## 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)Preliminary
Examples
Case 1. Remove proteins specified by the user in this step and keep everything else.
In the example below, the specific protein with the identifier "ALBU_BOVIN" will be removed. If removeList = TRUE, this function will remove what you’ve specified and keep the rest.
dataFiltAnno <- filterOutIn(dataTran, listName = "ALBU_BOVIN",
removeList = TRUE, saveRm = TRUE)| R.Condition | R.Replicate | NUD4B_HUMAN (+1) | A0A7P0T808_HUMAN (+1) | A0A8I5KU53_HUMAN (+1) | ZN840_HUMAN | CC85C_HUMAN | TMC5B_HUMAN | C9JEV0_HUMAN (+1) | C9JNU9_HUMAN | CYC_BOVIN | TRFE_BOVIN | KRT16_MOUSE | F8W0H2_HUMAN | H0Y7V7_HUMAN (+1) | H0YD14_HUMAN | H3BUF6_HUMAN | H7C1W4_HUMAN (+1) | H7C3M7_HUMAN | TCPR2_HUMAN | TLR3_HUMAN | LRIG2_HUMAN | RAB3D_HUMAN | ADH1_YEAST | LYSC_CHICK | BGAL_ECOLI | CYTA_HUMAN | KPCB_HUMAN | LIPL_HUMAN | PIP_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 | A0A7I2PK40_HUMAN (+2) | NBDY_HUMAN | H0Y5R1_HUMAN (+1) |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 100fmol | 1 | 10.56297 | 11.549314 | 11.719168 | 8.387172 | 8.669058 | 8.935121 | 7.667971 | 7.735483 | 13.24241 | 13.77688 | 10.72312 | 9.056313 | 10.379473 | 10.157323 | 8.313422 | 8.288011 | 10.130553 | 14.135921 | 7.613072 | 9.130065 | 10.369163 | 14.83226 | 13.74330 | 14.49696 | 9.207415 | 9.851878 | 8.751500 | 6.865301 | 7.547524 | 11.97922 | 14.55181 | 6.717365 | 7.658178 | 10.448500 | 10.927208 | 7.604818 | 10.107211 | 9.932092 | 7.694357 | 7.605108 | 7.931518 | NA | NA | NA |
| 100fmol | 2 | 10.79921 | 12.089148 | 9.719358 | 8.804231 | 9.018858 | 8.869544 | 7.678527 | 8.253683 | 13.40545 | 13.93127 | NA | 9.223125 | 10.214856 | 10.306899 | 8.134353 | 8.112689 | 10.074064 | 10.465471 | 7.901218 | 9.086952 | 10.291532 | 14.76691 | 13.67018 | 14.74484 | 9.235814 | 10.389015 | 8.730980 | 6.974870 | 6.854838 | 11.63425 | 14.74389 | 7.244019 | 8.395332 | 9.921177 | 10.553026 | 7.152687 | 10.107710 | 8.547503 | 7.072113 | 9.470045 | 8.038315 | 10.767577 | NA | NA |
| 100fmol | 3 | 10.45838 | 12.224751 | 11.099936 | 7.965002 | 9.117244 | NA | 6.862711 | 8.975209 | 13.08420 | 14.03803 | NA | 9.367429 | 10.049530 | 9.987064 | 8.237180 | 7.853620 | 10.601812 | 14.164706 | 7.572652 | 8.207806 | 10.360676 | 15.00145 | 13.55870 | 14.60032 | 9.218644 | 10.248554 | 8.172099 | NA | 6.848418 | 11.85400 | 14.61937 | 6.661707 | 8.263969 | 10.122465 | 10.239311 | 6.979322 | 10.869212 | 8.688500 | 7.219746 | 7.510801 | 7.724076 | 10.789401 | 9.972824 | NA |
| 100fmol | 4 | 10.71544 | 11.852006 | 10.885548 | 8.554835 | 9.095925 | 8.881386 | 6.409230 | 8.495249 | 13.43543 | 13.84119 | NA | 9.662869 | 10.453966 | 10.179130 | NA | 7.753558 | 9.645268 | 14.802626 | 8.101022 | 8.669744 | 10.296266 | 14.61578 | 13.69871 | 14.33172 | 8.690788 | 10.421396 | 8.449746 | NA | 7.142488 | 11.94343 | 14.58679 | 6.320530 | 8.008266 | 8.872427 | 10.645436 | 6.464862 | 9.766908 | 8.537630 | 7.160874 | 7.341750 | 7.859464 | 10.835300 | 9.738847 | 9.645902 |
