Student or educator? Sign up with your school email and get 6 months of Pro free.
CoChat
Sign Up
Cited by 865

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

cisTEM, user-friendly software for single-particle image processing

Open access
Grant, Timothy, Rohou, Alexis, Grigorieff, Nikolaus·2018·eLife
DOI 10.7554/elife.35383

Published version of a preprint

Open this paper in CoChat — free account

Abstract

We have developed new open-source software called cisTEM (computational imaging system for transmission electron microscopy) for the processing of data for high-resolution electron cryo-microscopy and single-particle averaging. cisTEM features a graphical user interface that is used to submit jobs, monitor their progress, and display results. It implements a full processing pipeline including movie processing, image defocus determination, automatic particle picking, 2D classification, ab-initio 3D map generation from random parameters, 3D classification, and high-resolution refinement and reconstruction. Some of these steps implement newly-developed algorithms; others were adapted from previously published algorithms. The software is optimized to enable processing of typical datasets (2000 micrographs, 200 k – 300 k particles) on a high-end, CPU-based workstation in half a day or less, comparable to GPU-accelerated processing. Jobs can also be scheduled on large computer clusters using flexible run profiles that can be adapted for most computing environments. cisTEM is available for download from cistem.org.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.7554/elife.35383

Cites

2 of 2 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 2 references

Research works printed but not linked: 53

  1. Abeyrathne, 2016, Ensemble cryo-EM uncovers inchworm-like translocation of a viral IRES through the ribosome, eLife, 5, e14874, 10.7554/eLife.14874 · DOI
  2. Bartesaghi, 2014, Structure of β-galactosidase at 3.2-Å resolution obtained by cryo-electron microscopy, PNAS, 111, 11709, 10.1073/pnas.1402809111 · DOI
  3. Bartesaghi, 2015, 2.2 A resolution cryo-EM structure of β-galactosidase in complex with a cell-permeant inhibitor, Science, 348, 1147, 10.1126/science.aab1576 · DOI · Paper page
  4. Chen, 2009, Molecular interactions in rotavirus assembly and uncoating seen by high-resolution cryo-EM, PNAS, 106, 10644, 10.1073/pnas.0904024106 · DOI
  5. Chen, 2013, High-resolution noise substitution to measure overfitting and validate resolution in 3D structure determination by single particle electron cryomicroscopy, Ultramicroscopy, 135, 24, 10.1016/j.ultramic.2013.06.004 · DOI · Paper page
  6. Cheng, 2015, A primer to single-particle cryo-electron microscopy, Cell, 161, 438, 10.1016/j.cell.2015.03.050 · DOI · Paper page
  7. Conesa Mingo, 2018, Scipion web tools: Easy to use cryo-EM image processing over the web, Protein Science, 27, 269, 10.1002/pro.3315 · DOI
  8. Crowther, 1996, MRC image processing programs, Journal of Structural Biology, 116, 9, 10.1006/jsbi.1996.0003 · DOI · Paper page
  9. Desfosses, 2014, SPRING - an image processing package for single-particle based helical reconstruction from electron cryomicrographs, Journal of Structural Biology, 185, 15, 10.1016/j.jsb.2013.11.003 · DOI
  10. Frank, 1996, SPIDER and WEB: processing and visualization of images in 3D electron microscopy and related fields, Journal of Structural Biology, 116, 190, 10.1006/jsbi.1996.0030 · DOI · Paper page
  11. Grant, 2015, Automatic estimation and correction of anisotropic magnification distortion in electron microscopes, Journal of Structural Biology, 192, 204, 10.1016/j.jsb.2015.08.006 · DOI
