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A single-cell assembler for capturing and sequencing “microbial dark matter” that forms small pools of randomly selected single cells (called a mini-metagenome) and further sequences all genomes from the mini-metagenome at once. SPAdes is intended for both standard isolates and single-cell MDA bacteria assemblies. It works with Illumina or IonTorrent reads and is capable of providing hybrid assemblies using PacBio, Oxford Nanopore and Sanger reads. You can also provide Additional contigs can also be provided to be used as long reads. SPAdes supports paired-end reads, mate-pairs and unpaired reads and can take as input several paired-end and mate-pair libraries simultaneously.
EBARDenovo / Extension, Bridging And Repeat-sensing Denovo
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Assembles paired-end RNA-Seq data. EBARDenovo is based on a bi-directional expansion method using paired-end RNA-Seq data to guide the transcriptome assembly. The software is suited for detecting chimeric reads, created by natural gene fusion or sequence recombination, and assembly errors. Its outputs can be used for further analyses such as the identification of RNA editing sites and gene fusion candidates.
A comprehensive and user-friendly system for computational analysis of bacterial RNA-seq data. As input, Rockhopper takes RNA sequencing reads output by high-throughput sequencing technology (FASTQ, QSEQ, FASTA, SAM, or BAM files). Rockhopper supports the following tasks: reference based transcript assembly; de novo transcript assembly; normalizing data from different experiments; quantifying transcript abundance; testing for differential gene expression; characterizing operon structures; visualizing results in a genome browser.
MIRA / Mimicking Intelligent Read Assembly
Uses a Swiss army knife of sequence assembly developed and used in the past 16 years to get assembly jobs done efficiently - and especially accurately. MIRA is a whole genome shotgun (WGS) and EST sequence assembler for Sanger, 454, Solexa (Illumina), IonTorrent data and PacBio. It supports ancillary data in TRACEINFO format (from NCBI), marks places of interest with tags so that these can be found quickly in finishing programs and has a single nucleotide polymorphism (SNP) analysis pipeline for sequencing data of viruses and prokaryotes.
STM / Scaffolding using Translation Mapping
Allows de-novo assembly of transcriptome using a reference proteome. STM exploits the fact that, by translating contigs into amino acid sequences, it is possible to search for orthologous regions in a reference proteome, even when it belongs to a distantly related organism. The method can join multiple transcript fragments that are part of a single gene, providing new and valuable information on the order and the orientation of these fragments along original transcript. Multiple- k, a method that performs multiple assemblies with various k-mer lengths and retains the best part of each one to form the final assembly is also available.
A de novo transcriptome assembler that takes advantage of techniques employed in Cufflinks to overcome limitations of the existing de novo assemblers. When tested on dog, human and mouse RNA-seq data, Bridger assembled more full-length reference transcripts while reporting considerably fewer candidate transcripts, hence greatly reducing false positive transcripts in comparison with the state-of-the-art assemblers. It runs substantially faster and requires much less memory space than most assemblers. More interestingly, Bridger reaches a comparable level of sensitivity and accuracy with Cufflinks.
CAFE / Co-Assembly of stranded and unstranded RNA-seq data Followed by End-correction
Improves the original assemblies, respectively assembled with stranded and/or unstranded RNA-seq data. CAFE is a high-performing transcriptome assembly pipeline that enables to predict the directions of about 220 billion unstranded reads, which led to the construction of more accurate transcriptome maps, comparable to the manually curated map. It should not only help to build comprehensive, precise transcriptome maps from complex genomes but also to expand the universe of non-coding genomes.
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.
A de novo algorithm to assemble full-length transcripts by remodeling the problem as tracking a set of trajectories of items over a splicing graph. This approach, which subtly integrates the coverage information into the procedure, has two exclusive features: 1) only splicing junctions are involved in the assembling procedure; 2) massive pell-mell reads are assembled seemingly by moving a comb along junction edges on a splicing graph. Being tested on both real and simulated RNA-seq datasets, BinPacker outperforms almost all existing de novo assemblers on all the tested datasets, even outperforms those ab initio assemblers on the dog dataset, in terms of commonly used comparison standards.
FRAMA / from RNA-seq to annotated mRNA assembly
A genome-independent annotation tool for de novo mRNA assemblies that addresses several post-assembly tasks, such as reduction of contig redundancy, ortholog assignment, correction of misassembled transcripts, scaffolding of fragmented transcripts and coding sequence identification. FRAMA executes in 8 successive steps: (i) assembly, (ii) primary processing, (iii) gene symbol assignment, (iv) fusion detection, (v) scaffolding, (vi) identification of CDS, (vii) identification of mRNA boundaries, and (viii) descriptive assembly statistics. FRAMA realizes the de novo construction of a low-redundant transcript catalog for eukaryotes, including the extension and refinement of transcripts. Thereby, results delivered by FRAMA provide the basis for comprehensive downstream analyses like gene expression studies or comparative transcriptomics.
