A new REDItools implementation to speed-up the RNA editing profiling in massive RNAseq data
Install from PyPi.
pip install REDItools3
Use the whl file under the dist directory.
pip install dist/reditools-0.1-py3-none-any.whl
Once installed, reditools can be run from the commandline.
python -m reditools
This is the core reditools function: detecting editing events from one or more BAM file.
The output is a tab separated table with these columns:
| Field | Description |
|---|---|
| Region | Chromosome or contig |
| Position | Position in the region |
| Reference | Base from the reference sequence |
| Strand | DNA strand (+, -, or *) |
| Coverage-q30 | How many reads had a quality of at least 30 |
| MeanQ | Mean read quality |
| BaseCount[A,C,G,T] | Total count of each base found |
| AllSubs | All the detected substitutions |
| Frequency | Ratio of non-reference bases to reference bases |
| gCoverage-q30 | Genomic Coverage-q30 (see annotate) |
| gMeanQ | Genomic MeanQ (see annotate) |
| gBaseCount[A,C,G,T] | Genomic BaseCount (see annotate) |
| gAllSubs | Genomic variants (see annotate) |
| gFrequency | Genomic variant frequency (see annotate) |
The last 5 columns will always be blank (-). They are reserved for output
from the annotate tool.
Annotate RNA editing output with variant detection from genomic data.
annotate takes two reditools output files and fills in the last five columns
of the first file with positional matches from the second.
For example, this RNA file:
Region Position Reference Strand Coverage-q30 MeanQ BaseCount[A,C,G,T] AllSubs Frequency gCoverage-q30 gMeanQ gBaseCount[A,C,G,T] gAllSubs gFrequency
chr1 1115715 C * 2 38.00 [0, 2, 0, 0] - 0.00 - - - - -
chr1 1115716 A * 2 38.00 [2, 0, 0, 0] - 0.00 - - - - -
With this DNA file:
Region Position Reference Strand Coverage-q30 MeanQ BaseCount[A,C,G,T] AllSubs Frequency gCoverage-q30 gMeanQ gBaseCount[A,C,G,T] gAllSubs gFrequency
chr1 1115716 A * 2 38.00 [2, 0, 0, 0] - 0.00 - - - - -
chr1 1115717 C * 2 38.00 [0, 2, 0, 0] - 0.00 - - - - -
Produces:
Region Position Reference Strand Coverage-q30 MeanQ BaseCount[A,C,G,T] AllSubs Frequency gCoverage-q30 gMeanQ gBaseCount[A,C,G,T] gAllSubs gFrequency
chr1 1115715 C * 2 38.00 [0, 2, 0, 0] - 0.00 - - - - -
chr1 1115716 A * 2 38.00 [2, 0, 0, 0] - 0.00 2 38.00 [2, 0, 0, 0] - 0.00
Identify repetitive elements in a FASTQ file.
Compute RNA editing index from reditools analyze output
(PMDI: 31636457).
The index tool computes the editing indices for all possible variants, not
just A-to-I (listed as A-G in the output).
Please cite the following papers when using REDItools3
- Fonzino A, Mazzacuva PL, Handen A, Silvestris DA, Arnold A, Pecori R, Pesole G, Picardi E. REDInet: a temporal convolutional network-based classifier for A-to-I RNA editing detection harnessing million known events. Brief Bioinform. 2025 Mar 4;26(2):bbaf107. doi: 10.1093/bib/bbaf107. PMID: 40112338; PMCID: PMC11924403.
- Picardi E, Pesole G. REDItools: high-throughput RNA editing detection made easy. Bioinformatics. 2013 Jul 15;29(14):1813-4. doi: 10.1093/bioinformatics/btt287. Epub 2013 Jun 5. PMID: 23742983.