  12. Grant, 2015, Measuring the optimal exposure for single particle cryo-EM using a 2.6 Å reconstruction of rotavirus VP6, eLife, 4, e06980, 10.7554/eLife.06980 · DOI · Paper page
  13. Grigorieff, 2000, Resolution measurement in structures derived from single particles, Acta Crystallographica Section D Biological Crystallography, 56, 1270, 10.1107/S0907444900009549 · DOI
  14. Grigorieff, 2007, FREALIGN: high-resolution refinement of single particle structures, Journal of Structural Biology, 157, 117, 10.1016/j.jsb.2006.05.004 · DOI · Paper page
  15. Grigorieff, 2016, Frealign: An exploratory tool for single-particle Cryo-EM, Methods in enzymology, 579, 191, 10.1016/bs.mie.2016.04.013 · DOI
  16. Harauz, 1986, Exact filters for general geometry 3-dimensional reconstruction, Optik, 73, 146
  17. Henderson, 2013, Avoiding the pitfalls of single particle cryo-electron microscopy: Einstein from noise, PNAS, 110, 18037, 10.1073/pnas.1314449110 · DOI
  18. Hohn, 2007, SPARX, a new environment for Cryo-EM image processing, Journal of Structural Biology, 157, 47, 10.1016/j.jsb.2006.07.003 · DOI · Paper page
  19. Iudin, 2016, EMPIAR: a public archive for raw electron microscopy image data, Nature Methods, 13, 387, 10.1038/nmeth.3806 · DOI · Paper page
  20. Kimanius, 2016, Accelerated cryo-EM structure determination with parallelisation using GPUs in RELION-2, eLife, 5, e18722, 10.7554/eLife.18722 · DOI · Paper page
  21. Lander, 2009, Appion: an integrated, database-driven pipeline to facilitate EM image processing, Journal of Structural Biology, 166, 95, 10.1016/j.jsb.2009.01.002 · DOI · Paper page
  22. Loveland, 2017, Ensemble cryo-EM elucidates the mechanism of translation fidelity, Nature, 546, 113, 10.1038/nature22397 · DOI
  23. Lyumkis, 2013, Likelihood-based classification of cryo-EM images using FREALIGN, Journal of Structural Biology, 183, 377, 10.1016/j.jsb.2013.07.005 · DOI · Paper page
  24. Mastronarde, 2017, Automated tilt series alignment and tomographic reconstruction in IMOD, Journal of Structural Biology, 197, 102, 10.1016/j.jsb.2016.07.011 · DOI · Paper page
  25. Matthews, 1968, Solvent content of protein crystals, Journal of Molecular Biology, 33, 491, 10.1016/0022-2836(68)90205-2 · DOI · Paper page
  26. McDonough, 1995, Detection of Signals in Noise
  27. McMullan, 2016, Direct electron detectors, Methods in Enzymology, 579, 1, 10.1016/bs.mie.2016.05.056 · DOI
  28. McMullan, 2015, Thon rings from amorphous ice and implications of beam-induced Brownian motion in single particle electron cryo-microscopy, Ultramicroscopy, 158, 26, 10.1016/j.ultramic.2015.05.017 · DOI
  29. Mindell, 2003, Accurate determination of local defocus and specimen tilt in electron microscopy, Journal of Structural Biology, 142, 334, 10.1016/S1047-8477(03)00069-8 · DOI · Paper page
  30. Moriya, 2017, High-resolution single particle analysis from electron cryo-microscopy images using SPHIRE, Journal of Visualized Experiments, 10.3791/55448 · DOI
  31. Oldham, 2016, Structure of the transporter associated with antigen processing trapped by herpes simplex virus, eLife, 5, e21829, 10.7554/eLife.21829 · DOI
  32. Penczek, 2014, CTER-rapid estimation of CTF parameters with error assessment, Ultramicroscopy, 140, 9, 10.1016/j.ultramic.2014.01.009 · DOI
  33. Punjani, 2017, cryoSPARC: algorithms for rapid unsupervised cryo-EM structure determination, Nature Methods, 14, 290, 10.1038/nmeth.4169 · DOI · Paper page
  34. Reboul, 2018, Single-particle cryo-EM-Improved ab initio 3D reconstruction with SIMPLE/PRIME, Protein Science, 27, 51, 10.1002/pro.3266 · DOI
