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Preliminary

## load R package
library(msDiaLogue)
## preprocessing
fileName <- "../inst/extdata/Toy_Spectronaut_Data.csv"
dataSet <- preprocessing(fileName,
                         filterNaN = TRUE, filterUnique = 2,
                         replaceBlank = TRUE, saveRm = TRUE)
## transformation
dataTran <- transform(dataSet, logFold = 2)
## annotation-based filtering
dataFiltAnno <- filterOutIn(dataTran, listName = "ALBU_BOVIN",
                            removeList = TRUE, saveRm = TRUE)
## normalization
dataNorm <- normalize(dataFiltAnno, normalizeType = "median")

Examples

Before imputing missing (NA) values, proteins can be filtered based on the proportion of non-missing observations using filterNA().

The minProp argument sets the minimum required non-missing proportion for a protein to be retained, and the by argument determines whether this proportion is evaluated within each condition (by = "cond") or across all samples (by = "all").

For example, setting minProp = 0.51 and by = "cond" requires that a protein must be observed in at least 51% of replicates within each condition. If a protein fails to meet the threshold in any condition, it will be removed. And saveRm = TRUE indicates that the filtered data will be saved as a .csv file named filtered_NA_data.csv in the current working directory.

dataFilt <- filterNA(dataNorm, minProp = 0.51, by = "cond", saveRm = TRUE)
R.Condition R.Replicate NUD4B_HUMAN (+1) A0A7P0T808_HUMAN (+1) A0A8I5KU53_HUMAN (+1) ZN840_HUMAN CC85C_HUMAN C9JEV0_HUMAN (+1) C9JNU9_HUMAN CYC_BOVIN TRFE_BOVIN F8W0H2_HUMAN H0Y7V7_HUMAN (+1) H0YD14_HUMAN H3BUF6_HUMAN H7C1W4_HUMAN (+1) H7C3M7_HUMAN TLR3_HUMAN LRIG2_HUMAN RAB3D_HUMAN ADH1_YEAST LYSC_CHICK BGAL_ECOLI CYTA_HUMAN KPCB_HUMAN LIPL_HUMAN CO6_HUMAN BGAL_HUMAN SYTC_HUMAN CASPE_HUMAN DCAF6_HUMAN DALD3_HUMAN HGNAT_HUMAN RFFL_HUMAN RN185_HUMAN ZN462_HUMAN ALKB7_HUMAN POLK_HUMAN ACAD8_HUMAN
100pmol 1 0.6578963 1.6912275 1.523093 -1.6229297 -0.9854966 -2.2020970 -2.0487396 3.452154 3.943761 -0.6386260 0.4190686 0.3832438 -1.8057427 -1.711792 0.2348458 -2.451893 -0.9267417 0.3315355 4.814073 3.813956 4.602821 -0.6759724 0.0138251 -1.1567811 -2.703667 1.866666 4.775565 -3.1627881 -2.212775 0.3976973 1.0009580 -2.370005 0.1730515 0.0000000 -2.4413680 -2.300598 -2.2255399
100pmol 2 1.1618220 2.6069381 0.499450 -0.8939165 -0.4318767 -2.0224822 -1.2582828 3.826245 4.398260 -0.3855094 0.5688423 0.7856583 -1.4665636 -1.598602 0.4582302 -1.817571 -0.6094305 0.6593645 5.179413 4.207712 4.995489 -0.2306371 0.5203989 -1.0431798 -2.550131 2.183688 5.153782 -2.2734413 -1.107578 0.5054164 1.0064713 -2.287126 0.7952927 -0.9506921 -2.6135205 0.000000 -1.6024466
100pmol 3 0.6700794 2.3944773 1.292374 -1.6925457 -0.6687828 -2.9987418 -0.8270544 3.584108 4.078495 -0.5356376 0.4615256 0.0895033 -1.5213077 -1.715882 1.0240181 -2.147069 -1.3776219 0.4651160 4.902153 3.948069 4.690354 -0.6886192 0.4043134 -1.4787373 -2.907444 1.976459 4.876785 -3.2755551 -1.478305 0.1742765 0.5943610 -2.635191 0.6053144 -1.0476748 -2.6195940 -2.377350 -2.0024438
100pmol 4 0.8459180 2.0861542 1.194119 -1.2273728 -0.6919248 -3.4192914 -1.4298346 3.588195 4.071733 -0.0242533 0.3495332 0.2761703 NA -1.974565 0.0000000 -1.904616 -1.1083001 0.4016035 4.859260 3.951123 4.629191 -1.0397232 0.3669244 -1.3587551 -2.708964 1.949330 4.844947 -3.3525778 -2.049782 -0.8802224 0.9334560 -3.173078 0.1359572 -1.1958590 -2.7445785 -2.634663 -2.0589152
