The Allen Human Brain Atlas (AHBA) is the first example of human brain transcriptomic mappings and detailed anatomical annotations which, for the first time, has allowed the integration of human brain transcriptomics with neuroimaging. This has been made possible because the AHBA offered an original dataset that contains mRNA expression measures for >20,000 genes covering the whole brain and, critically, in a standard stereotaxic space. In recent years many different methods have been used to integrate this data set with brain imaging data, although this endeavour has lacked harmony in terms of the workflow of data processing and subsequent analyses. In this work we discuss five main issues that experience has highlighted as in need of thorough consideration when integrating the AHBA with neuroimaging. These concerns are corroborated by comparing the performance of three different publicly available methods in correlating the same measures of serotonin receptors density with the correspondent AHBA mRNA maps. In this representative case, we were able to show how these methods can lead to discrepant results, suggesting that processing options are not neutral. We believe that the field should take into serious consideration these issues as they could undermine reproducibility and, in the end, the intrinsic value of the AHBA. We also advise on possible strategies to overcome these discrepancies. Finally, we encourage authors towards practices that will improve reproducibility such as transparency in reporting, algorithm and data sharing, collaboration.