Quantify resolution of a spatial proteomics experiment
QSep-class.RdThe QSep infrastructure provide a way to quantify the
resolution of a spatial proteomics experiment, i.e. to quantify how
well annotated sub-cellular clusters are separated from each other.
The QSep function calculates all between and within cluster
average distances. These distances are then divided column-wise by the
respective within cluster average distance. For example, for a dataset
with only 2 spatial clusters, we would obtain
| \(c_1\) | \(c_2\) | |
| \(c_1\) | \(d_11\) | \(d_12\) |
| \(c_2\) | \(d_21\) | \(d_22\) |
Normalised distance represent the ratio of between to within average distances, i.e. how much bigger the average distance between cluster \(c_i\) and \(c_j\) is compared to the average distance within cluster \(c_i\).
| \(c_1\) | \(c_2\) | |
| \(c_1\) | 1 | \(\frac{d_12}{d_22}\) |
| \(c_2\) | \(\frac{d_21}{d_11}\) | 1 |
Note that the normalised distance matrix is not symmetric anymore and the normalised distance ratios are proportional to the tightness of the reference cluster (along the columns).
Missing values only affect the fractions containing the NA when
the distance is computed (see the example below) and further used when
calculating mean distances. Few missing values are expected to have
negligible effect, but data with a high proportion of missing data
will will produce skewed distances. In QSep, we take a
conservative approach, using the data as provided by the user, and
expect that the data missingness is handled before proceeding with this
or any other analysis.
Objects from the Class
Objects can be created by calls using the constructor
QSep (see below).
Slots
x:Object of class
"matrix"containing the pairwise distance matrix, accessible withqseq(., norm = FALSE).xnorm:Object of class
"matrix"containing the normalised pairwise distance matrix, accessible withqsep(., norm = TRUE)orqsep(.).object:Object of class
"character"with the variable name ofMSnSetobject that was used to generate theQSepobject..__classVersion__:Object of class
"Versions"storing the class version of the object.
Extends
Class "Versioned", directly.
Methods and functions
- QSeq
signature(object = "MSnSet", fcol = "character"): constructor forQSepobjects. Thefcolargument defines the name of the feature variable that annotates the sub-cellular clusters. Non-marker proteins, that are marked as"unknown"are automatically removed prior to distance calculation.- qsep
signature{object = "QSep", norm = "logical"}: accessor for the normalised (whennormisTRUE, which is default) and raw (whennormisFALSE) pairwise distance matrices.- names
signature{object = "QSep"}: method to retrieve the names of the sub-celluar clusters originally defined inQSep'sfcolargument. A replacement methodnames(.) <-is also available.- summary
signature(object = "QSep", ..., verbose = "logical"): Invisible return all between cluster average distances and prints (whenverboseisTRUE, default) a summary of those.- levelPlot
signature(object = "QSep", norm = "logical", ...): plots an annotated heatmap of all normalised pairwise distances.norm(default isTRUE) defines whether normalised distances should be plotted. Additional arguments...are passed to thelevelplot.- plot
signature(object = "QSep", norm = "logical"...): produces a boxplot of all normalised pairwise distances. The red points represent the within average distance and black points between average distances.norm(default isTRUE) defines whether normalised distances should be plotted.
References
Assessing sub-cellular resolution in spatial proteomics experiments Laurent Gatto, Lisa M Breckels, Kathryn S Lilley bioRxiv 377630; doi: https://doi.org/10.1101/377630
Examples
## Test data from Christoforou et al. 2016
library("pRolocdata")
data(hyperLOPIT2015)
## Create the object and get a summary
hlq <- QSep(hyperLOPIT2015)
hlq
#> Object of class 'QSep'.
#> Data: hyperLOPIT2015
#> With 14 sub-cellular clusters.
summary(hlq)
#> Min. 1st Qu. Median Mean 3rd Qu. Max.
