sashagusev

An evaluation by Claude (Sonnet) of randomly sampled scientific abstracts

Prompt:

You are an expert statistical geneticist. submissions.csv contains scientific abstract submissions to a genetics conference. Review each of the abstracts and identify any topic trends related to author gender or race ethnicity and summarize your findings into an evaluation.

---

I've read all 982 abstracts. The Bash tool is blocked for write operations in the current permission mode, and I don't have a separate Write tool available. I'll present the full evaluation here so you can save it to evaluation.md, or you can enable file write permissions and I'll write it for you.

sashagusev

set.seed(42)
options(digits=3)

# --- Parameters
# sibling pairs
N = 100e3
# unadmixed individuals (for population estimate)
N_unadmixed = 10e3
# number of variants
M = 100

sashagusev

library("RColorBrewer")

# ---
# Parameters
# ---
# Samples
N = 2e3
# Epistatic heritability :
hsq_epistatic = 0.5
# Allele frequencies to use

sashagusev

clr = c("#d53e4f","#fc8d59","#99d594")
n=500e3
hsq = 0.5
seeds = 10

par(mfrow=c(1,4))
for ( maf in c(0,0.05,0.2,0.5) ) {
  plot(0,0,xaxt="n",las=1,type="n",pch=19,ylab="Phenotype",xlab="Genotype",ylim=c(-1,30),xlim=c(0,2),bty="n",main="")
  axis(side=1,at=c(0,1,2),labels = c("AA","Aa","aa"))
  hsq_add = rep(NA,seeds)

sashagusev

library(survival)

# ---
# Parameters
# ---
# number of individuals
n = 50e3
# desired hazard ratio
HR = 1.64
beta = log(HR)

sashagusev

# Fixed parameters
N = 10e6
AM_cor = 0.50

for ( Cultural_cor in c(sqrt(0.15),0.51) ) {
  cat("\nSimulating cultural transmission of" , Cultural_cor , '\n' )

  # Simulate two parental traits
  y_mother = rnorm(N,0,1)
  y_father = rnorm(N,0,1)

sashagusev

set.seed(42)

### --- REML
# Original code:
# https://github.com/sashagusev/SKK-REML-sim/blob/master/func_reml.R

library('msm')

# Utility function for calculating log of determinant
`logdet` <-

sashagusev

# Simulations and visualization of a heritable liability threshold model across generations and in families
# ---
# Liability functions (from Baselmans et al.)
# See: https://github.com/BartBaselmans/CHARRGe

risk_from_liability = function( prev , h2 ) {
  # Threshold
  Tx = -qnorm(prev,0,1)
  z = dnorm(Tx)
  i = z/prev

sashagusev

set.seed(1)

# Library for GLMM computations
library(PQLseq2)
# Library for mixed model / Wald test
library("GMMAT")

# convenience function to suppress prints
quiet <- function(x) { 
  sink(tempfile()) 

sashagusev

set.seed(42)

# Library for GLMM computations
library(PQLseq2)
# Library for mixed model / Wald test
library("GMMAT")

# convenience function to suppress prints
quiet <- function(x) { 
  sink(tempfile())