such as quality control module. The application aims to improve development of novel vaccines by authorizing to analyze and compare data from different laboratories.
Offers visualization of the information relevant to selection of immunogen peptide sequences AbDesigner identifies optimal immunizing peptides for antibody production using a peptide-based strategy. It includes commonplace measures, such as conservation, hydropathy, possible modification sites, transmembrane domains. It also provides specialized display of 3D structural information from the Protein Data Bank (PDB), allowing users to view all information extracted from UniProt and PDB databases interactively.
OSCAR / Optimized Side-Chain Atomic eneRgy
Permits to models protein side-chain. OSCAR proposes several functions as (1) OSCAR-o for orientation-dependent energy functions and (2) OSCAR-d for distance-dependent energy functions. This tool was developed for the protein tertiary structure prediction using the high quality energy functions.
Allows users to compute multiple sequence alignments (MSA). MAFFTash is a web application that authorizes to perform sequences and structures through two software in a row. First, inputs are submitted to the ash tool: a structural alignment program which maximize the number of structurally equivalent residues between two proteins. Then, the structural alignment is analyzed by MAFFT to build the most consistent overall multiple alignment corresponding to it.
ASH / Alignment of Structural Homologs
Provides a structural alignment program. ASH, based on a double dynamic programming algorithm, intends to maximize the number of structurally equivalent residues between two proteins. The application includes functions for query and template PDB files as well as options for processing superposition and rotate structures. Moreover, the software provides tools for perform a faster alignment (RASH) or to align structures with multiple solutions (GASH).
REMOCOD / REgulatory MOtif COmbination Detector
Identifies pairs of transcription factor binding sites (TFBSs) in sequences of a set of co-regulated genes thanks to gene IDs. REMOCOD provides a web interface which detects over-represented TFBSs in the analyzed sequences and then, infers the corresponding regulatory motifs related to these. The software includes with an optional function permitting users to remove redundancy. It can be run only for men and mice’ genes.
SeSaw / Sequence-derived Structure Amignment Weights
Allows users to determine conserved sequence and structural motifs in proteins. SeSaw is a web application which provides a list of the templates accompanied by their corresponding annotated alignments and 3D structural superpositions, ranked by similarity. Users can choose to visualize all hits or only the representatives one. The software can be applied to structural genomics targets, homology models and immunology.
Allows users to identify peptide antigens and homologous peptide antigens. PAComplx is a web application which takes into account two T-cell receptors binding to peptide-major histocompatibility complexes (TCR–pMHC) interfaces from complete pathogen genome and experimental peptide databases. The application gives access to a wide range of information such as detailed atomic interactions, amino acid compositions of peptide families or source proteins.
Determines the conserved loci of rRNA genes’ orientation. V-REVCOMP is a standalone software, based on hidden Markov models (HMM), that is able to detect and reorient reverse complementary ribosomal sequences. Moreover, it highlights sequences with uncertain assignments or no detected HMM regions in any orientation. As well, it can also be used for detecting various sequence anomalies.
DynaMiteC / Dynamic Modeling and Clustering
Allows users to describe dynamics of the transcriptional response to a stimulus. DynaMiteC is a standalone software, based on a two-impulse model, which provides a method for generate time course gene-expression profiles while classifying them into clusters corresponding to different dynamical responses. The software was tested by detecting inflammation and anti-viral stimuli which can be find in mice primary dendritic cells.
Allows users to predict potential epitopes on protein. LocaPep is a standalone software, based on a new clusters algorithm, which allows prediction thanks to information provided by mapping peptides from a phage display library. The software provides a unique prediction that, by construction, is composed of close residues forming a single patch in the antigen surface.
ATIVS / Analysis Tools for Influenza virus surveillance
Provides a web application for generating antigenic maps. ATIVS can perform two types of analysis: a serological data analysis for all influenza subtypes and HA1 sequence data for influenza A/H3N2 viruses; and, a sequence data analysis to obtain predicted antigenic distances calculating until 500 sequences. It aims to help in observing antigenic evolution of influenza viruses and facilitate the selection of vaccine strains.
