Sign In or Sign Up

Unlock your biological data

?

Try: RNA sequencing CRISPR Genomic databases DESeq

Software Databases

Bioinformatics workflow tools | RNA sequencing data analysis

1 - 50 of 82 results

Filters

Technology

Illumina 9 Life Technologies 5 Pacific Biosciences 2 Roche 2

Disease

Neuronal diseases 3 Cancer diseases 2 Cardiovascular diseases 2 Gastrointestinal diseases 2 Blood diseases 1 Immune diseases 1 Muscle diseases 1 Nephrological diseases 1 Skin diseases 1 Eye diseases 1

Operating System

Unix/Linux 68 Mac OS 34 Windows 25

Interface

Command line interface 59 Graphical user interface 17 Web user interface 15

Computer Skill

Basic 15 Medium 10 Advanced 59

License

GNU General Public License version 3.0 12 MIT License 11 GNU General Public License version 2.0 9 Commercial 6 Artistic License version 2.0 3 GNU Lesser General Public License version 3.0 2 Apache License version 2.0 2 GNU Affero General Public License version 3 1 BSD 3-clause “New” or “Revised” License 1

Get relevant results

Subscribe for free to unlock filters and target the right tools

Sign Up

1 - 50 of 82 results

Offers a way to manage pipelines. Toil supports arbitrary worker and leader failure, with strong check-pointing that allows resumption. It can be employed to run scientific workflows on a large scale in cloud or high-performance computing (HPC) environments. This tool was used to compute gene- and isoform- level expression values for 19 952 samples from four studies.

An easy-to-use application for microarray, RNA-Seq and metabolomics analysis. For splicing sensitive platforms (RNA-Seq or Affymetrix Exon, Gene and Junction arrays), AltAnalyze will assess alternative exon (known and novel) expression along protein isoforms, domain composition and microRNA targeting. In addition to splicing-sensitive platforms, AltAnalyze provides comprehensive methods for the analysis of other data (RMA summarization, batch-effect removal, QC, statistics, annotation, clustering, network creation, lineage characterization, alternative exon visualization, gene-set enrichment and more).

Provides a workflow for RNA-Seq-based differential gene expression (DGE) analysis. RobiNA gathers multiple packages and software with the aim of furnishing a cross-platform processing in four main steps: (i) quality assessment and filtering; (ii) mapping the reads to a user-provided reference genome or transcriptome; (iii) perform the experimental design and (iv) statistical analysis of DGE.

Establishes a central, redistributable workbench for scientists and programmers working with RNA-related data. The RNA workbench builds a sustainable community around it. This platform is unique in combining available tools, workflows and training material, as well as providing easy access for experimentalists. It serves as a central hub for programmers, which can easily integrate and deploy their existing or novel tools and workflows.

Octopus-toolkit

Examines epigenomic and transcriptomic next generation sequencing (NGS) data. Octopus-toolkit can be used for antibody- or enzyme-mediated experiments and studies for the quantification of gene expression. It can accelerate the data mining of public epigenomic and transcriptomic NGS data for basic biomedical research. This tool provides a private and a public mode: one to process the user’s own data, and the other to analyze public NGS data by retrieving raw files from the GEO database.

Advances the automation and visualization of RNA-seq data analyses results. QuickRNASeq is a pipeline that significantly reduces data analysts’ hands-on time, which results in a substantial decrease in the time and effort needed for the primary analyses of RNA-seq data before proceeding to further downstream analysis and interpretation. It provides a dynamic data sharing and interactive visualization environment for end users and enable non-expert end users to interact easily with the RNA-seq data analyses results.

Processes 3’ mRNA sequencing data. expressRNA classifies the sites where cleavage and polyadenylation take place. It is able to identify the differentially regulated poly(A) sites. This tool provides a flexible data integrative research platform. It facilitates highly reproducibility for computational analysis and allows users to visualize and share data and results in a user-friendly way.

An R package that simplifies the processing of RNA sequencing data, hiding the complex interplay of the required packages behind a single functionality. easyRNASeq calculates the coverage of high-throughput short-reads against a genome of reference and summarizes it per feature of interest (e.g. exon, gene, transcript). The data can be normalized as 'RPKM' or by the 'DESeq' or 'edgeR' package.

