The pathogenesis of severe Plasmodium falciparum malaria involves cytoadhesive microvascular sequestration of infected erythrocytes, mediated by P. falciparum erythrocyte membrane protein 1 (PfEMP1). PfEMP1 variants are encoded by the highly polymorphic family of var genes, the sequences of which are largely unknown in clinical samples as each parasite isolate contains a unique repertoire of var genes. This has hindered large scale analysis of var genes with previous characterisation attempts presenting a collection of limitations, including the inability to detect novel var sequences and only focussing on small regions of the var gene. Thus, the goal of this project was to develop novel approaches for var transcriptome quantification, which overcome the previous limitations and improve on current methods for var gene expression quantification. To achieve this, I first investigated different technical and biological factors, assembly tools and parameters in the context of var transcript assembly. This revealed the impact of read depth, read length, assembler type, k-mer value and the life cycle stage on var transcript assembly. The integration of these findings led to the development of a novel var transcript assembly and multi-dimensional quantification method. It substantially outperforms a previous approach on both laboratory and clinical isolates across a combination of metrics, including the N50 value, number of mis-assemblies and the ability to characterise lowly expressed var transcripts. It is a powerful tool to interrogate the var transcriptome in context with the rest of the transcriptome and can be applied to enhance our understanding of the role of var genes in malaria pathogenesis. I first applied the approaches to investigate changes in the var and core transcriptome during short-term in vitro cultivation. I then used the methods to assess the var transcriptome in infected individuals, where they previously had to be excluded from analysis. The new approaches lead the way for characterising the relationships between var gene expression and the rest of the parasite transcriptome. They enable large scale studies of associations of var gene expression with clinical outcomes and immunity to malaria. This has the potential to identify targets of novel therapy and identify key mediators of severe versus asymptomatic infections. This would further allow the development of vaccine candidates that would ensure high levels of immunity are achieved.