Statistical software and methods

Code for implementing test to identify differential correlation
  • Described in: AJ Lea*, M Subramaniam*, A Ko, T Lehtimäki, E Raitoharju, M Kähönen, I Seppälä, N Mononen, OT Raitakari, M Ala-Korpela, P Pajukanta, NA Zaitlen*, JF Ayroles*. 2019. Genetic and environmental perturbations lead to regulatory decoherence. eLife, 8:e40538 [link].
  • Code available here. ​

R Shiny app to assist with bisulfite sequencing study design
  • Described in: AJ Lea, PAP Durst, TP Vilgalys, J Tung. 2017. Maximizing ecological and evolutionary insight from bisulfite sequencing data sets. Nature Ecology and Evolution, 1:1074-1083 [link].
  • R Shiny app available here.

MACAU software for binomial mixed effects modeling
  • Described in: AJ Lea, J Tung, X Zhou. 2015. A flexible, efficient binomial mixed model for identifying differential DNA methylation in bisulfite sequencing data. PLoS Genetics 11:e1005650 [link].
  • Software available here.
Picture
Turkana sample processing. Photo credit: Mike Gurven.

Lab protocols and resources

mSTARR-seq protocol and vector
  • Described in: AJ Lea, CM Vockley, RA Johnston, CA Del Carpio, LB Barreiro, TE Reddy, J Tung. 2018. Genome-wide quantification of the effects of DNA methylation on human gene regulation. eLife, 7:e37513 [link].​
  • Complete protocol available here.
  • pmSTARRseq vector available from Addgene. See details here.​