If you use TractoR in your work, please cite the following paper, which describes the package in general:

J.D. Clayden, S. Muñoz Maniega, A.J. Storkey, M.D. King, M.E. Bastin & C.A. Clark (2011). TractoR: Magnetic resonance imaging and tractography with R. Journal of Statistical Software 44(8):1–18.

Additionally, the table below outlines the relevant papers which should be cited when using various parts of the functionality provided by TractoR.

Script name(s) Reference(s)
dpreproc (stage 2, with UseTopup:true only) Andersson J.L.R., Skare S. & Ashburner J. (2003). How to correct susceptibility distortions in spin-echo echo-planar images: Application to diffusion tensor imaging. NeuroImage 20(2):870–888.
dpreproc (stage 3, with MaskingMethod:bet only) Smith S. (2002). Fast robust automated brain extraction. Human Brain Mapping 17(3):143–155.
dpreproc (stage 4, with EddyCorrectionMethod:eddy only) Andersson J.L.R. & Sotiropoulos S.N. (2016). An integrated approach to correction for off-resonance effects and subject movement in diffusion MR imaging. NeuroImage 125:1063–1078.
bedpost Behrens T., Johansen-Berg H., Jbabdi S., Rushworth M. & Woolrich M. (2007). Probabilistic diffusion tractography with multiple fibre orientations: What can we gain? NeuroImage 34(1):144–155.
track, mtrack, rtrack Behrens T., Johansen-Berg H., Jbabdi S., Rushworth M. & Woolrich M. (2007). Probabilistic diffusion tractography with multiple fibre orientations: What can we gain? NeuroImage 34(1):144–155.
hnt-eval, hnt-interpret, hnt-ref, hnt-viz Clayden J., Bastin M. & Storkey A. (2006). Improved segmentation reproducibility in group tractography using a quantitative tract similarity measure. NeuroImage 33(2):482–492.
pnt-ref, pnt-train, pnt-eval Clayden J., Storkey A. & Bastin M. (2007). A probabilistic model-based approach to consistent white matter tract segmentation. IEEE Transactions on Medical Imaging 26(11):1555–1561.
pnt-em Clayden J., Storkey A., Muñoz Maniega S. & Bastin M. (2009). Reproducibility of tract segmentation between sessions using an unsupervised modelling-based approach. NeuroImage 45(2):377–385.
pnt-prune Clayden J., King M. & Clark C. (2009). Shape modelling for tract selection. In Yang G.-Z., Hawkes D., Rueckert D., Noble A. & Taylor C. (eds), Proceedings of the 12th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI). Lecture Notes in Computer Science, vol. 5762, pp. 150–157. Springer-Verlag.
reg-linear (with Method:fsl) Jenkinson M., Bannister P., Brady J. & Smith S. (2002). Improved optimisation for the robust and accurate linear registration and motion correction of brain images. NeuroImage 17(2):825–841.
reg-linear (with Method:niftyreg) Modat M., Cash D.M., Daga P., Winston G.P, Duncan J.S & Ourselin S. (2014). Global image registration using a symmetric block-matching approach. Journal of Medical Imaging 1(2):024003.
reg-nonlinear Modat M., Ridgway G., Taylor Z., Lehmann M., Barnes J., Hawkes D., Fox N. & Ourselin S. (2010). Fast free-form deformation using graphics processing units. Computer Methods and Programs in Biomedicine 98(3):278–284.
freesurf Please see
graph-build (with Type:functional and UseShrinkage:true) Schäfer J. & Strimmer K. (2005). A shrinkage approach to large-scale covariance matrix estimation and implications for functional genomics. Statistical Applications in Genetics and Molecular Biology 4(1):32.
Opgen-Rhein R. & Strimmer K. (2007). Accurate ranking of differentially expressed genes by a distribution-free shrinkage approach. Statistical Applications in Genetics and Molecular Biology 6(1):9.
graph-decompose (with Method:principal-networks) Clayden J., Dayan M. & Clark C. (2013). Principal networks. PLoS ONE 8(4):e60997.
graph-decompose (with Method:modularity) Newman M. (2006). Modularity and community structure in networks. Proceedings of the National Academy of Sciences of the United States of America 103:8577–8582.