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Brandon Lind, Ph.D. - Integrative Life Sciences

interests - forest genomics • local adaptation • quantitative traits • population genetics • python

Hello, World! 👋 I'm currently a Research Fellow at Northeastern University with Katie Lotterhos using simulated data to assess machine learning methods for ranking population risk to climate change. I was formerly at the University of British Columbia with Sally Aitken and Sam Yeaman working on the CoAdapTree project to assist four ecologically and economically important Canadian conifer species adapt in the face of changing climates.

I've created several custom python functions for everyday use - eg using engines to parallelize reading in of large dataframes, submit/query/update slurm jobs and slurm queue, creating basic maps, and more - check out my repo here

Contact

✉️ [email protected]
🐦 @iowensis
🎓 google scholar
🔬 research page
🔗 LinkedIn

Brandon Lind's Projects

baypass_pipeline icon baypass_pipeline

Efficiently run baypass jobs on compute canada servers by handling job number limitations with an artificial queue

burt icon burt

code related to finding ancestral variation for fire adaptation in southeastern pines

cmh_test icon cmh_test

This code takes output from the VarScan pipeline and calculates Cochran-Mantel-Haenszel chi-squared tests on stratified contingency tables of read counts standardized by population ploidy.

out_of_the_woods icon out_of_the_woods

scripts for: Lind BM et al. (2018) The genomics of local adaptation in trees: Are we out of the woods yet? Tree Genetics & Genomes 14: 29. https://doi.org/10.1101/203307

pypoolation icon pypoolation

python scripts for population genetic statistics for data coming out of the poolseq pipeline

relernn icon relernn

Recombination Landscape Estimation using Recurrent Neural Networks

stdpopsim icon stdpopsim

A library of standard population genetic models

teakettle icon teakettle

scripts for: Lind BM et al. (2018) Effect of fire and thinning on fine-scale genetic structure and gene flow in fire-suppressed populations of sugar pine (Pinus lambertiana Douglas). Forest Ecology & Management 447:115-129. https://doi.org/10.1016/j.foreco.2019.04.033

varscan_pipeline icon varscan_pipeline

Pipeline for CoAdapTree to autonomously process raw fastq files through SNP calling with VarScan and subsequent filtering following bioinformatic best practices.

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