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A Galaxy based web server for processing and visualizing deeply sequenced data. The web server's core functionality consists of a suite of newly developed tools, called deepTools, that enable users with little bioinformatic background to explore the results of their sequencing experiments in a standardized setting. Users can upload pre-processed files with continuous data in standard formats and generate heatmaps and summary plots in a straight-forward, yet highly customizable manner.
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A tool to create a single report visualizing output from multiple tools across many samples, enabling global trends and biases to be quickly identified. MultiQC allows accurate comparison between samples, allowing detection of subtle differences not noticeable when switching between different files. Data visualization aids batch effect detection and minimizes the risk of confounding factors affecting the results of the study.
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Estimates mapping quality of ambiguously mapped next generation sequencing (NGS) reads. AlignerBoost utilizes a Bayesian-based framework, and tests with both simulated and real DNA-seq and RNA-seq datasets at various thresholds. This tool is also single nucleotide polymorphism (SNP)-aware, and higher quality alignments can be achieved if provided with known SNPs. It can process one million alignments within 30 seconds on a typical desktop computer.
A Java application that supports user-friendly quality control of mapping data, by considering sequence features and their genomic properties. Qualimap takes sequence alignment data and provides graphical and statistical analyses for the evaluation of data. Qualimap 2 represents a next step in the quality control analysis of high-throughput sequencing data. Along with comprehensive single-sample analysis of alignment data, it includes new modes that allow simultaneous processing and comparison of multiple samples.
Verifies sample identities from FASTQ, BAM or VCF files. NGSCheckMate uses a model-based method to compare allele read fractions at known single-nucleotide polymorphisms (SNPs), considering depth-dependent behavior of similarity metrics for identical and unrelated samples. It is effective for a variety of data types, including exome sequencing, whole-genome sequencing, RNAseq, ChIP-seq, targeted sequencing and single-cell whole-genome sequencing, with a minimal requirement for sequencing depth. The tool can be used as a quality control step in next-generation sequencing (NGS) studies.
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.
Evaluates different aspects of RNA-seq experiments, such as sequence quality, GC bias, polymerase chain reaction bias, nucleotide composition bias, sequencing depth, strand specificity, coverage uniformity and read distribution over the genome structure. RSeQC takes both SAM and BAM files as input, which can be produced by most RNA-seq mapping tools as well as BED files, which are widely used for gene models. Most modules in RSeQC take advantage of R scripts for visualization, and they are notably efficient in dealing with large BAM/SAM files containing hundreds of millions of alignments.
A package for phylogenomic analyses of data collected from conserved genomic loci using targeted enrichment. PHYLUCE allows the assembly of raw read data to contigs, the identification of ultra-conserved elements (UCE) contigs, parallel alignment generation, alignment trimming, and alignment data summary methods in preparation for analysis and alignment and SNP calling using UCE or other types of raw-read data. As it stands, the PHYLUCE package is useful for analyzing both data collected from UCE loci and also data collection from other types of loci for phylogenomic studies at the species, population, and individual levels.
AEHS / ArrayExpressHTS
Allows pre-processing, expression estimation and data quality assessment of RNA-seq datasets. ArrayExpressHTS furnishes a standard Bioconductor ExpressionSet object containing expression levels from raw sequence files with a single R function call. It can be used to analyze user's own datasets or public RNA-seq datasets from the ArrayExpress Archive. This tool is able to discover and quantify non-coding RNA. Moreover, it is customizable to be adapted to users’ needs.
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.
CLC bio / CLC Genomics Workbench
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Allows to analyze, compare, and visualize next generation sequencing (NGS) data. CLC Genomics Workbench offers a complete and customizable solution for genomics, transcriptomics, epigenomics, and metagenomics. The software enables to generate custom workflows, which can combine quality control steps, adapter trimming, read mapping, variant detection, and multiple filtering and annotation steps into a pipeline.
CADBURE / Comparing Alignment results of user’s RNA-Seq Data Based on the relative reliability of Uniquely aligned Reads
Evaluates spliced aligner performance on user's RNA-Seq data by comparing a pair of alignment results obtained either from two different aligners with the similar parameter set or from two different parameter sets with the same aligner. In alignment comparison, CADBURE determines the relative reliability of unambiguously (also called uniquely) aligned reads and non-uniquely aligned reads. The reads are further subdivided into eight distinct scenarios of potential alignment outcomes. These scenarios are binned into three categories: true positive, false positive, and true negative which enables CADBURE to determine specificity and accuracy for each result.
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Assists users in manipulating high-throughput sequencing (HTS) data and formats. Picard is a Java toolkit that provides a set of command line scripts. It comprises Java-based utilities that manipulate SAM files, and a Java API for creating new programs that reads and writes SAM files. Both SAM text format and SAM binary (BAM) format are supported. It also works with next generation sequencing (NGS).
QoRTs / Quality of RNA-Seq Toolset
Produces a broad array of quality control metrics. QoRTs allows visualization and comparison of RNA-seq data across numerous replicates sorted and differentiated by batch, biological condition, library, read-group, and/or sample. It is able to generate a comprehensive array of quality control metrics, browser tracks, summary plots, and read counts. The summary tracks created by this tool can be displayed mean normalized coverages across multiple samples.
Offers straight-forward methods to assess RNA-seq datasets for problems with duplicate reads and is aimed towards simple integration into standard analysis pipelines as a default quality control metric. dupRadar assesses the fraction of duplicate reads per gene dependent on the expression level. Apart from the Bioconductor package dupRadar we provide shell scripts for easy integration into processing pipelines. To enable interpretation of the dependency of duplication rate and gene expression, dupRadar currently includes various visualization functions.
A FastQ/Fasta/SAM information extractor implemented in HTML5 capable of offering insights into next-generation sequencing (NGS) data. MuffinInfo can run on any software or hardware environment, in command line or graphically, and in browser or standalone. It presents information such as average length, base distribution, quality scores distribution, k-mer histogram, and homopolymers analysis. MuffinInfo improves upon the existing extractors by adding the ability to save and then reload the results obtained after a run as a navigable file, by supporting custom statistics implemented by the user, and by offering user-adjustable parameters involved in the processing, all in one software.
Provides several selection strategies for the selection of verification candidates for somatic mutation calls from single-nucleotide variant. Valection uses 6 separate strategies for selecting candidates for verification. The first samples each mutation with equal probability. Two approaches separate mutations either by recurrence or by algorithm. The three others account for both factors: increasing or decreasing per overlap and directed sampling. All strategies are available in four different languages (C, Perl, R, Python) via programmatic bindings.
Evaluates RNA-seq alignment results. RNAseqEval is a package that can be used to compare the alignment of simulated reads to their genomic origin, or to compare the alignment of real reads to a set of annotated transcripts. It is written in Python and contains two main scripts, one for evaluating data simulated using PBSIM and the other for evaluating real data or data whose origin is unknown. Both scripts require aligner output in SAM format which they compare to gene annotations and, in case of simulated data, alignment files in MAF format describing the origin of each simulated read.
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