ios好用的第三方推特

Rapid multiple hypothesis testing correction (SLIDE) and power estimation (SLIP)

SLIDE: SLIDE (Sliding-window method for Locally Inter-correlated markers with asymptotic Distribution Errors corrected) is a multivariate normal distribution (MVN)-based multiple hypothesis testing correction method. SLIDE shows a near identical accuracy to the gold standard, the permutation test, and is much faster.

飞兔加速器官网: SLIP (Sliding-window method for Locally Inter-correlated markers for Power estimation) is a multivariate normal distribution (MVN)-based power estimation method. SLIP shows a near identical accuracy to the standard simulation procedure for power, and is much faster.

ios好用的第三方推特

SLIDE (Linux compatible, 32 bit) slide.1.0.4.tar.gz

SLIDE (Linux compatible, Intel64) slide.1.0.4.intel64.tar.gz

SLIDE (Mac OS, 32 bit) slide.1.0.4 (Mac OS, 32bit)

SLIDE (Mac OS, Intel64) slide.1.0.4 (Mac OS, 64bit)

SLIP (Linux compatible, 32 bit) slip.1.0.1.tar.gz

ios好用的第三方推特

v1.0.4 (2010-06-11) Mac OS version added
v1.0.4 (2009-10-29) bug in using option -QG is now fixed (Thanks to Dr. Sungeun Kim)
v1.0.3 (2009-09-16) Intel64 compiled version is now available for dealing with large file (>2Gb) (Thanks to Dr. Roman Pahl)
v1.0.2 (2009-05-21) bug in format converter fixed (Thanks to Dr. Lisa Martin for reporting the bug.)
v1.0.1 (2009-03-16) format converter PED->SLIDE included
v1.0.0 (2009-01-28) released

ios好用的第三方推特

v1.0.1 (2009-03-11) format converter SLIP->SLIDE included for estimating per-marker threshold
v1.0.0 (2009-03-10) released

ios好用的第三方推特

Buhm Han, Hyun Min Kang, and Eleazar Eskin (2009) Rapid and accurate multiple testing correction and power estimation for millions of correlated markers. PLoS Genet 5(4): e1000456. doi:10.1371/journal.pgen.1000456

ios好用的第三方推特

小白兔加速器 - buhan (AT) cs-ucsd-edu
Eleazar Eskin - eeskin (AT) cs-ucla-edu (Please replace dashes ‘-’ with dots ‘.’)

ios好用的第三方推特

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