NEWS

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sffdr 1.1.2 (2026-03-31)

• Added monotonicity option (running min or PAVA)
• Better handling of weights in kernel density estimation
• function docorrelate_informative to handle overlapping samples

sffdr 1.1.1

• Added a weights argument which allows users to input inverse LD scores and fit to all SNPs.

sffdr 1.1.0 (2026-02-11)

Major Changes

• Now uses fastglm exclusively for significantly faster GLM fitting.

• Simplified pi0_model() function:

  • Removed knots parameter. Knots are now selected adaptively based on FDR thresholds and signal strength.
  • Added n_knots parameter (default: 5) for target knot count.
  • Added min_snps_per_knot parameter (default: 100) to ensure stable spline fitting.
  • Added max_knots parameter (default: 5) to prevent overfitting.

• Removed indep_snps functionality from sffdr(). Kernel density estimation now always uses all SNPs with appropriate nn smoothing to handle LD.

• Improved speed of locfit by subsampling the null region of the distribution (accounted for using the weights argument).

• Added 98 unit tests covering kernelEstimator, pi0_model, fpi0est, sffdr, and fpvalues.

sffdr 1.0.0 (2024-12-02)

• Initial CRAN submission.