Imaging Genomics

Imaging Genomics group: A platform to gain and share knowledge on imaging genomic analysis, to facilitate brainstorming that inspires new perspectives and spurs new ideas, and to promote collaborative efforts in addressing the challenges faced by the community.

Imaging Genomics Discussion Group Resources

• Regulatory landscape in brain development and disease (Dec 3, 2020)
• Cell-type-specific resolution epigenetics (Feb 25, 2021)

List of Resources

Below are links to helpful articles related to genetics, ENIGMA projects, new techniques in imaging genomics, and other related topics.

Useful tools

1. Gnomad browser: https://gnomad.broadinstitute.org/
2. Allen brain map:
   • https://portal.brain-map.org/
   • https://human.brain-map.org/ish/search/?page_num=0&page_size=400&no_paging=false&exact_match=false&search_term=*&search_type=gene
   • https://www.brainspan.org/ish?_ga=2.226890843.795051143.1593700341-2067836505.1593700341
   • http://casestudies.brain-map.org/ggb
3. USCS genome browser guide: https://genome.ucsc.edu/goldenPath/help/hgTracksHelp.html
4. Michigan imputation server: https://imputationserver.sph.umich.edu/index.html#!
5. PRSice for computing polygenic risk score: https://www.prsice.info/

A. Biostatistics:

1. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3469943/
2. https://www.semanticscholar.org/paper/Biostatistics-101%3A-data-presentation.-Chan/11e92bea7d503eeeac6e8e89d27fc13c840e43ff#extracted
3. http://cures.cardiff.ac.uk/files/2014/10/NSAMR-Statistics-Guide.pdf
4. https://johnjhaddad.weebly.com/uploads/2/5/2/0/2520519/medical_statistics_from_a_to_z.pdf (‘dictionary’)

B. Genetic Epidemiology

1. http://www.thelancet.com/series/genetic-epidemiology (start here!)
2. http://www.nature.com/nrg/journal/v15/n11/full/nrg3786.html
3. http://www.dorak.info/epi/genetepi.html (fundamentals)
4. http://www.math.vu.nl/sto/onderwijs/statisticalgenetics/dictaat20102011.pdf (basic)

C. Genetic Epidemiology of Psychiatric diseases

1. http://bmjopen.bmj.com/content/3/12/e004035
2. https://www.nature.com/ng/journal/v47/n7/full/ng.3285.html
3. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3800159/
4. https://www.slideshare.net/vavaponnu/sherlyns-genetic-epidemiology (slide show)

Additional Background Articles:

1. Bush WS, Moore JH (2012) Chapter 11: Genome-Wide Association Studies. PLoS Comput Biol 8(12): e1002822. https://doi.org/10.1371/journal.pcbi.1002822

2. Geschwind DH, Rakic P. Cortical evolution: judge the brain by its cover. Neuron. 2013;80(3):633-647. doi:10.1016/j.neuron.2013.10.045

3. Golov AK, Kondratyev NV, Kostyuk GP, Golimbet AVE. Novel Approaches for Identifying the Molecular Background of Schizophrenia. Cells. 2020;9(1):246. Published 2020 Jan 18. doi:10.3390/cells9010246

4. Hirschhorn, J., Daly, M. Genome-wide association studies for common diseases and complex traits. Nat Rev Genet 6, 95–108 (2005). https://doi.org/10.1038/nrg1521

5. Rakic P. Radial unit hypothesis of neocortical expansion. Novartis Found Symp. 2000;228:30-52. doi:10.1002/0470846631.ch3

6. Salzberg, S.L. Next-generation genome annotation: we still struggle to get it right. Genome Biol 20, 92 (2019). https://doi.org/10.1186/s13059-019-1715-2

7. Yandell, M., Ence, D. A beginner's guide to eukaryotic genome annotation. Nat Rev Genet 13, 329–342 (2012). https://doi.org/10.1038/nrg3174

8. Reay WR, Cairns MJ. Pairwise common variant meta-analyses of schizophrenia with other psychiatric disorders reveals shared and distinct gene and gene-set associations. Transl Psychiatry. 2020;10(1):134. Published 2020 May 12. doi:10.1038/s41398-020-0817-7

9. Price AJ, Jaffe AE, Weinberger DR. Cortical cellular diversity and development in schizophrenia [published online ahead of print, 2020 May 13]. Mol Psychiatry. 2020;10.1038/s41380-020-0775-8. doi:10.1038/s41380-020-0775-8

10. Amanda Rodrigue’s multivariate analysis paper: Rodrigue AL, Alexander-Bloch AF, Knowles EEM, et al. Genetic Contributions to Multivariate Data-Driven Brain Networks Constructed via Source-Based Morphometry [published online ahead of print, 2020 Apr 21]. Cereb Cortex. 2020;bhaa082. doi:10.1093/cercor/bhaa082

11. Rodrigue AL, McDowell JE, Tandon N, et al. Multivariate Relationships Between Cognition and Brain Anatomy Across the Psychosis Spectrum. Biol Psychiatry Cogn Neurosci Neuroimaging. 2018;3(12):992-1002. doi:10.1016/j.bpsc.2018.03.012

12. H-MAGMA: incorporate Hi-C data into MAGMA to infer target genes of GWAS results

    a. https://www.nature.com/articles/s41593-020-0603-0

13. FUMA: analyze cell specificity of GWAS results

    a. https://www.nature.com/articles/s41467-019-11181-1

ENIGMA based papers:

Virtual Histology: https://jamanetwork.com/journals/jamapsychiatry/article-abstract/2769908?casa_token=mTbNEr4_AzoAAAAA:DVsejZ8VczKo9gAosPu9AnEVmSbdgGvlv6mlUy9kALJ3ctC32HcWumlHDf1BwnV7uvex1XYhmEA

ENIGMA protocol: http://enigma.ini.usc.edu/protocols/genetics-protocols/

Genomics:

Genome Wide Risk of ADHD:

https://www.nature.com/articles/s41588-018-0269-7?fbclid=IwAR1C92BHM9skUkb46bIAxEqOl8IiY0VjNtkaept-uiHqg_hSPOgdjFZO9ok

https://www.bbrfoundation.org/event/genomics-across-diagnostic-boundaries-improve-precision-medicine-psychiatry

Group Leader