Assists in analyzing RNA-Seq data. RSEQtools contains a set of modules to perform a large variety of tasks including: (i) the quantification of expression values, (ii) the manipulation of gene annotation sets, (iii) the visualization of the mapped reads, (iv) the generation of signal tracks, (v) the identification of transcriptional active regions and several auxiliary utilities.

Provides an integrated analysis of high-throughput sequencing data in R, covering all steps from read preprocessing, alignment and quality control to quantification. QuasR supports different experiment types (including RNA-seq, ChIP-seq and Bis-seq) and analysis variants (e.g. paired-end, stranded, spliced and allele-specific), and is integrated in Bioconductor so that its output can be directly processed for statistical analysis and visualization.

NGS-Trex / NGS TRanscriptome profile EXplorer

Allows user to upload raw sequences and obtain an accurate characterization of the transcriptome profile. NGS-Trex can assess differential expression at both gene and transcript level. It compares the expression profile of different samples. All comparisons are performed using a custom database which is mainly populated with several sources obtained from the NCBI. The tool allows user to discard ambiguously assigned reads or to assign those reads to all competing genes in the case of ambiguities.

Allows users simultaneously perform mRNA and miRNA expression analysis. wapRNA is a web application that includes major processes for the next-generation mRNA or miRNA data analysis, including preprocessing raw sequenced reads, mapping tags to reference sequences, gene expression annotation, and other downstream functional analysis such as detecting differentially expressed genes, Gene Ontology and KEGG pathway analysis for RNA, novel miRNA predication and miRNA target prediction. Executable packages are available for users to build their pipeline locally.

Facilitates analysis of microarrays and miRNA/RNA-seq data on laptops. oneChannelGUI can be used for quality control, normalization, filtering, statistical validation and data mining for single channel microarrays. It consists of a didactical tool that can be employed to introduce scientists to the utilization and interpretation of microarray data. This tool serves in the investigation of microarray experiments based on the consolidated 3’ Affymetrix expression arrays.

Oqtans / Online quantitative transcriptome analysis

Provides a Galaxy interface to RNA-seq analysis tools. Oqtans is the online platform for quantitative RNA-seq data analysis. Its integration into the Galaxy framework ensures transparent and reproducible computational analyses. This application is available in five incarnations: (i) as a cloud machine image, (ii) as a public Galaxy instance, (iii) as a git repository, (iv) the Galaxy Toolshed, and (v) a preconfigured share string to launch Galaxy CloudMan using sharing instance functionality.

Processes large numbers of raw RNA-sequencing datasets. PRADA works on paired-end sequencing data and is based on: (1) its mapping to both transcriptomic and genome; or (2) its comprehensive repertoire of output information from the incorporated modules. It enables users to compute multiple analytical metrics. It provides different types of information from raw paired-end RNA-seq data: gene expression levels, quality metrics, detection of unsupervised and supervised fusion transcripts, detection of intragenic fusion variants, homology scores and fusion frame classification.

Analyses mapped reads from diverse High-throughput sequencing (HTS) experiments: ChIP-Seq, either punctuated or broad signals, CLIP-Seq and RNA-Seq. Pyicos is a command line utility for the conversion and manipulation of genomic coordinates files. It facilitates HTS analysis through its flexibility and memory efficiency, providing a useful framework for data integration into models of regulatory genomics. Pyicos is part of the Pyicoteo suite of tools.

Permits the computational evaluation of RNA-Seq data. READemption is an automated RNA-Seq processing with the initial purpose to handle differential RNA-Seq (dRNA-Seq) data for the determination of transcriptional start sites (TSSs) from bacterial, archaeal and eukaryotic species as well as for RNA virus genomes. READemption generates several output files that can be examined with common office suites, graphic programs and genome browser.

Grape / Grape RNA-Seq Analysis Pipeline Environment

Allows analysis of millions of short reads obtained from high-throughput RNA-Seq experiments. Grape is a workflow that automates the steps from RNA-Seq reads to transcript quantification and discovery. Its objective is to produce quantifications of transcript abundances and of the abundances of other transcriptional elements such as genes, exons, or splice junctions. It can be directly used to produce quantifications if an index from a reference transcriptome-independently assembled is generated.

