RNA dynamic quantification software tools | RNA sequencing data analysis
Cellular mRNA levels originate from the combined action of multiple regulatory processes, which can be recapitulated by the rates of pre-mRNA synthesis, pre-mRNA processing and mRNA degradation. Recent experimental and computational advances set the basis to study these intertwined levels of regulation.
Assesses the proportion of old and new RNA. GRAND-SLAM permits users to deduce the proportion and corresponding posterior distribution of new and old RNA for each gene in a single SLAM-seq experiment. This software provides five main features: (1) it doesn’t require control experiment; a single labeling experiment is enough to estimate RNA half-lives; (3) it exploits posterior distributions to estimate half-lives; (4) assures an internal quality control for gene and experiment and (5) it allows to investigate fast regulatory processes.
Allows to analyze 4sU- and RNA-seq data. INSPEcT can determine the probability of a given combination of rate to regulate the gene expression during the time-course by modeling and comparing alternative scenarios of transcriptional regulation. This tools allows to test the performance given a dataset and predict how many additional replicates and time points would be needed to reach the desired performance.
A computational method to assess a quantitative measure of mRNA integrity. This is done by quantitatively modeling of the 3' bias of read coverage profiles along each mRNA transcript. A per-sample summary mRIN is then derived as an indicator of mRNA degradation. This method has been used for systematic analysis of large scale RNA-Seq data of postmortem tissues, in which RNA degradation during tissue collection is particularly an issue.
Estimates RNA synthesis and decay rates from pre-processed microarray or RNA-Seq measurements of any organisms obtained via the Dynamic Transcriptome Analysis (DTA) or the comparative DTA (cDTA) protocol. DTA covers all aspects of the RNA labeling technique: bias correction, detailed visualization of quality control aspects and proper handling of the results. It can be integrated in R scripts for pre-processing.
Supplies a flexible interface and readily accommodates numerous different experimental designs. pulseR models count data with the more appropriate negative-binomial model. It can handle labelled and unlabelled spike-in sets in its workflow and accounts for potential labeling biases. This can be useful for taking into account the difference in the uridine content.
Allows the precise determination of transcript half-lives from measurements of RNA de novo transcription or decay determined with microarrays or RNA-seq. HALO is an extensible Java framework providing state-of-the-art methods for transcript half-life calculation as well as quality control, filtering and normalization. It can be integrated into other gene expression profiling frameworks or can be used as a standalone. It aims to calculate transcript half-lives in a fast and straightforward way from new measurements of de novo synthesis and/or decay both for microarrays or RNA-seq.
Quantitatively determines RNA degradation on the short-read distribution of individual transcripts. RD aims to characterize and adjust the position-dependent bias in RNA-Seq for individual transcripts. This tool can improve the accuracy of transcript isoform expression estimation.