Manages data for high-throughput cytometry environments. WebFlow is an application, available from both a web application and a standalone software, which provides functionalities for: (i) data annotation, (ii) drawing gates and defining populations, (iii) exporting or visualizing data via heat maps and (iv) calculating standards and custom statistics. It aims to supply a unique platform to improve analysis and detection speed and accuracy.
Automates processing of intensity-based cell image segmentation. FLIM-FRET analyzer can separate objects of interest from the background to delineate whole cells. It simplifies image segmentation into single cells followed by donor lifetime and donor/acceptor fluorescence intensity quantification. For the software to work, users have to create a FRET collection which associates fluorescent intensity and fluorescence decay image datasets. To create a FRET collection, users import the donor and acceptor fluorescent channels and the donor fluorescence decay curves.
Allows identification of gene pairs associated with biological phenotype or clinical outcome. This program is an equivalent model subject to a sum-to-zero constraint on regression coefficients. It works jointly with an algorithm based on the alternating direction method of multipliers (ADMM). This association permits especially identification and model parameter estimation. This tool can cover compositional data and reference point insensitive data.
FLIMX / FLIM eXplorer
Allows the analysis of fluorescence lifetime imaging ophthalmoscopy (FLIO) data. FLIMX corrects the influence of the crystalline lens fluorescence on the approximated fluorescence lifetime of the retina. It implements known multi-exponential and stretched exponential approaches, as well as new layer-based multi-exponential approaches. It also grafts stochastic and deterministic minimization algorithms to determine the fluorescence lifetime parameters.
Allows generation of connected sub-graphs from datasets of RNA-Seq reads. MapReduce-Inchworm permits management of massively distributed queries including for genome analysis and is useful for processing high throughput sequencing datasets more efficiently. It can cluster k-mers into multiple groups, each of which should contain k-mers from same gene. Its main functions are: map, collate, or reduce.
TRR / Transductive Ridge Regression
TRR was developed for structure-activity modelling. This tool is a correction of the Ridge Regression (RR) model to optimize the transduction parameter g. TRR is available upon request on the web site of the Laboratory.
Allows users to study poorly-studied network regions, without sacrificing its ability to faithfully evaluate well-studied communities. CommWalker is a module evaluation framework that takes this heterogeneity of annotation into account. This tool accepts modules having the potential to uncover functional structure in network regions where such advances are most needed.
MAE-FMD / Multi-Agent Evolutionary method for Functional Module Detection
Detects functional modules in protein-protein interaction (PPI) networks. MAE-FMD employs a group of agents as a population to carry out random walks from a start protein to other proteins in a PPI network and finish their individual solution encodings. It randomly places these agents into an evolutionary environment modeled as a lattice, and performs innovative agent-based operations such as competition, cooperation, and mutation.
Contains algorithms to perform iterative hierarchical cluster analyses: UVCluster, RCluster and SCluster. Jerarca provides alternative ways to obtain the matrices of secondary distances from a graph. It also includes different mathematical criteria to determine the best partition of the dendrogram into clusters, including “modularity” allowing to measure community structure in networks. It generates a lot of outputs useful to edit and visualize the results.
Accelerates the research process. SurpriseMe is composed of several algorithms and calculates distances among the solutions provided by the algorithms. It supplies users distance matrices (with variation of information (VI), Normalized Mutual Information (NMI) values) for helping to compare the solutions of the algorithms. It is useful for characterizing the community structure of complex networks.
ABC algorithm / Artificial Bee Colony algorithm
Determines cluster number and eliminates the noise spots. ABC algorithm is a flow clustering method that can select cluster centers. It operates according to a well-defined process: first, it generates the initial population which stands for feasible solutions; and then, each employed bee exploits a food source in the vicinity of its currently associated food source and evaluates nectar amounts.
Allows users to observe base and amino acid usage in a genome. Gene Spaghetti is a standalone software that utilizes a sliding Gaussian window to evaluate local base usage. It supports multiple statistics such as molecular weight, base skew statistics or codon usage principal components. It was developed to allows researchers to visualize the unusual amino acid and base usage of Mycobacteria marinum.