Allows users to characterize and quantify the set of all RNA molecules produced in cells. RseqFlow contains several modules that include: mapping reads to genome and transcriptome references, performing quality control (QC) of sequencing data, generating files for visualizing signal tracks based on the mapping results, calculating gene expression levels, identifying differentially expressed genes, calling coding single nucleotide polymorphisms (SNPs) and producing MRF and BAM files.

aRNApipe / automated RNA-seq pipeline

Analyzes single-end and stranded or unstranded paired-end RNA-seq data. aRNApipe focuses on high performance computing (HPC) environments and the independent designation of computational resources at each stage allowing optimization of HPC resources. It is highly flexible because its project configuration and management options. This tool can be adapted to changes in the current applications and the addition of new functionalities. It allows users to complete primary RNA-seq analysis.

Allows to develop tailored workflows for the analysis of whole-exome (WES), whole-genome (WGS), and transcriptome (RNA-seq) sequencing data. NGS-pipe is an automated framework for the design of pipelines for the analysis of large-scale sequencing data, such as cancer genomics data. It provides building blocks to execute state-of-the-art tools, as well as appropriate error handling. It also overcome the common lack of automated procedures to ensure reproducibility.

Performs RNA-seq data analysis through the Elastic Compute Cloud (EC2) service. NGSCloud is a platform allowing users to: (i) generate, view composition, and manipulate clusters and its associated nodes; (ii) manage volumes; (iii) handle datasets with various utilities for compressing or uploading; (iv) manage jobs and check for program operability in an RNA-seq workflow. This program focuses on non-model species with no reference genomes available.

Permits to process and analyze the raw files generated with the Spatial Transcriptomics (ST) method. ST Pipeline enables demultiplexing of spatially-resolved RNA-seq data and robust quality filtering and identification of unique molecules. It is highly customizable with numerous parameter settings. The tool is more robust, efficient and scales better to arrays with higher density. It filters data, aligns it to a genome, annotates it to a reference, demultiplexes by array coordinates and then aggregates by counts that are not duplicates using the Unique Molecular Identifiers.

Processes raw reads to count tables for RNA-seq data using Unique Molecular Identifiers (UMIs). zUMIs is a pipeline applicable for most experimental designs of RNA-seq data, such as single-nuclei sequencing techniques. This method allows for down sampling of reads before summarizing UMIs per feature, which is recommended for cases of highly different read numbers per sample. zUMIs is flexible with respect to the length and sequences of the barcodes (BCs) and UMIs, making it compatible with a large number of protocols.

Converts the raw fastq files into gene/isoform expression matrix and differentially expressed genes or isoforms. hppRNA is a one-in-all solution composed of four scenarios such as pre-mapping, core-workflow, post-mapping and sequence variation detection. It also turns the identification of fusion genes, single nucleotide polymorphisms (SNP), long noncoding RNAs and circular RNAs. Finally, this pipeline is specifically designed for performing the systematic analysis on a huge set of samples in one go, ideally for the researchers who intend to deploy the pipeline on their local servers.

Designed for mRNA, miRNA and circRNA identification and differential expression analysis, applicable to any sequenced organism. miARma-Seq is presented as a stand-alone tool that provides different well-established softwares at ease of installation process. It can analyse a large number of samples due to its multithread design. During the whole analysis miARma-Seq performs several quality control analysis creating quality reports for an easy evaluation of the data.

Analyzes the structure and functions of active microbial communities using the power of multi-threading computers. MetaTrans is designed to perform two types of RNA-Seq analyses: taxonomic and gene expression. It performs quality-control assessment, rRNA removal, maps reads against functional databases and also handles differential gene expression analysis. Its efficacy was validated by analyzing data from synthetic mock communities, data from a previous study and data generated from twelve human fecal samples.

Consists of a collection of investigation approaches and displays software for microarray data. Chipster is useful for several types of high throughput data such as microarrays, proteomics and next generation sequencing (NGS). It can be employed to normalize most of the commonly used chip types and permits to utilize the remapped information. This tool is useful for RNA degradation, relative log expression (RLE), normalized unscaled standard error (NUSE) or quality control probe expression.

CANEapp / Comprehensive automated Analysis of Next-generation sequencing Experiments

Integrates data from different sources and experiments. CANEapp is a platform for integrating next-generation sequencing (NGS) analysis pipelines and tools into a user-friendly suite that can be immediately accessed by scientists. It utilizes a standardized analysis pipeline and internally generated experimental design templates. It allows users to work on NGS data and high-throughput data.

