The following scripts are tailored to suite the data published in Forde et al. 2015
Running title: E. coli EC958 methylome
Python script dedicated to counting motifs within genomic segments R scripts dedicated to the statistical analysis and graphical output of the distribution of methylation motifs
Scripts available:
How to:
motif_counts.py
- Takes in a tab delimited file of motif positions in genome
- Takes in a tab delimited file of segments (in this case, 1 kbp segments with a 250bp overlap of the genome, generated using Bedtools makewindows option)
- Counts number of motifs within each segment and writes output to the outfile
adjusted_anova.R
- Takes in a tab delimited file, with each motif count per segment and region of each segment required
- For each methylation motif in the genome, perform an analysis of variance, adjusted for heteroscedasticity. Reports anova test statistic, mean motif count per genomic region, pair-wise post hoc P values and confidence intervals around the mean
motif_distance_vs_position.R
- Takes in a tab delimited file (start position of motif, distance between motifs, genomic region (i.e. Core-genome, Prophage, Genomic Island)), computes summary statistics and plots the distance between motifs (bp) vs. position in genome (bp). Figure can be saved in svg format