Iterative stable alignment and classification (ISAC) is an approach that performs multiple rounds of classification and alignment to find reproducible and stable class averages. ISAC is released as a part of EMAN2/Sparx and SPHIRE.
Usage: ISAC can be used for any single particle sample, but ISAC is particularly powerful in classifying structural heterogeneity into homogenous subsets. For example, here are ISAC averages for insulin-receptor nanodisc complexes (Gutmann et al. 2018):
For general information on job submission, please see here.
Input particle stack format:
RELION-extracted particle stacks. Click here to learn what this means. During processing, COSMIC2 will convert the RELION stack to EMAN2/Sparx/SPHIRE database files.
Required input parameters:
- Particle radius, in pixels: Indicate particle radius for the uploaded stack.
- Images per group: ISAC will divide your dataset into groups of this many particles to find reproducible class averages. The recommended starting point is 200 particles per class for cryoEM data.
- Minimum number of images per group: Smallest number of particles considered for a group to be averaged. Typically 60% of images per group.
- Number of reference-free iterations: (Default=30) Number of ISAC iterations to run.
- Do CTF correction: Check box to do phase flipping of averages. Note that this CTF correction is different from default CTF correction in RELION. ISAC uses phase flipping which is squaring Fourier space to make all values positive, whereas RELION (by default) will perform amplitude CTF correction, which is dividing each class average or 3D reconstruction by the sum of CTF values.
“Iterative stable alignment and clustering of 2D transmission electron microscope images.” Yang, Z., Fang, J., Chittuluru, J., Asturias, F. J. and Penczek, P. A. Structure. (2012) 20(2):237-47. Link