RAP / RNA-seq Analysis Pipeline

Allows users to analyze sequencing data in multiple steps. The RAP purpose is to investigate the complex transcriptional landscape of eukaryotic transcriptomes through a computationally optimized RNA-Seq data analysis. Users can perform a complete RNA-Seq analysis without any specific technical competence. It offers a web interface and provides different types of results which consist of several tabular and graphical representations.

A workflow system for laboratories with the need to analyze data from multiple NGS projects at a time. QuickNGS takes advantage of parallel computing resources, a comprehensive back-end database, and a careful selection of previously published algorithmic approaches to build fully automated data analysis workflows. QuickNGS considerably reduces the barriers that still limit the usability of the powerful NGS technology and finally decreases the time to be spent before proceeding to further downstream analysis and interpretation of the data.

Guide / Genome Informatics Data Explorer

Analyses RNA-seq and microarray data. Guide can perform various analyses including differential expression at both gene and pathway levels. It returns the results in easy-to-use tables and figures. This tool offers features to personalize the application for advanced users and non-standard data. It is able to provide a full report generation feature on the dataset.

Includes three types of workflows for different tasks. RNA-seq portal permits users to perform computing and analysis, including sequence quality control, read-mapping, transcriptome assembly, reconstruction and differential analysis. All these workflows support multiple samples and multiples groups of samples and perform differential analysis between groups in a single workflow job submission. This web portal offers bioinformatics software, workflows, computation and reference data and a platform to study complex RNA-seq data analysis for agricultural animal species.

TRAP / Time-series RNA-seq Analysis Package

Processes pathway and clustering analysis of time series RNA-seq data. TRAP exploits over-representation analysis (ORA) and signaling pathway impact analysis (SPIA) methods to evaluate pathways interactions between genes. Time points, i.e., time series are analyzed by the software to estimate a single pathway-level statistic. It enables multiple thresholds and customized pathways made of genes of interest for analyzing data.

Performs the analysis of sequencing data from cross-linking, ligation and sequencing of hybrids (CLASH) experiments. hyb is able to recognize chimeric reads in other applications as well as for the analysis of UV cross-linking and analysis of cDNAs (CRAC), crosslinking and immunoprecipitation (CLIP), and RNA-Seq data. This tool can be useful and applicable to any next-generation sequencing datasets.

OncoRep / Oncogenomics Report

A fully automated RNA-Seq based report for patients with (breast) cancer, which includes molecular classification, detection of altered genes, detection of altered pathways, identification of gene fusion events, identification of clinical actionable mutations (in coding regions) and identification of treatable target structures. Furthermore, OncoRep reports suitable drugs based on identified actionable targets, which can be considered in the treatment decision making process.

RNA CoMPASS / RNA Comprehensive Multi-Processor Analysis System for Sequencing

Analyzes exogenous and human sequences from RNAseq data. RNA CoMPASS is a parallel computation pipeline that provides a graphic user interface built from several open-source programs such as Novoalign and SAMMate. The application reads both the unmapped reads for pathogen discovery and the mapped reads for host transcriptome analysis. The program supports files generated from single-end, paired-end, and/or directional sequencing strategies.

TCW / Transcriptome Computational Workbench

Serves for methodical analysis for both single and comparative transcriptome data. TCW contains two manager programs: (1) singleTCW for building a database of annotated sequences with differential expression (DE) results for a single species; and (2) multiTCW for building a database of multiple species with comparison results. This approach can be used for the large-scale processing and online databases to extract information.

A multi-level bioinformatics protocol and pipeline. RNAMiner includes five steps: Mapping RNA-Seq reads to a reference genome, calculating gene expression values, identifying differentially expressed genes, predicting gene functions, and constructing gene regulatory networks.

OTP / One Touch Pipeline

Provides a platform for storing, handling and processing next generation sequencing (NGS) data. OTP performs both data management and processing and allows users to automate an entire process to raw data import from storage. The application includes functionalities for check quality control and sequence alignment and identify single-nucleotide and structural genomic events.

Assists users in obtaining genomic features from transcriptomic sequencing data, for any genome. MAP-RSeq is a comprehensive computational workflow, to align, assess and report multiple genomic features from paired-end RNA-Seq data. It uses a variety of freely available bioinformatics tools along with in-house developed methods using Perl, Python, R, and Java. This application is available in two versions: (i) a single threaded that runs on a virtual machine (VM) and (ii) a multi-threaded designed to run on a cluster environment.