| 200fmol | 1 | 10.57160 | 12.093929 | 10.856535 | 8.288291 | 7.216164 | 8.725776 | 7.033663 | NA | 14.23846 | 14.20109 | 11.01535 | 9.011903 | 10.202543 | 10.027751 | 8.090666 | 8.208457 | 10.493359 | 14.521801 | 7.897320 | 8.277242 | 9.979726 | 15.49626 | 14.50062 | 15.33837 | 8.698267 | 10.563345 | 8.813913 | 6.012131 | 6.985846 | 11.73893 | 14.69353 | 6.465701 | 7.674034 | 9.975073 | 10.868666 | 7.157451 | 8.509445 | 8.772143 | 7.914636 | 7.242116 | 8.734171 | 11.251413 | NA | 9.656401 |
| 200fmol | 2 | 10.63811 | 12.060734 | 11.098380 | NA | 8.909464 | NA | 7.265489 | 8.105569 | 14.15752 | 14.33555 | NA | 9.435343 | 10.091549 | NA | 8.451251 | 8.207311 | 10.145013 | 14.403733 | 7.485393 | 8.772034 | 10.354478 | 15.59053 | 14.41310 | 15.63168 | 9.438836 | 10.304035 | 8.869666 | NA | 7.181318 | 11.77274 | 14.85306 | 6.111517 | 8.059428 | 10.187635 | 9.504205 | 7.007345 | 9.605005 | 8.671425 | 7.279112 | 7.384706 | 6.980968 | NA | 10.206673 | 9.675987 |
| 200fmol | 3 | 10.57451 | 8.623909 | 10.867758 | 8.506773 | 9.157111 | 8.825558 | 6.738928 | 8.947838 | 13.98765 | 14.70973 | 10.47341 | 9.290490 | 10.576258 | 10.340571 | 8.157953 | 7.579605 | 9.997708 | NA | 7.381150 | 9.104115 | 10.010094 | 15.56289 | 14.71734 | 15.46245 | 8.717193 | 9.936654 | 8.503185 | NA | 6.753701 | 11.79073 | 14.75351 | 5.981363 | 6.942687 | 10.262921 | 10.909423 | 6.841965 | 9.710222 | 9.089162 | 8.352360 | 7.103882 | 7.321552 | 10.423182 | 9.568943 | 9.479491 |
| 200fmol | 4 | 10.45930 | 8.403669 | 11.227619 | 8.604641 | 8.227076 | 9.099286 | 6.611351 | 8.409371 | 14.22256 | 14.05391 | NA | 9.136406 | 9.770583 | 10.380054 | 8.376304 | 6.627840 | 10.085990 | NA | 7.299398 | NA | 10.210080 | 15.94951 | 14.47968 | 15.37392 | 9.096700 | 10.174299 | 8.274901 | NA | 6.767077 | 11.97618 | 14.90602 | 5.816397 | 7.816675 | 9.781058 | 10.794056 | 7.064621 | 9.227703 | 8.891323 | 7.699336 | 7.402811 | 8.684079 | 9.569093 | NA | NA |
| 50fmol | 1 | 10.29551 | 9.207660 | 7.512941 | 7.888064 | 8.445760 | NA | 9.477349 | 7.597259 | 13.00744 | 13.53207 | NA | 9.181972 | 9.834864 | 10.430808 | 8.140018 | 7.515010 | 9.243753 | 13.787087 | 7.298440 | 8.382651 | 10.230051 | 14.10498 | 12.92011 | 13.97831 | 11.460512 | 10.242765 | 8.117352 | 9.784420 | 7.222133 | 11.97947 | 14.49047 | 9.600191 | 6.996896 | NA | 8.873600 | 6.492949 | 8.625129 | 5.555271 | 7.741055 | 4.535630 | 7.261620 | NA | NA | NA |
| 50fmol | 2 | 10.52363 | NA | 10.487390 | 8.487168 | 8.440663 | NA | 7.953133 | 8.430766 | 12.89290 | 13.63222 | NA | 9.106515 | 8.981449 | 9.923728 | 8.183965 | 6.975365 | 9.845571 | 14.772685 | 7.187730 | 8.413291 | 10.270688 | 13.96591 | 12.86118 | 13.94872 | 9.571254 | NA | 8.622316 | 7.311721 | 7.475005 | 12.13606 | 14.60519 | 7.821160 | 7.259115 | 8.211273 | 10.246660 | 6.791597 | 9.374858 | 8.927497 | 7.123085 | 6.437772 | 6.576050 | NA | NA | NA |
