Transcription Elongation Profiling
Calculate Area Under Curve (AUC) and Differences of AUC for Transcript...
Calculate Attenuation from AUC and Other Transcript Features
Calculate Average Expression and Filter Transcript Data
Blacklist High Mappability Regions in Genomic Data
Check Validity of Experiment Table
Count NA values per transcript and condition
Create a Unified Table of Scores
Compute ECDF for Genes Based on Expression Data
Calculate knee for each condition separately
Identify the Knee and Max ECDF Differences for Each Transcript
Split Gene Annotations into Fixed-Size Windows
Compute Mean and Differences of Scores for Each Condition
Plot AUC Comparison Between Conditions
Plot Empirical Cumulative Distribution Function (ECDF)
Plot Histogram of Distance from TSS to Knee Point
Plot Metagenes for Gene Groups
Generate all tepr plots for all experiment comparisons
Preprocess Experimental Data for Genomic Analysis
Retrieve and Combine Annotation Information
Retrieve all the comparison names from the experiment table
Perform the tepr differential nascent rna-seq analysis
Perform tepr differential nascent rna-seq analysis for multiple condit...
Define Universe and Group of Genes Based on Expression Data
The general principle relies on calculating the cumulative signal of nascent RNA sequencing over the gene body of any given gene or transcription unit. 'tepr' can identify transcription attenuation sites by comparing profile to a null model which assumes uniform read density over the entirety of the transcription unit. It can also identify increased or diminished transcription attenuation by comparing two conditions. Besides rigorous statistical testing and high sensitivity, a major feature of 'tepr' is its ability to provide the elongation pattern of each individual gene, including the position of the main attenuation point when such a phenomenon occurs. Using 'tepr', users can visualize and refine genome-wide aggregated analyses of elongation patterns to robustly identify effects specific to subsets of genes. These metrics are suitable for internal comparisons (between genes in each condition) and for studying elongation of the same gene in different conditions or comparing it to a perfect theoretical uniform elongation.