Reducing bias and variance for CTF estimation in single particle cryo-EM

Ayelet Heimowitz, Joakim Andén, Amit Singer

Research output: Contribution to journalArticlepeer-review

Abstract

When using an electron microscope for imaging of particles embedded in vitreous ice, the recorded image, or micrograph, is a significantly degraded version of the tomographic projection of the sample. Apart from noise, the image is affected by the optical configuration of the microscope. This transformation is typically modeled as a convolution with a point spread function. The Fourier transform of this function, known as the contrast transfer function (CTF), is oscillatory, attenuating and amplifying different frequency bands, and sometimes flipping their signs. High-resolution reconstruction requires this CTF to be accounted for, but as its form depends on experimental parameters, it must first be estimated from the micrograph. We present a new method for CTF estimation based on multitaper techniques that reduce bias and variance in the estimate. We also use known properties of the CTF and the background power spectrum to further reduce the variance through background subtraction and steerable basis projection. We show that the resulting power spectrum estimates better capture the zero-crossings of the CTF and yield accurate CTF estimates on several experimental micrographs.

Original languageEnglish (US)
Article number112950
JournalUltramicroscopy
Volume212
DOIs
StatePublished - May 2020

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Atomic and Molecular Physics, and Optics
  • Instrumentation

Keywords

  • Contrast transfer function
  • Cryo-electron microscopy
  • Linear programming
  • Multitaper estimator
  • Spectral estimation
  • Steerable basis expansion

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