Determines infection with Plasmodium in red blood cells from a set of images. Plasmodium Autocount is an image-analysis software, based on a circular Hough transform, which focuses on stained spots for identifying potentially infected cells and discards them. It had been tested for allowing the determination of parasitaemia from infected mouse blood.
Cell Counting Aid
Assists in registering cell counting. Counting Aid is a standalone software which allows users to manually records cells’ locations and to display cell between infected or not infected. The application authorizes users to export the counting results as an Excel file for further analysis. It aims to provide a way for proceeding an accurate manual counting when users can’t use an automated program.
Allows users to compare large-scale protein sequences. Afree is a standalone software which aims to furnish a quick alternative to BLASTp by performing all-against-all sequence comparison as a single task and outputs all sequence pairs that share a similarity threshold defined by the user. It can provide input files for other tools for run other analysis such as gene matching or orthologs identification.
Allows users to perform Empirical Bayesian linear modelling. Fitnoise authorizes to experiment measurements related with genes or genomic features by deducing differential expression testing. The software is available both as a standalone application and as a part as the nesoni software and provides four regular and two experimental noise models. The package is able to analyze PAT-Seq data to determine the differential poly(A) tail length.
Allows users to assemble bacteria’ antigenic variant sequences. Assemblet is a python short read assembler that can analyze sequencing reads of DNA that results from polymerase chain reaction (PCR) amplification.
Performs a pipeline for Illumina or SOLiD sequencing reads with poly(A) tails analysis. Tail Tools includes multiple tools that permit to generating an HTML report of the analysis, a way for results visualization as an interactive heatmap, the various peaks called from the analyzed reads, per-sample files and reads counts coupled to tail length statistics.
Offers an application for detecting unimodal, bimodal, and multimodal characteristics. Anchor is a python package which can analyze normalized binary data.
Allows users to investigate single-cell RNA-seq data for detecting copy number alterations and loss of heterozygosity events. badger is a R package which provides a set of statistical methods based on a hierarchical Bayesian approach.
BGP / branching Gaussian process
Provides a method for identifying the branching times of individual genes. BGP is an open source software using a sparse variational inference and permits a defined parameter estimation via the maximisation of a bound on the marginal likelihood. The application aims to be accurate in global state estimation of errors and high noise. Its uncertainty can also be used in downstream analysis of the individual gene branching times.
Allows users to analyze single cell sequencing. Citrus is a toolkit that provides two different methods. First scPLS, a statistical method considering both control and target genes, which permits users to discard unwanted variation and is able to use the data to improve inference of confounding factors by using the partial least squares regression. In addition, the toolkit also furnishes a clustering method that potentially reflects confounding factors.
Harnesses genetic variation to determine the genetic identity of each droplet containing a single cell. Demuxlet can detect droplets containing two cells from different individuals (doublets). It implements a statistical model for evaluating the likelihood of observing RNA-seq reads overlapping a set of single nucleotide polymorphisms (SNPs) from each cell- containing droplet.
Offers a mapping strategy based on spatially distributed scores. DistMap is an algorithm which uses measured gene expression and allows researchers to map single cell RNA sequencing data without requiring transcript-level imputation. The software also includes functions that can be utilized to visualize the expression pattern corresponding to a gene’s gradient calculation.
Allows users to transform raw data from dropSeq/scrbSeq experiment to the final count matrix with QC plots. dropSeqPipe is an open source application that can perform five different tasks: (i) generate fastqc reports of the input data, (ii) obtain the final file for the aligned sorted data, (iii) produce plots based on pre-processing and alignement, (iv) create species plot, and (v) extract the expression data.
Provides a method based on a modeling of Waddington’s epigenetic landscape for retrieving pseudotimes from single-cell data. HopLand is a standalone software that does not depend on prior knowledge of key marker genes and permits users to simulate real biological processes. It can also be applied to determine key regulators and interactions, and, to a broader understanding of various cellular processes such as embryonic development or cancer cell proliferation.
