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Scripts for identifying sites with differential error rates in mapped nanopore DRS data

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A tool for detecting modifications from Nanopore DRS errors using a low modification control

How to use:

  • Basecall & map direct RNA data (all datasets MUST be sequenced at approximately the same time with the exactly the same flowcell/kit/MinKNOW software, and basecalled and mapped in the same way with the same model, otherwise you WILL get loads of false positives. Nanopore update their pores/kits/models/software all the time, so be wary...).
  • Run differr on mapped bam files.
  • Output from differr is a bed file with the positions with significantly altered error, and a optional hdf5 file with all of the per reference base basecalls, which might be useful for further analyses.
  • Columns of bed file are:
    • chrom, start, end, name
    • score: -log10 of the FDR, rounded to nearest whole number
    • strand
    • odds ratio: the change in the ratio of matches to mismatches in the wild type compared to the mutant with low modifications. An odds ratio > 0 indicates more modifications in the WT.
    • G statistic for the comparison of pooled WT and mutant samples.
    • -log10 P value for the comparison of pooled WT and mutant samples.
    • -log10 FDR for the comparison of pooled WT and mutant samples.
    • G statistic for the homogeneity test of mutant replicates.
    • -log10 P value for the homogeneity test of mutant replicates.
    • G statistic for the homogeneity test of wild type replicates.
    • -log10 P value for the homogeneity test of wild type replicates.

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Scripts for identifying sites with differential error rates in mapped nanopore DRS data

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