SES Text Mining Algorithms for Electronic Health Records
From the Crawford Lab: We have developed a set of text-mining algorithms to extract education and occupation, both important variables that describe socioeconomic status (SES), from electronic health records. The development and evaluation of the algorithm is described in PMC5147499, and the exclusion, jobs, and prefix lists developed for this algorithm can be found here. Detailed usage of the package can be found on the github site.
Hi-MC: High-throughput Mitochondrial Haplogroup Classification
From the Crawford Lab: The Hi-MC package provides high-level mitochondrial haplogroups given standard PLINK .map and.ped files. Hi-MC is a cost-effective approach to characterize major haplogroups in large sample sizes similar to those described in PMC4113317. Detailed usage of the package can be found on the github, the preprint, and the final publication in PeerJ.
COCOS: Codon Consequence Scanner
From the Bush Lab and Haines Lab, Mariusz Butkiewicz has developed COCOS, a plugin for the Ensembl Variant Effect Predictor (VEP) plugin for annotating reading frame changes. The plugin captures Amino Acid sequence alterations stemming from variants that produce an altered reading frame, e.g. stop-lost variants and small genetic Insertion and Deletions (InDels). The GitHub repository for COCOS can be found here.
Interaction eQTL Analysis
From the Bush Lab: This archive contains scripts and data for performing an analysis looking for cis-interacting variants that influence gene expression. Our publication can be found here: http://www.cell.com/ajhg/fulltext/S0002-9297(16)30323-8