# Evaluation of Nanopore direct RNAseq data in Galaxy
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Direct RNA sequencing (DRS) using Oxford Nanopore technologies enables direct sensing of native RNA molecules. The RNA modification detection workflows for DRS data utilize the electrical deviations in the signal to identify RNA modifications directly in vivo by comparing the signal to unmodified RNA samples that are transcribed in vitro.
Up to now, two different works have tackled understanding the scope of SARS-CoV-2 genomic and sub-genomic RNAs using Nanopore DRS (Kim et al. (opens new window) and Taiaroa et al. (opens new window) ). Here, we provide workflows for the methylation analysis of SARS-CoV-2 within Galaxy framework in a scalable and reproducible fashion. In this way, we can provide a consistent analysis of the two available datasets. Thanks to the scalable nature of the Galaxy workflows, we will be able to consistenly process upcoming DRS data as well.
| description | sample | URL |
|---|---|---|
| Read mapping to viral genome | Fr1,Fr2,Fr3,Korean | |
| SARS-CoV-2: classify ONT reads by candidate junction regions | Fr1,Fr2,Fr3,Korean | |
| SARS-CoV-2: classify ONT reads by confirmed junction sites | Fr1,Fr2,Fr3,Korean | |
| Downsample reads to reduce coverage bias | ||
| Nanocompore sampcomp modification detection for three samples as one condition | Fr-3, IVT | |
| Tombo sample compare modification detection | All | |
| Map and downsample reads | IVT | |
| Variant analysis of isolates | Fr1,Fr2,Fr3 | |
| Construction of the combined human/SARS-CoV-2 reference genome | Fr1,Fr2,Fr3 | |
| Read mapping and sgRNA assignment | Fr1 | |
| Read mapping and sgRNA assignment | Fr2 | |
| Read mapping and sgRNA assignment | Fr3 | |
| Read mapping and sgRNA assignment | Kr | |
| Read mapping and sgRNA assignment | Au | |
| Read mapping and sgRNA assignment | IVT | |
| Nanopolish event alignment results | All | |
| Nanocompore modification results | Fr1, Fr2, Fr3 | |
| Tombo modification results | All |