![]() By 1970, the family had grown to include the Charger Daytona and the Dodge Challenger, and when the final year of the Scat Pack came to pass, the Dodge Demon 340 was also included. The Scat Pack logo was a variation on the drag-racing Super Bee found on, well, the Dodge Super Bee, and collectively the group of cars was referred to as "the hive." The marketing team went on the warpath, blanketing dealerships, magazines, and television with references to Scat City and the full line-up of Scat Pack cars. For the money, members received a monthly newsletter, a quarterly magazine, a wallet card declaring their loyalty, a bumper sticker, a jacket patch, and a racing guide. It was a play on words - the Rat Pack had been Sinatra's gang of Hollywood pals that became legendary for their partying and the pictures they made together - and as such Dodge also created an actual Scat Pack Club that both car owners and Mopar fans could join for the very affordable price of $3. The problem was put to the talented team at the Ross Roy Ad Agency, which came up with the idea of the "Scat Pack" designation that would encompass all of these cars. What was missing, however was a way to unify each of these uniquely named models under a single, world-beating banner - an issue that would only get worse with the introduction of the Dodge Super Bee mid-year. A 340-cubic-inch Dart Swinger was also available, and of course 426 Hemi power was also in the cards for all three models. ![]() By the time 1968 rolled around, Dodge was in the catbird seat with its line-up of fierce street machines, including the Dodge Coronet R/T, the Dodge Charger R/T, and the Dodge Dart GTS, each of which could be ordered with an (underrated) 375-horsepower, 440-cubic-inch V8 under the hood. You need PCs, outcome phenotypes and all eigenvalues to run EigenCorr.The late '60s represented the fiercest period of competition between the Big Three (and to a lesser extent, AMC) for the attentions of speed-thirsty American buyers. EigenCorr: EigenCorr is an R-package to compute p-values of principal components (PCs) based on EigenCorr1, EigenCorr2 and Tracy-Widom methods. We have recently extended it to gene-based rare-variant test (Transmeta-rare). The packages can be downloaded from the following github. This is an early version, and we will keep updating it. TransMeta & TransMetaRare : TransMeta is an R-package to compute single SNP p-values of trans-ethnic meta-analysis using a kernel-based random effect model. JointScoreTest: JointScoreTest is an R-package to perform a joint test of fixed and random effects in the Generalized linear mixed model framework.ĭSVA: dSVA is an R-package to identify hidden factors in high-dimensional biomedical data. The methods implemented in the package ( FastSPA ) can accurately calculate p-values even when the case-control ratio is extremely unbalanced. SPAtest: SPAtest is an R-package to perform score test for associations between genetic variants and binary traits using saddlepoint approximation. IECAT : iECAT is an R-package to test for single variant and gene/region-based associations using external control samples. Please install it from Github asĭevtools::install_github("leeshawn/MetaSKAT") It can carry out a meta-analysis of SKAT, SKAT-O and burden tests with individual-level genotype data or gene-level summary statistics.ĭownload (Github): link - Currently unavailable on CRAN. MetaSKAT: MetaSKAT is an R package for gene-based meta-analysis across studies. It also has functions for sample size and power calculations. For binary traits, it can calculate p-values using resampling and asymptotic based adjustment methods. It can carry out burden test, SKAT, SKAT-O, and combined test of common and rare variants with adjusting for covariates and kinship. SKAT: SKAT is an R-package for rare variant association analysis. ~400,000 samples in UKBiobank) and produce accurate p-values by using saddlepoint approximation.įor the UKBiobank analysis results, see Resources page It can analyze very large sample data (ex. SAIGE: SAIGE is an R-package for testing for associations between genetic variants and binary phenotypes with adjusting for sample relatedness and case-control imbalance.
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