In our test, all samples had fewer than 50% adapter-adapter ligation reads (Additional file 1: Figure S2). PEPPRO counts and reports the fraction of reads that contain adapter-adapter ligation products, then removes adapter sequences and adapter-adapter ligation sequences before downstream alignment. The frequency of adapter-adapter ligation can be reduced by molecular techniques (see the Methods section), but these are not always possible and many experiments retain adapters in high molar excess, leading to substantial adapter-adapter sequences. The second ligation can lead to adapter-adapter ligation products that are amplified by PCR. These methods require two independent ligation steps to fuse distinct RNA adapters to each end of the nascent RNA molecule. Adapter ratioĪ common source of unwanted reads in PRO/GRO/ChRO-seq libraries results from adapter-adapter ligation. Here, we describe each plot and statistic produced by PEPPRO. Results of PEPPRO can be explored in the PEPPRO HTML-based web report, which displays all of the output statistics and QC plots (see PEPPRO documentation). We ran PEPPRO on our public test set, our differential expression test set, and our spike-in set. To demonstrate how PEPPRO responds to mRNA contamination, we also generated a set of 11 samples built from a single PRO-seq library (GSM1480327) that we spiked with increasing amounts of RNA-seq data (GSM765405) (Additional file 1: Figure S1). Thus, PEPPRO provides a unified, cross-platform pipeline for nascent RNA profiling projects. PEPPRO can be easily deployed across multiple samples either locally or via any cluster resource manager, and we also produced a computing environment with all the command-line tools required to run PEPPRO using either docker or singularity with the bulker multi-container environment manager. PEPPRO is compatible with the Portable Encapsulated Projects (PEP) format, which defines a common project metadata description, facilitating interoperability. PEPPRO features include (1) a serial alignment approach to remove ribosomal DNA reads (2) nascent transcription-specific quality control outputs and (3) a modular setup that is easily customizable, allowing modification of individual command settings or even swapping software components by editing human-readable configuration files. Here, we introduce PEPPRO, an analysis pipeline for uniform initial sample processing and novel quality control metrics. While tools are available for downstream analysis, such as to identify novel transcriptional units and bidirectionally transcribed regulatory elements, there is no comprehensive, unified approach to initial sample processing and quality control. With increasing data production, we require analysis pipelines for these data types. These advantages have led to growing adoption of global run-on (GRO-seq), precision run-on (PRO-seq), and, most recently, chromatin run-on (ChRO-seq) experiments. Fourth, nascent RNA profiling can be used to determine pausing and RNA polymerase accumulation within any genomic feature. Third, nascent RNA profiling measures unstable transcripts, which can be used to infer regulatory element activity and identify promoters and enhancers de novo by detecting bidirectional transcription and clustered transcription start sites (TSSs). Second, nascent RNA profiling measures not only RNA polymerase occupancy, but also orientation by default, whereas traditional RNA-seq requires specific library preparation steps to capture orientation. Steady-state transcription levels are commonly measured by RNA-seq, but there are many advantages to quantifying nascent RNA transcripts: First, it measures the transcription process directly, whereas steady-state mRNA levels reflect the balance of mRNA accumulation and turnover.
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