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ERANGE / Enhanced Read Analysis of Gene Expression
A software tool for mapping and quantifying Mammalian transcriptomes by RNA-Seq. The functions of ERANGE are to (i) assign reads that map uniquely in the genome to their site of origin and, for reads that match equally well to several sites ('multireads'), assign them to their most likely site(s) of origin; (ii) detect splice-crossing reads and assign them to their gene of origin; (iii) organize reads that cluster together, but do not map to an already known exon, into candidate exons or parts of exons; and (iv) calculate the prevalence of transcripts from each known or newly proposed RNA, based on normalized counts of unique reads, spliced reads and multireads.
MISO / Mixture of Isoforms
Offers a model for alternative splicing (AS) at exon or isoform level. MISO is a program that uses information in single-end or paired-end RNA-seq data and a Bayesian inference to estimate the probability for a read to be issued from a particular isoform. The program is available through two packages: in C language (fastmiso) or in Python language (misopy). The application supplies confidence intervals (CIs) for: (i) estimating of exon and isoform abundance, (ii) identifying differential expression. It can be applied for analyzing isoform regulation.
Analyzes parallel RNA sequence data to catalog transcripts and assess differential and alternative expression of known and predicted mRNA isoforms in cells and tissues. ALEXA-Seq comprises several functions: (1) creation of a database of expression and alternative expression sequence ‘features’, (2) mapping of short paired-end sequence reads to these features, (3) identification of features that are expressed above background noise while taking into account locus-by-locus noise, or (4) identification of features that are differentially expressed in samples.
RSEM / RNA-Seq by Expectation-Maximization
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Performs gene and isoform level quantification from RNA-Seq data. RSEM is a software package that quantifies gene and isoform abundances from single-end (SE) or paired-end (PE) RNA-Seq data. The software enables visualization of its output through probabilistically-weighted read alignments and read depth plots. It does not require a reference genome and thus can be useful for quantification with de novo transcriptome assemblies.
BitSeq / Bayesian inference of transcripts from sequencing data
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An application for inferring expression levels of individual transcripts from sequencing (RNA-Seq) data and estimating differential expression (DE) between conditions. An advantage of this approach is the ability to account for both technical uncertainty and intrinsic biological variance in order to avoid false DE calls. The technical contribution to the uncertainty comes both from finite read-depth and the possibly ambiguous mapping of reads to multiple transcripts.
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Offers a platform for the detection of genomic features into transcripts from next generation RNA sequencing data. RNA-eXpress provides a graphic user interface (GUI) dedicated to the identification of splice variants, transcription start sites, UTRs, introns as well as non-coding RNA features. Users can run feature annotation, comparison, sequence extraction and read counting. The application can supply results as summary statistics, histograms or pie charts.
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.
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).
A command-line software program to go from a de novo transcriptome assembly to gene-level counts. Corset takes a set of reads that have been multi-mapped to the transcriptome (where multiple alignments per read were reported) and hierarchically clusters the transcripts based on the proportion of shared reads and expression patterns. It will report the clusters and gene-level counts for each sample, which are easily tested for differential expression with count based tools such as edgeR and DESeq.
SQANTI / Structural and Quality Annotation of Novel Transcript Isoforms
Provides a wide range of descriptors of transcript quality and generates a graphical report to aid in the interpretation of the sequencing results. SQANTI is a pipeline for the in-depth characterization of isoforms obtained by full-length transcript sequencing, which are commonly returned in a fasta file format without any extra information about gene/transcript annotation or attribute description. This software is oriented to be used for characterization of isoforms generated by PacBio Iso-Seq pipeline. Besides, it can be applied to any organism.
Detects and quantify alternative splicing (AS) events in RNA-Seq experiments. Solas is an R package that is composed of three different functions: (i) DASI (Differential Alternative Splicing Index), for the detection of alternative splicing events differentiating two conditions; (ii) CASI (Cell Alternative Splicing Index), for the identification of genes and exons which are part of an AS event; and (iii) POEM (Proportion Estimation) for the quantification of the relative proportion of different isoforms.
Detects and visualizes of differential alternative transcription. DiffSplice is an ab initio method to detect alternative splicing isoforms that are differentially expressed under different conditions using high-throughput RNA-seq reads. This software directly localizes where differential splicing occurs, making it easier to identify exons involved in alternative transcription. It estimates the relative proportion of alternative transcription flows in every ASM and calculates the Jensen–Shannon divergence (JSD) to quantify the difference in transcription between samples.
Traph / Transcrips in gRAPHs
Allows to identify and quantify transcript. Traph is a de novo genome-based tool with two-fold advantage: (i) it translates a problem as an established one in the field of network flows, which can be solved in polynomial time, with different existing solvers and (ii) it is general enough to encompass many of the previous proposals under the least sum of squares model. This method is based on network flows for a multi-assembly problem arising from isoform identification and quantification with RNA-Seq.
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.
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.
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.
WemIQ / Weighted-log-likelihood expectation maximization method on Isoform Quantification
Integrates an effective bias removal with a weighted expectation maximization (EM) algorithm to distribute reads among isoforms efficiently. WemIQ improves the quantification of isoform and gene expression as well as the derived exon inclusion rates. It provides robust expression estimates across different laboratories and protocols, which is valuable for the integrative analysis of RNA-seq. This tool can distinguish bias heterogeneity from true biological heterogeneity.
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