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Exon skipping identification software tools | RNA sequencing data analysis

Considering that more than 90% of the human multi-exon genes have been found to undergo alternative splicing (AS), exon-skipping could be one of the most important ways to steer transcriptional regulation. RNA-seq enables better characterization and quantification of individual transcriptomes because it can detect both gene expression and alternative splicing AS. Exon-skipping is the most common AS mechanism known in mammals, and is a major contributor to protein diversity in mammals. Exon-skipping results in the loss of an exon in the alternatively spliced mRNA.


Source: (Wang et al., 2015) A survey of computational methods in transcriptome-wide alternative splicing analysis. Biomol Concepts.


 

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AStalavista / Alternative Splicing TrAscriptional LAndscape VISualization Tool And more
Allows identification, extraction and displaying of complex alternative splicing (AS) events from annotated genes. AStalavista is an alternative splicing transcriptional landscape visualization tool for investigating and comparing types and distributions of the different AS events found in whole genome annotations and user provided gene sets. The software enables identification of arbitrarily complex combinations of hitherto described AS events, either visually or by representation in a univocal notation system. It can be used if the sequencing/annotation process has not been completed.
AltAnalyze
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).
GESS / Graph-based Exon-Skipping Scanner
Detects de novo exon-skipping events directly from raw RNA-seq data without prior knowledge of gene-annotation information. First, we build a splicing-site-linking graph from splicing-aware aligned reads using a greedy algorithm. We then iteratively scan this linking graph to obtain those patterns conforming to skipping events. Finally, we apply the MISO model to calculate the ratio of skipping versus inclusion isoforms and determine which is the dominant isoform.
dSpliceType
A generalized framework to systematically investigate the synergistic and antagonistic effects of differential splicing and differential expression. dSpliceType detects and prioritizes a list of genes that are differentially expressed and/or spliced. In particular, the multivariate dSpliceType is among the fist to utilize sequential dependency of normalized base-wise read coverage signals and capture biological variability among replicates using a multivariate statistical model.
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