An extensible environment for both building and running end-to-end analysis workflows with automated report generation for a wide range of next-generation sequencing (NGS) applications. Its unique features include a uniform workflow interface across different NGS applications, automated report generation, and support for running both R and command-line software on local computers and computer clusters. A flexible sample annotation infrastructure efficiently handles complex sample sets and experimental designs. To simplify the analysis of widely used NGS applications, systemPipeR provides pre-configured workflows and reporting templates for RNA-seq, ChIP-seq, VAR-seq and Ribo-seq.

Extracts raw Illumina reads to differentially expressed genes. SPARTA is a bacterial RNA-seq analysis tool performing transcriptional profiling experiments using RNA-seq. It enables microbiologists to simplify their researches and provides supplies the ability to incorporate a hands-on approach to next-generation sequencing (NGS) technologies in the classroom. Moreover, it outputs quality analysis reports, gene feature counts and differential gene expression tables and scatterplots.

A toolbox for analyses that may be performed with the use of gene annotations or alternatively, in an unsupervised mode, on any genomic region to find novel or non-standard transcripts. The data back-end may be a MySQL database or a set of files in standard BAM format. The processing in R can be run on a machine without any particular hardware requirements, and scales linearly with the number of genomic loci and number of samples analyzed. The main features of rnaSeqMap include coverage operations, discovering irreducible regions of high expression, significance search and splicing analyses with nucleotide granularity.

TRAPLINE / Transparent Reproducible and Automated PipeLINE

Serves for RNAseq data processing, evaluation and prediction. TRAPLINE guides researchers through the NGS data analysis process in a transparent and automated state-of-the-art pipeline. It can detect protein-protein interactions (PPIs), miRNA targets and alternatively splicing variants or promoter enriched sites. This tool includes different modules for several functions: (1) it scans the list of differentially expressed genes; (2) it includes modules for miRNA target prediction; and (3) a module is implemented to identify verified interactions between proteins of significantly upregulated and downregulated mRNAs.

LSTrAP / Large-Scale Transcriptome Analysis Pipeline

Pre-processes RNA-seq data and maps it to the genome. LSTrAP performs quality control and produces co-expression networks. It provides functional and comparative genomics data to enable a host of downstream analyses. This tool offers a single command solution to process a large volume of RNA-Seq samples. It can assist users to identify relevant candidate genes in biological processes of interest and guide future experiments.

Automates the processing and analysis of several commonly used Next Generation Sequencing (NGS) datasets including: ChIP-seq, RNA-seq, Global Run On sequencing (GRO-seq), micrococcal nuclease footprint sequencing (MNase-seq), DNase hypersensitivity sequencing (DNase-seq), and transposase-accessible chromatin using sequencing ATAC-seq datasets. CIPHER provides an analysis mode that accomplishes complex bioinformatics tasks such as enhancer prediction. It supplies functions to integrate various NGS datasets together.

VIPER / Visualization Pipeline for RNA-Seq

Allows users to perform on different subjects: alignment steps, quality control (QC), differential gene expression and pathway analyzes. VIPER utilizes a computational workflow management system named Snakemake to combine many tools currently employed in RNA-seq analysis. Moreover, it includes a variety of optional steps for variant analysis, fusion gene detection, viral DNA detection and evaluation of potential immune cell infiltrates.

SePIA / Sequence Processing Integration and Analysis

Automates RNA-seq processing, integration and analysis. SePIA allows reproducible analysis of total RNA, poly(A)-derived RNA, small RNA, and integrated microRNA (miRNA) and mRNA data. It provides a selection of state-of-the-art RNA-seq tools and methods with minimal effort to run. This tool organizes computational results in reproducible, presentable, and easy-to-use formats for in-depth investigation.

Allows the user to perform many common analyses on ChIP-seq, microarray and RNA-seq data. Glbase is a flexible and multifunctional toolkit which includes many functions to intersect two lists of data, including operations on genomic interval data and support for the efficient random access to huge genomic data files. The software is designed to rapidly bring biological data into a Python-based analytical environment to facilitate analysis and data processing.

