Q: How can I cite this work?
A: If you find these tools useful for your research, please cite as: Stein JL*, de la Torre-Ubieta L*, Tian Y, Parikshak NN, Hernandez IA, Marchetto MC, Baker DK, Lu D, Lowe JK, Wexler EM, Muotri AR, Gage FH, Kosik KS, Geschwind DH. “A quantitative framework to evaluate modeling of cortical development by neural stem cells.” Neuron 83, 69–86. July 2, 2014. [Link]

Q: Does this work on data derived from all microarray platforms?
A: We have tested and used CoNTExT on the following commonly used chips: Illumina HT-12, Illumina HumanRef-8, Affymetrix Exon 1.0 ST Array, Affymetrix Human Genome U133 Plus 2.0 Array, and Affymetrix Gene 1.0ST microarray.  All other microarray platforms have not been tested or validated.  That being said, if you want to, go for it!

Q: Does this work for RNA-seq data?
A: We have not tested or validated RNA-seq data in this framework.  We are planning on this in the future, though.

Q: I have only profiled neural progenitors, but not differentiated cells. Or, I only have profiled differentiated cells, but not progenitor cells. Can I still use the tool?
A: No. The website is set up to only study the transitions between progenitor to differentiated cells.  The transition mapping and module preservation tools require this transition.  The individual sample machine learning framework, CoNTExT, can predict individual samples but the website is not set up to run this piece of code alone.  Please contact the developers if you are interested in this.

Q: I ran my progenitors on one microarray batch and my differentiated cells on a separate microarray batch.  Will this interfere with my results?
A: No one can tell you if it will or will not influence your results, and if there is an influence you will not be able to correct for it.  As such, we strongly recommend that you not use data acquired where batch is perfectly correlated with condition.

Q: My data does not match well by transition mapping, how should I interpret results of CoNTExT machine learning framework?
A: All samples, even if they are not brain, will match to some brain region and temporal identity.  You should use caution when interpreting any low matching samples.  For a quantification of how much to trust CoNTExT based on transition mapping, see Figure S4 from our paper.

Q: If I stare deeply into these pictures, sometimes I see the eye of Sauron. Should I be worried?
A: This probably means your data is matching well. Fear not, child. Though rings should not be worn while interpreting these results, just in case.

Q: After reading all these answers, I still don’t know why it’s not working. What should I do?
A: Email the developers, and they will do their best to help you.