  35. Rohou, 2015, CTFFIND4: Fast and accurate defocus estimation from electron micrographs, Journal of Structural Biology, 192, 216, 10.1016/j.jsb.2015.08.008 · DOI · Paper page
  36. Roseman, 2004, FindEM--a fast, efficient program for automatic selection of particles from electron micrographs, Journal of Structural Biology, 145, 91, 10.1016/j.jsb.2003.11.007 · DOI
  37. Scheres, 2012, Prevention of overfitting in cryo-EM structure determination, Nature Methods, 9, 853, 10.1038/nmeth.2115 · DOI · Paper page
  38. Scheres, 2005, Maximum-likelihood multi-reference refinement for electron microscopy images, Journal of Molecular Biology, 348, 139, 10.1016/j.jmb.2005.02.031 · DOI · Paper page
  39. Scheres, 2015, Semi-automated selection of cryo-EM particles in RELION-1.3, Journal of Structural Biology, 189, 114, 10.1016/j.jsb.2014.11.010 · DOI · Paper page
  40. Sheth, 2015, Visualization and quality assessment of the contrast transfer function estimation, Journal of Structural Biology, 192, 222, 10.1016/j.jsb.2015.06.012 · DOI
  41. Sigworth, 2004, Classical detection theory and the cryo-EM particle selection problem, Journal of Structural Biology, 145, 111, 10.1016/j.jsb.2003.10.025 · DOI
  42. Sindelar, 2012, Optimal noise reduction in 3D reconstructions of single particles using a volume-normalized filter, Journal of Structural Biology, 180, 26, 10.1016/j.jsb.2012.05.005 · DOI
  43. Stewart, 2004, Noise bias in the refinement of structures derived from single particles, Ultramicroscopy, 102, 67, 10.1016/j.ultramic.2004.08.008 · DOI
  44. Subramaniam, 2016, Resolution advances in cryo-EM enable application to drug discovery, Current Opinion in Structural Biology, 41, 194, 10.1016/j.sbi.2016.07.009 · DOI
  45. Subramaniam, 2013, Structure of trimeric HIV-1 envelope glycoproteins, PNAS, 110, E4172, 10.1073/pnas.1313802110 · DOI
  46. Tang, 2007, EMAN2: an extensible image processing suite for electron microscopy, Journal of Structural Biology, 157, 38, 10.1016/j.jsb.2006.05.009 · DOI · Paper page
  47. Thon, 1966, Zur Defokussierungsabhängigkeit des Phasenkontrastes bei der elektronenmikroskopischen Abbildung, Zeitschrift für Naturforschung A, 21a, 476, 10.1515/zna-1966-0417 · DOI · Paper page
  48. van Heel, 1996, A new generation of the IMAGIC image processing system, Journal of Structural Biology, 116, 17, 10.1006/jsbi.1996.0004 · DOI · Paper page
  49. Van Heel, 1982, Detection of objects in quantum-noise-limited images, Ultramicroscopy, 7, 331, 10.1016/0304-3991(82)90258-3 · DOI
  50. van Heel, 2013, Finding trimeric HIV-1 envelope glycoproteins in random noise, PNAS, 110, E4175, 10.1073/pnas.1314353110 · DOI
  51. Voss, 2009, DoG Picker and TiltPicker: software tools to facilitate particle selection in single particle electron microscopy, Journal of Structural Biology, 166, 205, 10.1016/j.jsb.2009.01.004 · DOI · Paper page
  52. Zhang, 2016, Gctf: Real-time CTF determination and correction, Journal of Structural Biology, 193, 1, 10.1016/j.jsb.2015.11.003 · DOI
  53. Zhou, 2015, Structure and conformational states of the bovine mitochondrial ATP synthase by cryo-EM, eLife, 4, e10180, 10.7554/eLife.10180 · DOI · Paper page

Cited by

Metadata

Authors
Grant, T., Rohou, A., & Grigorieff, N.
Venue
eLife
Publisher
eLife Sciences Publications, Ltd
Published
2018-03-07
Volume
7
ISSN
2050-084X (ISSN-L)
DOI
10.7554/elife.35383
OpenAlex
W2791354025
Cited by
865
References
2
FWCI
52.04
Type
journal article
Language
en
Open access
gold
Licence
Funders
Howard Hughes Medical Institute

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.