Revision 96e51a937818e80436dc53d73c7f33f949de7963 authored by Nicola Galvanetto on 25 May 2022, 08:03:00 UTC, committed by GitHub on 25 May 2022, 08:03:00 UTC
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README.md
# NativeSMFS (please download the release)
**SMFS data source files (non empty spectra)**
File format: row text files where row 1 is the force signal of the 1st trace, row 2 is the tip-sample separation of the 1st trace, etc.
(described in details here https://doi.org/10.1016/j.bpj.2018.02.004).
Files can be opened for visualization with our open source software Fodis https://github.com/galvanetto/Fodis
**Clustering code [SMFS_clustering-master.zip]**
_Please note that the clustering does not include the "Block 5: Refinement and merging" in the methods section that is performed Block 5: Refinement and merging with our software Fodis_
We provide the source code of our method for clustering heterogeneous AFM-SMFS data from pulling experiments performed on proteins together with the files neccesary to run a toy example.
The files included in this repository are:
cluster_traces.cpp - the source code
cluster_tracesv23_3_20-win64_static_O2.exe - a static executable for Windows
input.txt - contains the input parameters of the algorithm
Dataset_Mixed.txt - test dataset containing four groups of traces corresponding to the unfolding of four different proteins
reference_output.txt - the correct output results for Dataset Mixed
The code has been tested with an Intel compiler: intel/18.0.3 with the following command:
icc -std=c++0x -O3 cluster_traces.cpp -fopenmp -o cluster_traces.x
To run the code:
./cluster_traces.x input.txt > output.txt
The code is also compatible with the gnu compiler.
The generated output file contains a list of the used parameter values followed by the actual results divided in columns containing the following information:
col1="tr ";
col2=Trace number;
col3=Length;
col4=Quality score;
col5=Number of peaks;
col6=Cluster number;
col7=Cluster number without filters;
col8=Distance from the cluster center;
In the very end of the output file, information about the clusters is printed. Each cluster is descirbed in terms of cluster center, size and members (cluster core traces).
The values of the input parameters in input.txt are the default ones.
Results
Dataset Mixed contains 4 groups of traces corresponding to the unfolding of 4 different proteins:
Group 1 - unfolding of the CNGA1 channel (Maity et al, Nat Commun, 2015)
Group 2 - unfolding of a tandem globular polyprotein (Alpha3D + 4xNUG2) (Heenan and Perkins, Biophys J, 2018)
Group 3 and Group 4 correspond to the unfolding of two unidentified proteins from AFM-SMFS experiments in the plasma membrane of the rod outer segment.
The total number of clusters you should obtain for Dataset Mixed is 5.
The traces from the 4 groups in the dataset are distributed in our clusters as follows:
cluster 1 - contains the traces from Group 2
cluster 2 - contains the traces from Group 1
cluster 3, 4, 5 - contain the traces from Group 3
The traces from group 4 do not belong to the core of any of the five clusters indicating that they are not similar enough according to the criteria implemented in the code.
For more information on the density peak clustering: https://www.science.org/doi/abs/10.1126/science.1242072
For more information on the density peak clustering applied to AFM-SMFS: https://doi.org/10.1093/bioinformatics/btaa626
**Protein Candidates assignment [Mass.Spec.table.Bayesian.analysis.rar]**
Matlab code that follows the Bayesian method described in Methods
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