#> 0.9458 3.6189 4.9075 5.1172 6.5779 11.4970
## mean distance matrix
qsep(hlq, norm = FALSE)
#> Actin cytoskeleton
#> Actin cytoskeleton 0.1372312
#> Endoplasmic reticulum/Golgi apparatus 0.4690770
#> Mitochondrion 0.7536736
#> Extracellular matrix 0.4030989
#> Nucleus - Chromatin 0.8050828
#> Cytosol 0.5661409
#> Plasma membrane 0.2164849
#> Nucleus - Non-chromatin 0.7485378
#> Endosome 0.3955070
#> 60S Ribosome 0.4991471
#> Lysosome 0.3924089
#> Peroxisome 0.6861757
#> 40S Ribosome 0.5657759
#> Proteasome 0.6686545
#> Endoplasmic reticulum/Golgi apparatus
#> Actin cytoskeleton 0.4690770
#> Endoplasmic reticulum/Golgi apparatus 0.1315295
#> Mitochondrion 0.4961792
#> Extracellular matrix 0.1676919
#> Nucleus - Chromatin 0.6674186
#> Cytosol 0.8032906
#> Plasma membrane 0.4314796
#> Nucleus - Non-chromatin 0.7266946
#> Endosome 0.3298215
#> 60S Ribosome 0.4405743
#> Lysosome 0.3526493
#> Peroxisome 0.4138766
#> 40S Ribosome 0.6106558
#> Proteasome 0.8685051
#> Mitochondrion Extracellular matrix
#> Actin cytoskeleton 0.7536736 0.4030989
#> Endoplasmic reticulum/Golgi apparatus 0.4961792 0.1676919
#> Mitochondrion 0.1373421 0.5455040
#> Extracellular matrix 0.5455040 0.1053434
#> Nucleus - Chromatin 0.5424170 0.6929457
#> Cytosol 0.9585277 0.7755911
#> Plasma membrane 0.7462545 0.3556568
#> Nucleus - Non-chromatin 0.7106804 0.7267853
#> Endosome 0.7198622 0.2420721
#> 60S Ribosome 0.5168101 0.4430401
#> Lysosome 0.7471831 0.2483814
#> Peroxisome 0.2418018 0.4724549
#> 40S Ribosome 0.6601247 0.6060881
#> Proteasome 0.9917128 0.8497961
#> Nucleus - Chromatin Cytosol
#> Actin cytoskeleton 0.8050828 0.5661409
#> Endoplasmic reticulum/Golgi apparatus 0.6674186 0.8032906
#> Mitochondrion 0.5424170 0.9585277
#> Extracellular matrix 0.6929457 0.7755911
#> Nucleus - Chromatin 0.1463443 0.9484646
#> Cytosol 0.9484646 0.1414339
#> Plasma membrane 0.8341281 0.7443767
#> Nucleus - Non-chromatin 0.4154339 0.7974210
#> Endosome 0.8226749 0.7826439
#> 60S Ribosome 0.5602938 0.6438972
#> Lysosome 0.8451732 0.7995801
#> Peroxisome 0.5094584 0.9068309
#> 40S Ribosome 0.6518274 0.5331764
#> Proteasome 0.9718751 0.1600117
#> Plasma membrane Nucleus - Non-chromatin
#> Actin cytoskeleton 0.2164849 0.7485378
#> Endoplasmic reticulum/Golgi apparatus 0.4314796 0.7266946
#> Mitochondrion 0.7462545 0.7106804
#> Extracellular matrix 0.3556568 0.7267853
#> Nucleus - Chromatin 0.8341281 0.4154339
#> Cytosol 0.7443767 0.7974210
#> Plasma membrane 0.1148277 0.8199944
#> Nucleus - Non-chromatin 0.8199944 0.1783578
#> Endosome 0.3425939 0.8135370
#> 60S Ribosome 0.5616175 0.4546378
#> Lysosome 0.3274954 0.8365127
#> Peroxisome 0.6788467 0.6518952
#> 40S Ribosome 0.6760487 0.4643483
#> Proteasome 0.8444952 0.8064265
#> Endosome 60S Ribosome Lysosome
#> Actin cytoskeleton 0.3955070 0.49914711 0.3924089
#> Endoplasmic reticulum/Golgi apparatus 0.3298215 0.44057429 0.3526493
#> Mitochondrion 0.7198622 0.51681006 0.7471831
#> Extracellular matrix 0.2420721 0.44304012 0.2483814
#> Nucleus - Chromatin 0.8226749 0.56029383 0.8451732
#> Cytosol 0.7826439 0.64389721 0.7995801
#> Plasma membrane 0.3425939 0.56161748 0.3274954
#> Nucleus - Non-chromatin 0.8135370 0.45463783 0.8365127
