3.5 Quantification
1. For static and diffusing RNA particles:
(a) Organize the tracking data as spreadsheets in the .xlsx
format for all the cells (including the tracking data for
the controls) in a single folder.
(b) In Matlab, add the Diff2fit folder containing the scripts
and the folder containing the tracking data to the path.
(c) Execute Diff2fit by calling the “Diff2fit.m” script and
choose the folder containing the tracking data.
(d) This script quantifies the tracking data as:
l
Diffusion coefficients based on either single- or
two-population fit along with percentage of the particles exhibiting the corresponding movement, r
2 value,
and goodness of fit for each cell. The abovementioned
values are stored in the file “tracking filename _diffusion_coefficients_fit_results.txt” and the plot visualizing the single- and two-population fit is stored as
“tracking filename_fit.tif” (Figs. 2a, b).
l
Instantaneous diffusion coefficients for each displacement window (three displacements over four frames)
are calculated and stored in the file “tracking filename
_IDC_all1.txt.” The plot visualizing the instantaneous
diffusion coefficients is stored as “tracking filenameInstantaneous_Diffusion_Coefficients.tif.”
(e) Use the diffusion coefficients, percentage of the particles
exhibiting the corresponding movement, or instantaneous diffusion coefficients elucidated from multiple
cells to quantify the type of movement exhibited by the
corresponding RNA (Figs. 2c, d).
2. For RNA particles undergoing directed movement:
(a) Organize the tracking data as spreadsheets in the .xlsx
format for each cell in a way that each track is a separate
sheet (see test.xlsx file inside the HMM-analysis folder
from https://data.fmi.ch/PublicationSupplementRepo/
?group¼gchao).
(b) Download the HMM-Bayes package from http://hmmbayes.org/ and add the following files available from the
Chao lab (see Subheading 2.3)
l
hmm_skeleton_MultiTrajip_SingleTrajProcess.m
l
hmm_skeleton_singletraj.m
l
XlsReadTraj.m
to the Democode folder inside the HMM-Bayes folder.
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Varun Bhaskar et al.
1. For static and diffusing RNA particles:
(a) Organize the tracking data as spreadsheets in the .xlsx
format for all the cells (including the tracking data for
the controls) in a single folder.
(b) In Matlab, add the Diff2fit folder containing the scripts
and the folder containing the tracking data to the path.
(c) Execute Diff2fit by calling the “Diff2fit.m” script and
choose the folder containing the tracking data.
(d) This script quantifies the tracking data as:
l
Diffusion coefficients based on either single- or
two-population fit along with percentage of the particles exhibiting the corresponding movement, r
2 value,
and goodness of fit for each cell. The abovementioned
values are stored in the file “tracking filename _diffusion_coefficients_fit_results.txt” and the plot visualizing the single- and two-population fit is stored as
“tracking filename_fit.tif” (Figs. 2a, b).
l
Instantaneous diffusion coefficients for each displacement window (three displacements over four frames)
are calculated and stored in the file “tracking filename
_IDC_all1.txt.” The plot visualizing the instantaneous
diffusion coefficients is stored as “tracking filenameInstantaneous_Diffusion_Coefficients.tif.”
(e) Use the diffusion coefficients, percentage of the particles
exhibiting the corresponding movement, or instantaneous diffusion coefficients elucidated from multiple
cells to quantify the type of movement exhibited by the
corresponding RNA (Figs. 2c, d).
2. For RNA particles undergoing directed movement:
(a) Organize the tracking data as spreadsheets in the .xlsx
format for each cell in a way that each track is a separate
sheet (see test.xlsx file inside the HMM-analysis folder
from https://data.fmi.ch/PublicationSupplementRepo/
?group¼gchao).
(b) Download the HMM-Bayes package from http://hmmbayes.org/ and add the following files available from the
Chao lab (see Subheading 2.3)
l
hmm_skeleton_MultiTrajip_SingleTrajProcess.m
l
hmm_skeleton_singletraj.m
l
XlsReadTraj.m
to the Democode folder inside the HMM-Bayes folder.
276
Varun Bhaskar et al.