1
2

0 - 0 of 0 results

1 - 18 of 18 results

Filters

Job seeker

Yes Disable 5

Position

Bioinformatician 13 Biologist 3 Developer 2

Fields of Interest

RNA-seq analysis 16 Gene expression array analysis 8 ChIP-seq analysis 6 WGS analysis 5 Protein interaction analysis 3 De novo sequencing analysis 3 scRNA-seq analysis 3 Genome edition 2 WES analysis 2 Metagenomic sequencing analysis 2 MS-based untargeted proteomics 1 BS-seq analysis 1 aCGH data analysis 1 DNA methylation array analysis 1

Country

United States of America (the) 5 China 3 India 3 Korea (the Republic of) 3 Spain 2 France 1 Pakistan 1

Programming Language

Python 11 R 11 Perl 7 MATLAB 4 Java 3 PHP 3 Shell (Bash) 3 C++ 3 Javascript 2 C 2

Find experts in bioinformatics

Subscribe for free to unlock filters and identify experts of the field

Sign Up

1 - 18 of 18 results

Group leader in Computational RNA Biology Pompeu Fabra University

Pyicos MIRA SUPPA

Master Korea Advanced Institute of Science and Technology

Cufflinks SAMtools Sickle

PhD Student Institute of Life Sciences

Working on Immunology and Systems Biology.

EuMicrobedbLite GATK Bowtie

Sangram keshari sahu

Computational Biology and Bioinformatics Indian Institute of Science Education and Research Mohali

A bioinformatics graduate. Junior Research Fellow at IISER Mohali doing a project in Computational Biology.

BEDTools DAVID DESeq

Antoine Rousselin

Ingénieur d'étude Centre Franois Baclesse

ONCOCNV CNVkit CNV-seq

Computational Biology Pfizer (United States)

QuickRNASeq

cell biology Guangzhou Institutes of Biomedicine and Health

deepTools SCDE Glbase

Bioinformatics Seoul National University

miARma-Seq RSEM EBSeq

Bioinformatics Chinese Academy of Sciences

Unai López de Heredia Larrea

Forest Genetics/bioinformatics Universidad Politécnica de Madrid

NGScloud ddradseqtools

Vinu Ramachandran

Research Scholar University of Madras

CANEapp RTPrimerDB ICG

Bioinfomagician Dankook University

Octopus-toolkit

Bioinformatic Programmer II University of California, San Francisco

zUMIs CEMiTool SinQC

I am an Electrical Engineer and Developer University of Engineering and Technology Lahore

LAVA GATK VARiD

Rinaldo Catta-Preta

Graduate Student Researcher University of California Davis Medical Center

DeepEnhancer Spectacle BWA

student Central South University

wapRNA Tuxedo ARCHS4

Madhu Sudhana Saddala

Genomics and Proteomics Johns Hopkins University

I am Dr. Madhu Sudhana Saddala working as a Postdoctoral Fellow in Wilmer Eye Institute, Johns Hopkins University School of Medicine, Baltimore, USA. Currently working on NGS data analysis of retinal and macular disease of eye.

DESeq easyRNASeq DEAR-O

PhD student Arizona State University

IGB ModelTest-NG R-Markdown

Parent category

RNA-seq analysis

Benchmarking

(Poplawski et al., 2015) Systematically evaluating interfaces for RNA-seq analysis from a life scientist perspective. Briefings in bioinformatics.
PMID: 26108229
(Everaert et al., 2017) Benchmarking of RNA-sequencing analysis workflows using whole-transcriptome RT-qPCR expression data. Sci Rep.
PMID: 28484260

Link to literature

Methodology

(Das et al., 2016) Analysis of Annotation and Differential Expression Methods used in RNA-seq Studies in Crustacean Systems. Integr Comp Biol.
PMID: 27940611

Related users

Seoul National University

Chinese Academy of Sciences

Rinaldo Catta-Preta

University of California Davis Medical Center

We use cookies to improve your experience and to deliver content tailored to your interests. See our privacy policy for more details.

About

Features

Blog

Community

Latest 100

Contact

Submit tool

Terms of use

Privacy policy

Tools
Bioinformatics trends
Latest 100
Community

Product
About
Features
Blog

Resources
Terms of use
Privacy policy

Contact

Unlock your biological data

© 2015 - 2018 OMICtools