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Allows users to interact with high-throughput sequencing data. SAMtools permits the manipulation of alignments in the SAM/BAM/CRAM formats: reading, writing, editing, indexing, viewing and converting SAM/BAM/CRAM format. It limits the mapping quality of reads with excessive mismatches and applies base alignment quality to fix alignment errors. This tool can sort and merge alignments, remove polymerase chain reaction (PCR) duplicates or generate per-position information.
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A software suite for the comparison, manipulation and annotation of genomic features in browser extensible data (BED) and general feature format (GFF) format. BEDTools also supports the comparison of sequence alignments in BAM format to both BED and GFF features. The tools are extremely efficient and allow the user to compare large datasets (e.g. next-generation sequencing data) with both public and custom genome annotation tracks. BEDTools can be combined with one another as well as with standard UNIX commands, thus facilitating routine genomics tasks as well as pipelines that can quickly answer intricate questions of large genomic datasets.
rMATS / replicate Multivariate Analysis of Transcript Splicing
A statistical model and computer program designed for detection of differential alternative splicing from replicate RNA-Seq data. rMATS uses a hierarchical model to simultaneously account for sampling uncertainty in individual replicates and variability among replicates. In addition to the analysis of unpaired replicates, rMATS also includes a model specifically designed for paired replicates between sample groups. The hypothesis-testing framework of rMATS is flexible and can assess the statistical significance over any user-defined magnitude of splicing change. The old version of rMATS was called MATS.
Estimates, from RNA-seq experiments, the mean-variance relationship of the log-counts, generates a precision weight for each observation and enters these into the limma empirical Bayes analysis pipeline. voom opens access for RNA-seq analysts to a large body of methodology developed for microarrays. Simulation studies show that voom performs as well or better than count-based RNA-seq methods even when the data are generated according to the assumptions of the earlier methods. The voom methodology is implemented in the voom function of the limma package available from the Bioconductor project repository.
Tests for differential usage of exons and hence of isoforms in RNA-seq samples. DEXSeq uses generalized linear models and offers reliable control of false discoveries by taking biological variation into account. It also detects with high sensitivity genes, and in many cases exons, that are subject to differential exon usage. DEXSeq achieves reliable control of false discovery rates by estimating variability for each exon or counting bin and good power by sharing dispersion estimation across features.
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.
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.
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.
ST Pipeline
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.
A package that provides efficient low-level and highly reusable S4 classes for storing ranges of integers, RLE vectors (Run-Length Encoding) and, more generally, data that can be organized sequentially (formally defined as Vector objects), as well as views on these Vector objects. IRanges provides also efficient list-like classes for storing big collections of instances of the basic classes. All classes in the package use consistent naming and share the same rich and consistent "Vector API" as much as possible.
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.
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.
Combines existing well-known and novel RNA-seq tools for not only detection and quantification of viral RNA, but also variants in the viral transcripts. ViGEN includes 4 major modules: the first module allows to align and filter out human RNA sequences; the second module maps and count (remaining un-aligned) reads against reference genomes of all known and sequenced human viruses; the third module quantifies read counts at the individual viral genes level thus allowing for downstream differential expression analysis of viral genes between experimental and controls groups, and the fourth module calls variants in these viruses.
IRAP / integrated RNA-seq Analysis Pipeline
A flexible RNA-seq analysis pipeline that allows the user to select and apply their preferred combination of existing tools for mapping reads, quantifying expression and testing for differential expression. iRAP also includes multiple tools for gene set enrichment analysis and generates web browsable reports of the results obtained in the different stages of the pipeline. Depending upon the application, iRAP can be used to quantify expression at the gene, exon or transcript level.
Array Studio
Provides the premier enterprise solution for data content, framework and graphical user interface for omic and next-generation sequencing data analysis. Array Suite (Array Studio and Array Server) differs from standard desktop solutions or open source solutions, with Array Studio providing the graphical user interface for NGS and omic analysis and visualization and Array Server providing the enterprise back-end solution for project management, sample management and data storage.
A python toolkit providing best-practice pipelines for fully automated high throughput sequencing analysis. You write a high level configuration file specifying your inputs and analysis parameters. This input drives a parallel pipeline that handles distributed execution, idempotent processing restarts and safe transactional steps. The goal is to provide a shared community resource that handles the data processing component of sequencing analysis, providing researchers with more time to focus on the downstream biology.
PORT / Pipeline of RNA-Seq Transformations
Allows users to perform RNA-Seq differential expression analysis. PORT is a pipeline dedicated to resampling based read-level normalization and quantification. The application can apply two types of normalization at gene and exon-intron-junction level, based on various normalization factors such as ribosomal or mitochondrial content as well as the proportion of gene-mappers. It first filters the input files and categorizes it. Then, the pipeline performs the resample of the sequence for lastly merging the files to quantify features.
Allows users to analyze alternative splicing using RNA-Seq. Quantas is a toolkit that is composed of two main elements: (i) gapless which is a package that uses paired-end RNA-seq data to deduce transcript structure; and (ii) countit, that numbers RNA-seq reads for each alternative splicing isoform and is also able to quantify gene expression. The application permits users to summarize alternative splicing results and to perform statistical tests before generating files that can be visualized through the UCSC genome browser.
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