| 50fmol | 3 | 10.60367 | 5.345717 | 10.612237 | 6.489340 | 8.222371 | 8.411847 | 8.013816 | 8.079752 | 12.42126 | 13.61379 | 10.27392 | 9.121908 | NA | 10.143559 | 8.010191 | 6.062055 | 9.596066 | 9.501729 | NA | NA | 10.032851 | 14.00212 | 12.57959 | 13.95996 | 10.108303 | 10.109936 | 8.316336 | 7.002350 | 6.696528 | 11.86976 | 14.63679 | 7.575196 | 6.846958 | 8.143986 | 9.743188 | 6.489755 | 8.919981 | 8.287137 | 8.287868 | 6.960939 | 6.041769 | NA | NA | NA |
| 50fmol | 4 | 10.45092 | 9.758661 | 10.219694 | 8.183409 | 7.966386 | 8.538480 | 7.346957 | 8.562192 | 12.64933 | 13.48221 | NA | NA | 9.303066 | 10.289551 | 8.536331 | 4.793597 | 9.722454 | 14.046393 | 7.296901 | 7.907745 | 10.183775 | 14.07886 | 12.67173 | 13.91862 | 9.672954 | 10.300261 | NA | 7.364202 | NA | 11.92845 | 14.86372 | 7.857094 | 7.778509 | 9.078169 | 9.965852 | 5.010268 | 9.009555 | 8.896037 | 7.505010 | 7.094798 | 7.037478 | NA | NA | NA |
If saveRm = TRUE, the filtered-out data ("ALBU_BOVIN") will be saved as an .xlsx file named filterOutIn.xlsx in the current working directory, and you can inspect this list to see what was removed.
To remove multiple entries, users may combine exact matching listName with pattern matching regexName. For example, in addition to removing "ALBU_BOVIN", the following code also removes any protein whose identifier contains the string "HUMAN".
dataFiltAnno2 <- filterOutIn(dataTran,
listName = "ALBU_BOVIN", regexName = "HUMAN",
removeList = TRUE, saveRm = TRUE)| R.Condition | R.Replicate | CYC_BOVIN | TRFE_BOVIN | KRT16_MOUSE | ADH1_YEAST | LYSC_CHICK | BGAL_ECOLI |
|---|---|---|---|---|---|---|---|
| 100fmol | 1 | 13.24241 | 13.77688 | 10.72312 | 14.83226 | 13.74330 | 14.49696 |
| 100fmol | 2 | 13.40545 | 13.93127 | NA | 14.76691 | 13.67018 | 14.74484 |
| 100fmol | 3 | 13.08420 | 14.03803 | NA | 15.00145 | 13.55870 | 14.60032 |
| 100fmol | 4 | 13.43543 | 13.84119 | NA | 14.61578 | 13.69871 | 14.33172 |
| 200fmol | 1 | 14.23846 | 14.20109 | 11.01535 | 15.49626 | 14.50062 | 15.33837 |
| 200fmol | 2 | 14.15752 | 14.33555 | NA | 15.59053 | 14.41310 | 15.63168 |
| 200fmol | 3 | 13.98765 | 14.70973 | 10.47341 | 15.56289 | 14.71734 | 15.46245 |
| 200fmol | 4 | 14.22256 | 14.05391 | NA | 15.94951 | 14.47968 | 15.37392 |
| 50fmol | 1 | 13.00744 | 13.53207 | NA | 14.10498 | 12.92011 | 13.97831 |
| 50fmol | 2 | 12.89290 | 13.63222 | NA | 13.96591 | 12.86118 | 13.94872 |
| 50fmol | 3 | 12.42126 | 13.61379 | 10.27392 | 14.00212 | 12.57959 | 13.95996 |
| 50fmol | 4 | 12.64933 | 13.48221 | NA | 14.07886 | 12.67173 | 13.91862 |
Case 2. Keep the proteins specified by the user in this step and remove everything else.