200pmol 1 1.2367495 2.7209140 1.643059 -0.9241627 -2.0376118 -2.1284865 NA 4.926798 5.071045 -0.3843617 0.9573775 0.7511402 -1.2486171 -1.348386 1.1799089 -1.519906 -1.0325902 0.8746494 6.245210 5.245063 6.005343 -0.8155394 0.9062960 -0.7355826 -2.086968 2.468791 5.354433 -2.9824358 -1.791057 0.5501207 1.7437348 -2.291354 -0.7523574 -0.5793031 -1.4223468 -2.145883 -0.5956163
200pmol 2 0.8920522 2.1320303 1.448951 NA -0.5354481 -2.5546421 -1.4310495 4.653112 4.847591 -0.2522428 0.4211597 NA -1.4825147 -1.620216 0.3960272 -2.067634 -0.8169825 0.6131741 5.965971 4.954881 5.748865 -0.3324563 0.6299749 -0.9458767 -2.553825 2.208374 5.114606 -3.5195148 -1.671696 0.3551539 -0.1366535 -2.779264 0.1366535 -0.8642755 -2.5798709 -2.309546 -2.3627650
200pmol 3 1.2852038 -0.8407850 1.836982 -0.7498530 -0.1779857 -2.6275134 -0.4297874 5.025134 5.020476 -0.1217261 1.1101593 0.9043385 -1.1300491 -1.793222 0.8158324 -1.870606 -0.5628205 0.9300210 6.311564 5.279995 6.070587 -0.5160321 0.7621903 -0.8359278 -2.306285 2.467474 5.407801 -3.3621142 -2.223375 0.8759602 1.3922679 -2.542126 0.5557834 -0.1662571 -1.0158409 -2.121038 -1.6854347
200pmol 4 1.5207481 -0.6040897 2.060276 -0.3758423 -0.8639327 -2.4855064 -0.7430913 5.224020 5.377023 0.0161123 0.7924755 1.0651086 -0.7232350 -2.448600 0.8442237 -1.693849 NA 1.1502570 6.655618 5.628997 6.343191 -0.0161123 1.0727957 -0.6382337 -2.135701 2.815138 5.691298 -2.9208223 -1.419815 0.9018856 1.6702296 -2.088800 0.1983234 -0.0738239 -1.3827316 -1.718714 -0.5015723
50pmol 1 1.3569066 -0.0418239 -1.605374 -1.1289594 -0.9034872 0.0539109 -1.5868197 3.547765 4.397999 0.0418239 0.6383018 1.0090953 -0.9876086 -1.713483 0.1019217 -1.921549 -0.9836494 1.0378691 4.827457 3.633069 4.671661 2.3687002 0.8333762 -1.0023667 -2.155108 2.618091 5.473048 0.5514687 -1.981854 NA -0.3248609 -2.734260 -0.6292096 -3.5325733 -1.2902634 -4.787183 -2.0214147
50pmol 2 1.6024612 NA 1.579083 -0.5872764 -0.4786125 -0.9419543 -0.6649410 3.779592 4.677255 0.2521855 0.1196002 1.1937745 -0.7693976 -2.240260 0.7951258 -1.798939 -0.4338096 1.3649676 5.070432 3.993905 4.912229 0.8090999 NA -0.4372525 -1.552151 2.850557 5.750686 -1.2356313 -1.562935 -0.8838660 1.2757206 -2.381622 0.6504456 0.0000000 -1.7357928 -2.468666 -2.2680179
50pmol 3 1.6576732 -3.4526216 1.552080 -2.4702967 -0.6505471 -0.8524562 -0.7371056 3.729220 4.679342 0.2920380 NA 1.1969443 -0.6623836 -2.395087 0.6664780 NA NA 1.3371078 5.157961 3.997182 4.927047 0.9774672 1.0924818 -0.5422253 -1.947256 2.893225 5.804690 -1.1925628 -1.811837 -0.6752742 1.0031749 -2.315473 0.2331366 -0.8188381 -0.5723308 -2.056650 -2.4453921
50pmol 4 1.3361532 0.6443309 1.275179 -1.1057418 -1.2905885 -1.5849506 -0.6332468 3.345342 4.341111 NA 0.0000000 1.1344349 -0.8056352 -4.298759 0.5579245 -2.058139 -1.0248051 0.9560929 4.778818 3.668827 4.637064 0.5802164 0.9408524 NA NA 2.591638 5.452341 -1.6387928 -1.429612 0.1904210 0.7490866 -4.231605 -0.1802510 -0.3981666 -1.8530176 -2.042691 -2.1323101
Note: There is no rule in the field of proteomics for filtering based on percentage of missingness, similar to there being no rule for the number of replicates required to draw a conclusion. However, reproducible observations make conclusions more credible. Setting the minProp to 0.51 requires that any protein be observed in a majority of the replicates by condition in order to be considered. For 3 replicates, this would require 2 measurements to allow imputation of the 3rd value. If only 1 measurement is seen, the other values will remain NA, and will be filtered out in a subsequent step.