QUIN-XL's Tutorial

QUIN-XL is available for download here.

The software requires version 4.8 or higher of the .NET framework, which can be downloaded here, if it is not already installed.

To start your analysis, you can go to the menu “File” and click on the “New” button.

Then, select the main directory with all your SIM-XL output files and the experiment *.raw files. This will be a recursive search of all the folders (it will look within subfolders) so just select the root directory of the experiment. If QUIN does not find any *.raw files in the directory, it will give a warning and will not extract XICs.

Once the folder has been selected, QUIN will list all the found SIM-XL output files in the following screen:

Here you can choose which files will be part of your analysis by checking/unchecking them in the “File Selection” column. This is also the step where you should give an ID for your experiments, as this will be how they will be referred to from now on. You can group multiple files as the same condition by giving them the same ID (note, they will be analysed as one if you do that). If you hover the mouse in one of the files, you can see the directory it came from. If there is a file missing here, you can add it manually by clicking “Include New File”.

QUIN-XL will then proceed to read the SIM-XL files and extract quantification values for your cross-links. This step can take a while depending on how many .raw files you have to analyse and their sizes. You can see the progress in the black screen if you want to:

Once all the files have been loaded, QUIN will ask if you want to manually set the chromatographic range to use as normalization factor for the XICs. If you select "No", the total ion current (TIC) will be used as normalization factor.

As soon as it loads, you can save a project file with all the XICs by clicking on the button “Save”. The format of the file is *.qnr.

You can then click on the menu “Filters” and filter your cross-links according to their scores from SIM-XL, the link type and the cross-linker used; you can also see the XIC values normalized by the TIC and group the cross-links according to the residue site instead of seeing them as different species. Once you have chosen all your filters, just click on “Apply”:

In the main XL table, you can double click on the peptide cell, or on the cell of one of the XIC values. If you double click on the peptide, a window containing the information of all the different identifications for it (different charges, isotopes, files…) in every biological condition will open:

If you double click on one of the XIC values (in the XL table in the main screen), the “XIC Viewer” will pop up, showing all the XIC curves for XL in that particular biological condition. If you open the “XICs” menu on the left side of the screen, you can see more information on each of the curves. If you right click on the plot, the options for aligning, smoothing or the saving the XICs will appear:

Here you can choose to either let the algorithm decide the optimal number of clusters or you can manually set by choosing one of the options on “Cluster Determination”. Let the option “Unit Vector”, on the “Normalization” area, checked, as otherwise you will cluster the XLs according to their XIC intensities and not quantitative profile. Click on “Run”.

In this example it shows that the algorithm tried to fit the data in up to 7 clusters and determined that the best number of clusters was 6. This is some useful information in case you want to try clustering with a different number of pre-set groups, but otherwise you can just close this window.

You can see all the clusters represented as 2D plots here, where each line is a cross-link assigned to that specific cluster. You can see a table with all the XLs and their respective clusters by clicking on the “Crosslinks” menu on the left:

With the clusters at hand, there are a few things you can do. To see a specific XL represented in its cluster, double click on it at the table. QUIN will focus on the cluster and highlight the XL:

If you think a XL was assigned to a wrong cluster and fits better in another, you can manually change it by writing the number of another cluster in the “Cluster Number” column. A window will open up asking for you to write the new number; then, just press the enter key.

If you did not like a cluster and think that there are different profiles represented there, you can recluster it by right clicking on the plot and choosing into how many groups you would like to further split the cluster and clicking on “Recluster with k=…”:

The following window will open up; here you can keep reclustering until you think the fit is good or you can accept the new clusters.

Once you accept them, the new clusters will substitute the old one in the main screen.

You can also see the XLs in each cluster in the 2D Map of the protein by right clicking on the chosen plot and clicking on “Show 2D Map”:

If you have a 3D model of your protein and wish to see the XLs represented there, you can export the cross-links from each cluster as a PyMOL script by clicking on the “Save .pml Files” button. It will save one *.pml script for each of the clusters.