Allows users to deduce undirected networks. NetworkInference is a standalone software which implements four algorithms for providing a fully connected, weighted network with indication about edge’s confidence. It includes various functionalities such as options for discretize or estimate the probability distribution. Moreover, the generated network is coupled to a list which attributes an edge for each pair of genes.
PBA / Population Balance Analysis
Provides a method for population balance analysis. PBA is a python application that allows computation of possible dynamical trajectories and their associated properties. It authorizes to calculate a k-nearest neighbor (knn) graph from an expression matrix, pseudo-inverse Laplacian, potential, fate probabilities and mean first passage times in a both a single process or as separated scripts.
PIVOT / Platform for Interactive analysis and Visualization Of Transcriptomics data
Allows users to analyze and visualize RNA-Seq data. PIVOT furnishes four mains functionalities (i) a graphical interface that is able to wrap existing open source packages in a single user-interface (ii) multiple tools to manipulate datasets to perform derivation or normalization (iii) a way for allowing the compatibility between inputs and outputs from different analysis modules and, (iv) functions for automatically generate reports, publication-quality figures, and reproducible computations.
GASH / Genetic algorithm ASH
Computes globally optimal alignment. GASH can estimate the true maximum of the Number of Equivalent Residues (NER) score for an arbitrary pair of protein structures. It is based on a double dynamic programming (DDP) method improved. This tool integrates a distance cut-off to define the structural environment. It may produce misalignment when it employs side-chain atoms in addition to Cα atoms to define the equivalence.
DFAST / DDBJ Fast Annotation and Submission Tool
Permits pseudogene annotation and orthologous assignments between reference genomes. DFAST follows two main steps: structural annotation for predicting biological features such as coding data sequences (CDSs), RNAs, and clustered regularly interspaced short palindromic repeats (CRISPRs); and functional annotation for inferring protein functions of predicted CDSs. It can be customized by users in the standalone version.
The NCBI Eukaryotic Genome Annotation Pipeline
Annotates eukaryotic genome content for NCBI resources. The NCBI Eukaryotic Genome Annotation Pipeline is based on alignment programs and on a hidden Markov model (HMM)-based gene prediction program. It aligns transcripts, proteins and RNA-Seq reads to the genome. This tool periodically re-annotates organisms when new proofs or assemblies are realised. It returns annotation that are labeled with an Annotation Release number.
Scans viral metagenomes from hundreds of next generation sequencing (NGS) samples. ViraPipe employs data parallel computation strategy. It is able to processes genomic data in partitions at many levels. This tool can avoid false mappings which occurs when the sample reads are merged before the alignment. It is based on existing tools such as BWA aligner, MegaHit de novo assembler, BLAST or HMMER3.
Eases the bridge between artificial intelligence (AI) and ImageJ, a scientific image analysis platform. FunImageJ aims to be employed to construct independently distributable programs, as well as ImageJ scripts that can be used within the Fiji distribution of ImageJ. This tool integrates a number of core features of other pre-existing software in order to provide a powerful platform for image processing.
PQHE / Pooled QTL Heritability Estimator
Permits pooled quantitative trait loci (QTL) heritability (QH) estimation under different experimental designs. PQHE can reflect the structure of the population. It was tested by analyzing four reported QTLs mapped by bulked segregant analysis (BSA)-seq in rice and yeast. This tool needs large populations and large pools to reduce random sampling errors in QTL allele frequencies.
Consists in tumor mutation management and machine learning analysis framework. Orchid allows users to manage, annotate, and analyze tumor mutations by integrating mutation data with popular databases. It accepts a wide assortment of feature types. This tool can annotate mutations from any region of the genome, allowing for the analysis of non-coding mutations. It offers convenience functions to assist the visualization and analysis models.