If we set removeList to FALSE, running this code will remove everything you DIDN’T specify and keep only things that matched your search terms.
dataFiltAnno3 <- filterOutIn(dataTran,
listName = "ALBU_BOVIN", regexName = "HUMAN",
removeList = FALSE)| R.Condition | R.Replicate | NUD4B_HUMAN (+1) | A0A7P0T808_HUMAN (+1) | A0A8I5KU53_HUMAN (+1) | ZN840_HUMAN | CC85C_HUMAN | TMC5B_HUMAN | C9JEV0_HUMAN (+1) | C9JNU9_HUMAN | ALBU_BOVIN | F8W0H2_HUMAN | H0Y7V7_HUMAN (+1) | H0YD14_HUMAN | H3BUF6_HUMAN | H7C1W4_HUMAN (+1) | H7C3M7_HUMAN | TCPR2_HUMAN | TLR3_HUMAN | LRIG2_HUMAN | RAB3D_HUMAN | CYTA_HUMAN | KPCB_HUMAN | LIPL_HUMAN | PIP_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 | A0A7I2PK40_HUMAN (+2) | NBDY_HUMAN | H0Y5R1_HUMAN (+1) |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 100fmol | 1 | 10.56297 | 11.549314 | 11.719168 | 8.387172 | 8.669058 | 8.935121 | 7.667971 | 7.735483 | 16.73148 | 9.056313 | 10.379473 | 10.157323 | 8.313422 | 8.288011 | 10.130553 | 14.135921 | 7.613072 | 9.130065 | 10.369163 | 9.207415 | 9.851878 | 8.751500 | 6.865301 | 7.547524 | 11.97922 | 14.55181 | 6.717365 | 7.658178 | 10.448500 | 10.927208 | 7.604818 | 10.107211 | 9.932092 | 7.694357 | 7.605108 | 7.931518 | NA | NA | NA |
| 100fmol | 2 | 10.79921 | 12.089148 | 9.719358 | 8.804231 | 9.018858 | 8.869544 | 7.678527 | 8.253683 | 16.59264 | 9.223125 | 10.214856 | 10.306899 | 8.134353 | 8.112689 | 10.074064 | 10.465471 | 7.901218 | 9.086952 | 10.291532 | 9.235814 | 10.389015 | 8.730980 | 6.974870 | 6.854838 | 11.63425 | 14.74389 | 7.244019 | 8.395332 | 9.921177 | 10.553026 | 7.152687 | 10.107710 | 8.547503 | 7.072113 | 9.470045 | 8.038315 | 10.767577 | NA | NA |
| 100fmol | 3 | 10.45838 | 12.224751 | 11.099936 | 7.965002 | 9.117244 | NA | 6.862711 | 8.975209 | 16.63252 | 9.367429 | 10.049530 | 9.987064 | 8.237180 | 7.853620 | 10.601812 | 14.164706 | 7.572652 | 8.207806 | 10.360676 | 9.218644 | 10.248554 | 8.172099 | NA | 6.848418 | 11.85400 | 14.61937 | 6.661707 | 8.263969 | 10.122465 | 10.239311 | 6.979322 | 10.869212 | 8.688500 | 7.219746 | 7.510801 | 7.724076 | 10.789401 | 9.972824 | NA |
| 100fmol | 4 | 10.71544 | 11.852006 | 10.885548 | 8.554835 | 9.095925 | 8.881386 | 6.409230 | 8.495249 | 16.60032 | 9.662869 | 10.453966 | 10.179130 | NA | 7.753558 | 9.645268 | 14.802626 | 8.101022 | 8.669744 | 10.296266 | 8.690788 | 10.421396 | 8.449746 | NA | 7.142488 | 11.94343 | 14.58679 | 6.320530 | 8.008266 | 8.872427 | 10.645436 | 6.464862 | 9.766908 | 8.537630 | 7.160874 | 7.341750 | 7.859464 | 10.835300 | 9.738847 | 9.645902 |