RNA-seq portal
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.
Assembles large-scale expressed sequence tags (EST) datasets and automatically identifies and correct assembly errors. iAssembler employs an iterative assembly strategy and automated assembly error corrections to deliver highly accurate de novo assemblies of EST sequences. This method contains seven major functional modules: (i) general controller, (ii) MIRA assembler, (iii) CAP3 assembler, (iv) megablast assembler, (v) type I error corrector, (vi) type II error corrector, and (vii) unigene base corrector.
SATRAP / SOLiD Assembler TRAnslation Program
A computer program designed to efficiently translate de novo assembled color-space sequences into a base-space format. The program was tested and validated using simulated and real transcriptomic data; its modularity allows an easy integration into more complex pipelines, such as Oases for RNA-seq de novo assembly. SATRAP is available either as a multi-step pipeline incorporating several tools for RNA-seq assembly or as an individual module for use with the Oases package.
NOmESS / NOn-redundant protEin Sequence Sets
An automated pipeline for the assembly of available sequence information (e.g. ESTs, Contigs, RNAseq, exome sequencing data etc.) into a non-redundant reference dataset based on homology to a closely related species. NOmESS facilitates to overcome the limitations of proteomic studies with poorly characterized organisms. In a step by step process the input sequences are clustered, assembled, joined and in the end representatives of each cluster are selected, resulting in a non-redundant reference set representing the maximal available amino acid sequence information. This set can then be used as the search database in a MaxQuant run.
Adopts a novel approach to metatranscriptomic assembly that makes use of the fact that there is a database of millions of known protein sequences associated with mRNAs. How to effectively use the protein information is nontrivial given the size of the database and given that different mRNAs might lead to proteins with similar functions (because different amino acids might have similar characteristics). IDBA-MTP employs a similarity measure between mRNAs and protein sequences, dynamic programming techniques, and seed-and-extend heuristics to tackle the problem effectively and efficiently. Experimental results show that IDBA-MTP outperforms existing assemblers by reconstructing 14% more mRNAs.
A pipeline for post-processing of pre-assembled transcriptomes using reference based method. TransPS applies an align-layout-consensus structure, consisting of three major stages. First, query sequences are aligned with a reference genome. Second, query sequences are ordered based on the alignment to the reference. Third, non-redundant sequences matched to the same gene of reference genome are scaffolded into one contig. TransPS shows promising results on the test transcriptome datasets, where redundancy is greatly reduced by more than 50% and, at the same time, coverage is improved considerably.
An integrated collection of Perl modules focused on building efficient pipelines for NGS data processing. ViennaNGS comes with functionality for extracting and converting features from common NGS file formats, computation and evaluation of read mapping statistics, as well as normalization of RNA abundance. Moreover, ViennaNGS provides software components for identification and characterization of splice junctions from RNA-seq data, parsing and condensing sequence motif data, automated construction of Assembly and Track Hubs for the UCSC genome browser, as well as wrapper routines for a set of commonly used NGS command line tools.
DRUT / Discovery and Reconstruction of Unannotated Transcripts
Allows transcriptome discovery, reconstruction and quantification in partially annotated genomes. DRUT is an annotation-guided general framework. The software incorporates an enhancement of EM algorithm, VTEM, to detect overexpressed reads and/or exons corresponding to the unannotated transcripts and to estimate annotated transcript frequencies. It was validated using three experiments over human RNA-seq data, two experiments on transcriptome quantification and one experiment on transcriptome discovery and reconstruction.
Automatically combines transcriptomes from difference sources, such as assembly and annotation, into a compact and unified reference. necklace is applicable to any species with an incomplete reference genome. It aligns and counts reads in preparation for testing for differential gene expression and differential transcript usage analysis. This tool provides the following steps: initial assembly, clustering transcripts into gene groupings, reassembly to build the superTranscriptome and finally alignment and counting of mapped reads in preparation for differential expression testing.
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.
Assembles Illumina single or paired-end reads and incorporates strand-specific RNA-Seq reads into the assembly. Rnnotator is an automated software pipeline that consists of three major components: preprocessing of reads, assembly, and post-processing of contigs. In the absence of a reference transcriptome, the software can produce a set of transcripts directly from RNA-Seq reads. It was applied to two yeast transcriptomes and the results were compared to the reference gene catalogs of these organisms.
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