#> Endosome 0.1804409 0.54561425 0.1706577
#> 60S Ribosome 0.5456143 0.08250087 0.5709784
#> Lysosome 0.1706577 0.57097838 0.1023701
#> Peroxisome 0.6442550 0.41710740 0.6716427
#> 40S Ribosome 0.6762709 0.22048766 0.7022256
#> Proteasome 0.8642925 0.67687443 0.8858795
#> Peroxisome 40S Ribosome Proteasome
#> Actin cytoskeleton 0.6861757 0.56577585 0.66865454
#> Endoplasmic reticulum/Golgi apparatus 0.4138766 0.61065583 0.86850511
#> Mitochondrion 0.2418018 0.66012471 0.99171284
#> Extracellular matrix 0.4724549 0.60608808 0.84979611
#> Nucleus - Chromatin 0.5094584 0.65182738 0.97187508
#> Cytosol 0.9068309 0.53317641 0.16001172
#> Plasma membrane 0.6788467 0.67604868 0.84449520
#> Nucleus - Non-chromatin 0.6518952 0.46434826 0.80642652
#> Endosome 0.6442550 0.67627087 0.86429254
#> 60S Ribosome 0.4171074 0.22048766 0.67687443
#> Lysosome 0.6716427 0.70222557 0.88587953
#> Peroxisome 0.1378630 0.57564364 0.94187426
#> 40S Ribosome 0.5756436 0.08388726 0.53905744
#> Proteasome 0.9418743 0.53905744 0.08625819
## normalised average distance matrix
qsep(hlq)
#> Actin cytoskeleton
#> Actin cytoskeleton 1.000000
#> Endoplasmic reticulum/Golgi apparatus 3.566325
#> Mitochondrion 5.487565
#> Extracellular matrix 3.826523
#> Nucleus - Chromatin 5.501293
#> Cytosol 4.002866
#> Plasma membrane 1.885302
#> Nucleus - Non-chromatin 4.196833
#> Endosome 2.191892
#> 60S Ribosome 6.050204
#> Lysosome 3.833237
#> Peroxisome 4.977229
#> 40S Ribosome 6.744479
#> Proteasome 7.751780
#> Endoplasmic reticulum/Golgi apparatus
#> Actin cytoskeleton 3.418152
#> Endoplasmic reticulum/Golgi apparatus 1.000000
#> Mitochondrion 3.612725
#> Extracellular matrix 1.591860
#> Nucleus - Chromatin 4.560606
#> Cytosol 5.679619
#> Plasma membrane 3.757626
#> Nucleus - Non-chromatin 4.074365
#> Endosome 1.827864
#> 60S Ribosome 5.340238
#> Lysosome 3.444845
#> Peroxisome 3.002086
#> 40S Ribosome 7.279483
#> Proteasome 10.068668
#> Mitochondrion Extracellular matrix
#> Actin cytoskeleton 5.492000 2.937371
#> Endoplasmic reticulum/Golgi apparatus 3.772380 1.274937
#> Mitochondrion 1.000000 3.971864
#> Extracellular matrix 5.178342 1.000000
#> Nucleus - Chromatin 3.706445 4.735038
#> Cytosol 6.777214 5.483772
#> Plasma membrane 6.498905 3.097308
#> Nucleus - Non-chromatin 3.984578 4.074873
#> Endosome 3.989463 1.341559
#> 60S Ribosome 6.264298 5.370126
#> Lysosome 7.298839 2.426307
#> Peroxisome 1.753928 3.426989
#> 40S Ribosome 7.869189 7.225032
#> Proteasome 11.497028 9.851773
#> Nucleus - Chromatin Cytosol
#> Actin cytoskeleton 5.866617 4.125454
#> Endoplasmic reticulum/Golgi apparatus 5.074288 6.107304
#> Mitochondrion 3.949387 6.979127
#> Extracellular matrix 6.577972 7.362505
#> Nucleus - Chromatin 1.000000 6.481050
#> Cytosol 6.706063 1.000000
#> Plasma membrane 7.264170 6.482553
#> Nucleus - Non-chromatin 2.329217 4.470907
#> Endosome 4.559249 4.337398
#> 60S Ribosome 6.791368 7.804732
#> Lysosome 8.256053 7.810677
#> Peroxisome 3.695397 6.577769
#> 40S Ribosome 7.770279 6.355869
#> Proteasome 11.267046 1.855032
#> Plasma membrane Nucleus - Non-chromatin
#> Actin cytoskeleton 1.577520 5.454575
#> Endoplasmic reticulum/Golgi apparatus 3.280478 5.524955
#> Mitochondrion 5.433546 5.174528
#> Extracellular matrix 3.376167 6.899202