TOPPE / The End Of Pulse Programming
Interprets files for GE scanners. TOPPE allows rapid implementation and testing of new pulse sequences in a research setting, particularly for non-oblique 3D imaging. It facilitates looping through several image acquisitions with, for example, different flip angles and/or time repetition (TR), as is done in magnetic resonance (MR) fingerprinting. This tool permits rapid prototyping of MR pulse sequences.
reCAT / recover Cycle Along Time
Reconstructs cell cycle time-series using single-cell transcriptome data. reCAT is a computational method consists of four steps: (i) the data processing, including quality control, normalization, and clustering of single cells, (ii) the order of the clusters is then recovered by finding a traveling salesman cycle, (iii) two scoring methods, Bayes-scores and mean-scores subsequently discriminate among cycle stages and (iv) a hidden Markov model (HMM) and a Kalman smoother finally estimate the underlying gene expression levels of the single-cell time-series.
Provides a computational method for single cell data analysis. SoptSC can be employed to discover the number of clusters, cell subpopulations and marker genes for each cell subpopulation from data submitted by the researchers. It does not need initial cell neither initial cluster to deduce pseudotime and lineage. This tool can be used for the inference of signaling network given a group of Ligand-Receptor pairs and their downstream target genes.
TRAPeS / TCR Reconstruction Algorithm for Paired-End Single-cell
Reconstructs T cell receptors (TCRs) from paired-end sequencing libraries of single cells, even at short (25 bp) read length. TRAPeS is a software that works on the original reads - leading to increased sensitivity. The TRAPeS algorithm has four main steps: (i) identifying putative pairs of variable (V) and joining (J) segments, (ii) collecting putative CDR3-originating reads, (iii) reconstructing the CDR3 and (iv) separating similar TCRs and determining chain productivity.
Assists users in the estimation of velocity and the related data analysis. Velocyto is an analysis framework developed for the analysis of expression dynamics single cell RNA seq data. This analysis logic is implemented separately in R and python environments. This method consists of two main components: (i) a command line interface (CLI) used to run the pipeline that generates spliced/unspliced expression matrices and (ii) a library that includes functions to estimate RNA velocity from the data matrices.
Allows searchers to follow, filter and save papers from all journals relevant to user’s research. Researcher is a mobile app that permits to (i) find and read academic journals by selecting from hundreds of academic journals, (ii) filter by specific keywords to easily find papers, avoiding the need to set up alerts, complex RSS readers and navigate manually through multiple journal websites and (iii) bookmark articles and journals and read later on mobile or desktop.
Guides and summarizes the hierarchical exploration of large single-cell data. CyteGuide is an integrated visualization for that extends Hierarchical Stochastic Neighborhood Embedding (HSNE) by providing effective navigation and visualization of the exploration hierarchy. It can be applied to the analysis of other high-dimensional data as well as other hierarchical techniques. An interactive demonstration is available on the site.
CCC / Carrier Cycling Casca
Provides a simple motif designated as a which simultaneously considers the dynamics of substrates and coenzymes. The carrier cycling cascade (CCC) is a minimal model of metabolic systems that includes recycling of the moiety-conserved carriers with complex formation between carriers and other metabolites. It consists only of active carrier-consuming and producing steps.
Provides current experimental knowledge of the proximal hepatic insulin signaling network. This model provides a sequential method of postprandial hepatic control of glucose and lipid by insulin, according to which delayed aPKC switch-off contributes to selective hepatic insulin resistance. This model is quantitatively informed by two in vivo data sets from rodent studies, where hepatic insulin signaling was measured after refeeding or after various patterns (pulsatile/constant/T2D) of pre-hepatic insulin infusion.
RAGTOP / RNA-As-Graph-TOPologies
Predicts global 3D topologies compatible with a given RNA 2D structure. RAGTOP is a hierarchical sampling approach: (i) a 2D tree topology is annotated, (ii) an initial planar graph is constructed by junction prediction, (iii) graphs are sampled by Monte Carlo, (iv) candidate graphs are assessed and compared with reference graphs, and (v) all atom models are constructed by graph partitioning, fragment search, and assembly of corresponding all atom.
MICtools / Maximal Information Coefficient tools
Identifies relevant associations amongst a large number of variables. MICtools is an open-source software that provides (i) an efficient implementation of Total Information Coefficient (TICe) and Maximal Information Coefficient (MIC) estimators, (ii) a permutation-based strategy for estimating TICe empirical p values, (iii) several methods for multiple testing correction, (iv) the MICe estimates for each association called signicant.
