The importance of reproducible and transparent methods is receiving increasing recognition throughout the neuroimaging field. With its origins in bioinformatics, Snakemake is a fast-growing open source workflow management system that provides a high level of transparency, reproducibility and adaptability. Despite its wide adoption in the scientific community (>5 new citations/week), Snakemake has not yet had significant uptake in the neuroimaging community. In this work, we highlight aspects of Snakemake that can be of particular benefit to neuroimaging research and introduce a novel Python package and extension to Snakemake called Snakebids that provides interoperability with the BIDS and BIDS Apps standards. Snakebids provides the capability to turn a conventional Snakemake workflow into a command-line executable BIDS App, by adding elements that describe the BIDS App command-line interface to the Snakebids config file. It dynamically produces a Snakemake config file from an input dataset parsed with PyBIDS and provides a Snakemake-friendly helper function to generate BIDS-compliant paths, simplifying adherence to BIDS derivatives file naming standards. Snakemake can be an extremely useful tool for the neuroimaging community, as it allows users to rapidly prototype workflows that are easily understandable and adaptable by others. Snakebids provides a mechanism to build modular BIDS Apps that integrate with existing pre-processing and analysis tools and allow reuse of Snakemake workflows across multiple studies and datasets.