#> Nucleus - Chromatin 5.699765 2.838743
#> Cytosol 5.263072 5.638118
#> Plasma membrane 1.000000 7.141084
#> Nucleus - Non-chromatin 4.597470 1.000000
#> Endosome 1.898649 4.508607
#> 60S Ribosome 6.807412 5.510703
#> Lysosome 3.199131 8.171452
#> Peroxisome 4.924068 4.728573
#> 40S Ribosome 8.059015 5.535385
#> Proteasome 9.790319 9.348985
#> Endosome 60S Ribosome Lysosome
#> Actin cytoskeleton 2.882049 3.637272 2.859474
#> Endoplasmic reticulum/Golgi apparatus 2.507586 3.349623 2.681142
#> Mitochondrion 5.241381 3.762940 5.440307
#> Extracellular matrix 2.297934 4.205676 2.357826
#> Nucleus - Chromatin 5.621503 3.828601 5.775239
#> Cytosol 5.533638 4.552637 5.653384
#> Plasma membrane 2.983548 4.890957 2.852059
#> Nucleus - Non-chromatin 4.561265 2.549022 4.690083
#> Endosome 1.000000 3.023784 0.945782
#> 60S Ribosome 6.613436 1.000000 6.920877
#> Lysosome 1.667066 5.577587 1.000000
#> Peroxisome 4.673155 3.025521 4.871813
#> 40S Ribosome 8.061664 2.628381 8.371064
#> Proteasome 10.019831 7.847074 10.270091
#> Peroxisome 40S Ribosome Proteasome
#> Actin cytoskeleton 5.000144 4.122794 4.872468
#> Endoplasmic reticulum/Golgi apparatus 3.146645 4.642729 6.603120
#> Mitochondrion 1.760581 4.806427 7.220750
#> Extracellular matrix 4.484904 5.753452 8.066916
#> Nucleus - Chromatin 3.481232 4.454068 6.641018
#> Cytosol 6.411695 3.769793 1.131353
#> Plasma membrane 5.911872 5.887504 7.354454
#> Nucleus - Non-chromatin 3.654986 2.603465 4.521399
#> Endosome 3.570449 3.747880 4.789893
#> 60S Ribosome 5.055794 2.672549 8.204452
#> Lysosome 6.560924 6.859672 8.653691
#> Peroxisome 1.000000 4.175476 6.831959
#> 40S Ribosome 6.862111 1.000000 6.425975
#> Proteasome 10.919244 6.249348 1.000000
## Update the organelle cluster names for better
## rendering on the plots
names(hlq) <- sub("/", "\n", names(hlq))
names(hlq) <- sub(" - ", "\n", names(hlq))
names(hlq)
#> [1] "Actin cytoskeleton"
#> [2] "Endoplasmic reticulum\nGolgi apparatus"
#> [3] "Mitochondrion"
#> [4] "Extracellular matrix"
#> [5] "Nucleus\nChromatin"
#> [6] "Cytosol"
#> [7] "Plasma membrane"
#> [8] "Nucleus\nNon-chromatin"
#> [9] "Endosome"
#> [10] "60S Ribosome"
#> [11] "Lysosome"
#> [12] "Peroxisome"
#> [13] "40S Ribosome"
#> [14] "Proteasome"
## Heatmap of the normalised intensities
levelPlot(hlq)
## Boxplot of the normalised intensities
par(mar = c(3, 10, 2, 1))
plot(hlq)
## Boxplot of all between cluster average distances
x <- summary(hlq, verbose = FALSE)
boxplot(x)
## Missing data example, for 4 proteins and 3 fractions
x <- rbind(c(1.1, 1.2, 1.3), rep(1, 3), c(NA, 1, 1), c(1, 1, NA))
rownames(x) <- paste0("P", 1:4)
colnames(x) <- paste0("F", 1:3)
## P1 is the reference, against which we will calculate distances. P2
## has a complete profile, producing the *real* distance. P3 and P4 have
## missing values in the first and last fraction respectively.
x
#> F1 F2 F3
#> P1 1.1 1.2 1.3
#> P2 1.0 1.0 1.0
#> P3 NA 1.0 1.0
#> P4 1.0 1.0 NA
## If we drop F1 in P3, which represents a small difference of 0.1, the
## distance only considers F2 and F3, and increases. If we drop F3 in
## P4, which represents a large distance of 0.3, the distance only
## considers F1 and F2, and decreases. dist(x)