SAFE-clustering / Single-cell Aggregated (From Ensemble) Clustering
Provides stable and robust clustering for scRNA-seq data. SAFE-clustering is an unsupervised ensemble method that: (i) performs independent clustering using four state-of-the-art methods, SC3, CIDR, Seurat and t-SNE + k-means; and (ii) combines the four individual solutions into one consolidated solution using one of three hypergraph partitioning algorithms: hypergraph partitioning algorithm (HGPA), meta-clustering algorithm (MCLA) and cluster-based similarity partitioning algorithm (CSPA).
Screens and designs gene circuits capable of performing arbitrary functions. GeneNet is a python method that can be readily applied to biological networks of any type and size. This application can also design circuits to perform more complex computations and functions. It provides two key functions that can execute: (i) train the network to perform some desired function and (ii) simulate the network and examine its behaviour.
Determines the extent to which engineered cell populations have established Gene Regulatory Networks (GRNs) that govern C/T identity. CellNet is a computational platform that provides a platform for assessing and improving efforts at cellular engineering. It was used to improve the conversion of B cells to macrophages and to reveal the unanticipated intestinal potential of induced hepatocyte-like cells.
Facilitates collaboration and enables reproducible science by providing a robust, secure and scalable platform to the community at large. FireCloud is a NCI Cloud Pilot that provides a cancer genome analysis platform on a cloud computing environment that hosts all of TCGA data and is loaded with state-of-the-art tools and workflows. This resource is designed to support collaborative science with specific controls on who can access different resources.
EMU / Elementary metabolite units
Identifies minimum amount of information needed to simulate isotopic labeling within a reaction network. EMU is a bottom-up modeling approach based on a highly efficient decomposition algorithm. The functional units generated by the decomposition algorithm form the new basis for generating system equations that describe the relationship between fluxes and isotopomer abundances. This approach is valid for any stable-isotope measurement and any labeling input.
Enriches metabolomic data sets with known databases identifiers. MetaboliteIDConverter is a Shell module that allows users to convert Metabolite Identifiers to and from database identifiers. This open source software uses the Chemical Translation Service (CTS) to convert metabolite identifiers. Any of the following database can be used as input database: InChIKey, KEGG ID, ChEBI, or Chemical Name.
Provides a software capable of 13C assisted fluxomics. Iso2Flux is an application capable of integrating a wide array of experimental data (metabolites secretions and uptakes, gene expression and metabolomics) to identify the steady state metabolic flux distribution. This framework has been designed as a flexible tool that can be operated both through the command line and a graphical user interface.
Offers a method for evaluate time-varying instantaneous reproduction numbers from incidence time series. EpiEstim is a R package that relies on knowledge of the serial interval distribution but is able to directly incorporate uncertainty in serial interval distribution estimates. It can also detect changes in the reproduction number. Additionally, the package implements the Wallinga and Teunis method to facilitate comparison.
Provides flexible model fitting for epidemiological data analysis models. Epifit intends to fit variety models such as Cox regression or linear models as well as some models which expressed likelihood across negative binomial, gamma and Weibull distributions. The software also contains some functionalities of data handling including the possibility to create a person-years table from event, time and covariate data.
Compiles a combination of epidemic/network-related tools. Epinet is a R package that can generate contact networks to simulate the transmission of diseases. It includes features to perform bayesian inference on network and epidemic parameters. Moreover, the package allows users to convert the obtained transmission tree in Newick format or to generate posterior samples of an object.
Allows users to analyze statistical network. Statnet is a software which is available both as a R package and as a web application. It supplies a framework for exponential-family random graph models (ERGM)-based network modeling: tools for model estimation, evaluation and model-based network simulation. The software can be run for evaluating if a model can be considered as degenerated.
Allows users to fit, simulate from, plot and evaluate exponential family random graph models (ERGMs). ergm is a R package which aims to describe the local selection forces that shape the global structure of a network. It includes several functionalities for allowing users to simulate random networks using an ERGM; evaluate the goodness of fit of an ERGM to the data, obtain approximate maximum likelihood estimates (MLEs) and perform graphical goodness-of-fit checks.
