Recent breakthroughs in mRNA modifications have enabled RNA therapeutics with stabilised mRNA to improve vaccine efficacy. Despite their importance in biotechnology, the impact of mRNA modifications on stability and translation are poorly understood. N6-methyladenosine (m6A) is an mRNA modification thought to either improve translation efficacy or reduce stability of transcripts. We studied this modification in Plasmodium falciparum by disrupting the methyltransferase that makes m6A. Sequencing of m6A in mRNA has only recently become possible with Oxford Nanopore Technologies direct RNA sequencing. However, it is unclear how robust and accurate this detection of m6A is. We therefore compared four open-source tools that have been independently developed to identify m6A sites in Nanopore RNA-seq from P. falciparum trophozoites. Two of these tools detect m6A through machine learning systems trained to artificial RNA synthesized with m6A, whereas two work by detecting statistical differences between transcripts that possess or lack m6A. We found the former were less correlated in site prediction than the latter category. For transcripts with the most m6A sites predicted by each tool, six highly methylated transcripts were common to three tools. Future work involves time-series analysis of P. falciparum transcriptome using updated Nanopore flow cells with proprietary m6A detection.