Provides an assortment of statistical methods. Surveillance is a R package which authorizes to model and monitor time series of counts and continuous-time point processes of epidemic phenomena, and offers a multitude of methods for visualization, likelihood inference and simulation of endemic-epidemic models. The package also includes features to perform the regression-oriented modeling of spatiotemporal epidemic data.
Provides a set of methods for analyzing and simulating network evolution thanks to exponential-family random graph models (ERGM). tergm is a R package that extends the statnet toolkit.
IsoDyn / Isotopomer Dynamics
Allows users to simulate an environment for the dynamics of metabolite labeling by 13C isotopes in metabolic reactions of living cells. IsoDyn is a standalone software which utilizes a classical kinetic model of metabolic pathways related to a module for calculating the distribution of 13C isotopic isomers of metabolites. It was tested for determining the features of cancer cell metabolism.
Allows users to analyze metabolomics data from untargeted liquid chromatography tandem mass spectra (LC-MS/MS) measurements. MetFamily is an open source application that identifies metabolite families for helping in interpretation of complex metabolomics data and supports semi-targeted analyses. The software authorizes to export several features such as selected sets of precursor ions or publication-ready high-quality images.
Offers a method for identifying untargeted metabolites thanks to genetic spiking. Metabomatching is a standalone software developed in Matlab which permits users to annotate nuclear magnetic resonance (NMR) files as well as perform statistical analysis. The model can also be run by using the Docker platform and a simplified version is implemented into the PhenoMeNal software.
Offers a way for Proton Nuclear Magnetic Resonance (1H-NMR) data pre-treatment. PepsNMR is a R package that supplies multiple features such as authorizing to read the free induction decay (FID) signals in Bruker format.
Furnishes a program to handle CDF files. RaMID is a R package that allows users to preprocess raw data and evaluate the mass spectra of 13C-labeled metabolites. The software first separates the time courses for selected m/z peaks and corrects their baseline, then, it picks the less contaminated distribution of peaks in the time points and evaluate the selected distribution and finally provides an exportable file that can be read by the MIDcor software.
Statistical Power Analysis tool
Provides a method for analyze metabolic phenotyping data sets. Statistical Power Analysis tool is a standalone software available in both Python and Matlab language. The application first models the distribution of pilot study data, and then introduces an artificial effect for finally deriving estimates and confidence intervals for performance metrics. The method is suited for large population studies performed with standardized protocols.
Allows users to proceed file conversions from 1D nuclear magnetic resonance spectroscopy (NMR) raw formats to nmrML. nmrMLconvert is a software available both as a web application and as a standalone program and includes a comprehensive JAVA-based converter. It accepts Bruker (TOPSPIN, X-WINNMR), Variant/Agilent (VNMRJ) and Jeol (JDF, DELTA) format to be performed from a compiled archive.
Allows users to handle multidimensional nuclear magnetic resonance (NMR) data. Nmrglue is a module whose main functions are reading, writing, and interacting with spectral data from multiple commons formats: Bruker, Nmrpipe, Sparky ,Varian/Agilent, Simpson, Rowland. Moreover, the software also includes several common functions for processing the submitted data such as apodization, spectral shifting, or baseline smoothing and flattening. Besides, additional data formats can be implemented.
Estimates cell composition while avoiding platforms biases. methylCC is a R package that proposes a latent variable model with region-specific and platform-dependent random effects. It permits to evaluate the composition from a DNA methylation whole blood sample on both microarray and sequencing platform technology. It was tested on real and simulated whole blood samples measured on a sequencing platform.
Allows users to perform haplotype phasing and local ancestry inference (LAI). Loter is a python package that supplies a parameter-free and rapid software without specifications of statistical or biological parameters to allow LAI processing for a wide range of species. The software is not based on a probabilistic formulation and aims to will make more accessible genomic studies about admixture processes.
MASC / Multiple sequence Alignment based on a Suffix tree and Center-star strategy
Allows users to perform multiple sequences alignments (MSA) among highly similar sequences. MASC is a standalone software which can be applied for MSA in linear time and for very high-throughput cases. The method is implemented on Spark-distributed parallel framework for massive scale sequence data with the aim of accelerating the process. However, it has been noticed that the software decreases in efficiency when it must manage complex variations.
GSMC / Combining Parallel Gibbs Sampling with Maximal Cliques for hunting DNA Motif
Provides an accurate method for DNA motif discovery, especially for detecting cofactor motifs in better large-scale ChIP-Seq data. GSMC uses Gibbs sampling to generate initial motifs and then employs maximal cliques to cluster them under Similarity with Position Information Contents (SPIC) and finally regards the first motif for each cluster as an output motif.
CLIMP / Clustering Motifs via Maximal Cliques with Parallel Computing Design
Allows clustering of large-scale motif. CLIMP is able to gather the motifs that belong to the same groups and to dissociate the motifs belonging to several groups. It contains a novel metric for measuring the similarity between two motifs. It also permits to merge motifs of the same transcription factor (TF) family. It can tolerate mass data to produce more accurate results in a short time.
SPIC / Similarity with Position Information Contents
Serves for column-to-column motif comparison. SPIC is a similarity metric based on column information contents. It calculates a score between the position-specific scoring matrix (PSSM) multiplied by the information content (IC) of one column and the position frequency matrix (PFM) of the other column, and vice versa. It is especially useful for recovering motifs in a database, grouping relevant motifs, merging sub-motifs or redundant motifs, or digging true motifs out of chaos.
Serves for designing aptamer-sticky bridge-cargo complexes. AptaBlocks is capable of designing universal sticky bridges for either many cargoes with similar sequences or a smaller number of cargoes with distinct sequences. It can realize sticky bridges for an aptamer-siRNA conjugate considering two alternative ways of forming RNA complexes. It allows users to accelerate the development of flexible and effective drug delivery systems.
PAIRUP-MS / Pathway Analysis and Imputation to Relate Unknowns in Profiles from MS-based metabolite data
Allows users to analyze unknown signals. PAIRUP-MS is a program useful for processing, matching, and annotating metabolite signals in MS-based profiling datasets. This tool performs meta and pathway analyses for unknown signals. It can be applied to diverse untargeted profiling datasets and is helpful to advance metabolomics as a powerful approach for elucidating biology underlying human traits and diseases.
AVA,Dx / Analysis of Variation for Association with Disease
Utilizes whole exome sequencing data to detect Crohn’s disease (CD) status. AVA,Dx is a disease-prediction model that assists users in research of undiscovered diseases. With this tool, researchers are able to foresee CD status for previously invisible individuals from another study on CD. It allows users to highlight pathogenesis pathways and can advance clinical diagnostic time and accuracy.
Consists in a biophysical dynamic module. Biophysical-dynamic-module-for-PIN-polarisation is a model prediction build upon the up-to-date experimental results on the influencing factors and cellular processes and their non-linear interactions. The modelling and simulations of this module assists postulate that relative influence of the mechanical tension of the plasma membrane can surpass that of the GTPases Rho of Plant (ROP).
Investigates somatic enhancer mutations enriched biological networks in cancer. Ennet allows users to discover potential cancer-driving networks through integrating enhancer-gene interactions with functional molecular networks. It provides a new perspective to find new mechanisms for tumor development from somatic mutations in enhancers (SMEs).
Allows creation of genome multiple sequence comparisons. Panaconda is an algorithmic approach for discovering collision points within a group of genomes. It creates a de Bruijn graph and uses it’s traversal to create the pan-synteny (PS)-graph from sequence conservation in any orientation, whereas Partial Order Alignment (POA) requires that blocks of alignment occur in the same orientation.
PRSoS / PRS-on-Spark
Allows users to measure polygenic risk scores (PRS). PRSoS provides enhanced data output options and can be applied to observed genotypes, hard calls, and imputed posterior probabilities. It also supplies a reliable option to retain much of the strand-ambiguous single nucleotide polymorphisms (SNPs). It makes use of parallel computing to accelerate PRS calculation. This tool is useful for better understanding the polygenic basis of complex traits.