| 200fmol | 1 | 10.57160 | 12.093929 | 10.856535 | 8.288291 | 7.216164 | 8.725776 | 7.033663 | NA | 17.01166 | 9.011903 | 10.202543 | 10.027751 | 8.090666 | 8.208457 | 10.493359 | 14.521801 | 7.897320 | 8.277242 | 9.979726 | 8.698267 | 10.563345 | 8.813913 | 6.012131 | 6.985846 | 11.73893 | 14.69353 | 6.465701 | 7.674034 | 9.975073 | 10.868666 | 7.157451 | 8.509445 | 8.772143 | 7.914636 | 7.242116 | 8.734171 | 11.251413 | NA | 9.656401 |
| 200fmol | 2 | 10.63811 | 12.060734 | 11.098380 | NA | 8.909464 | NA | 7.265489 | 8.105569 | 16.68193 | 9.435343 | 10.091549 | NA | 8.451251 | 8.207311 | 10.145013 | 14.403733 | 7.485393 | 8.772034 | 10.354478 | 9.438836 | 10.304035 | 8.869666 | NA | 7.181318 | 11.77274 | 14.85306 | 6.111517 | 8.059428 | 10.187635 | 9.504205 | 7.007345 | 9.605005 | 8.671425 | 7.279112 | 7.384706 | 6.980968 | NA | 10.206673 | 9.675987 |
| 200fmol | 3 | 10.57451 | 8.623909 | 10.867758 | 8.506773 | 9.157111 | 8.825558 | 6.738928 | 8.947838 | 16.79798 | 9.290490 | 10.576258 | 10.340571 | 8.157953 | 7.579605 | 9.997708 | NA | 7.381150 | 9.104115 | 10.010094 | 8.717193 | 9.936654 | 8.503185 | NA | 6.753701 | 11.79073 | 14.75351 | 5.981363 | 6.942687 | 10.262921 | 10.909423 | 6.841965 | 9.710222 | 9.089162 | 8.352360 | 7.103882 | 7.321552 | 10.423182 | 9.568943 | 9.479491 |
| 200fmol | 4 | 10.45930 | 8.403669 | 11.227619 | 8.604641 | 8.227076 | 9.099286 | 6.611351 | 8.409371 | 16.81152 | 9.136406 | 9.770583 | 10.380054 | 8.376304 | 6.627840 | 10.085990 | NA | 7.299398 | NA | 10.210080 | 9.096700 | 10.174299 | 8.274901 | NA | 6.767077 | 11.97618 | 14.90602 | 5.816397 | 7.816675 | 9.781058 | 10.794056 | 7.064621 | 9.227703 | 8.891323 | 7.699336 | 7.402811 | 8.684079 | 9.569093 | NA | NA |
| 50fmol | 1 | 10.29551 | 9.207660 | 7.512941 | 7.888064 | 8.445760 | NA | 9.477349 | 7.597259 | 17.00833 | 9.181972 | 9.834864 | 10.430808 | 8.140018 | 7.515010 | 9.243753 | 13.787087 | 7.298440 | 8.382651 | 10.230051 | 11.460512 | 10.242765 | 8.117352 | 9.784420 | 7.222133 | 11.97947 | 14.49047 | 9.600191 | 6.996896 | NA | 8.873600 | 6.492949 | 8.625129 | 5.555271 | 7.741055 | 4.535630 | 7.261620 | NA | NA | NA |
| 50fmol | 2 | 10.52363 | NA | 10.487390 | 8.487168 | 8.440663 | NA | 7.953133 | 8.430766 | 16.82764 | 9.106515 | 8.981449 | 9.923728 | 8.183965 | 6.975365 | 9.845571 | 14.772685 | 7.187730 | 8.413291 | 10.270688 | 9.571254 | NA | 8.622316 | 7.311721 | 7.475005 | 12.13606 | 14.60519 | 7.821160 | 7.259115 | 8.211273 | 10.246660 | 6.791597 | 9.374858 | 8.927497 | 7.123085 | 6.437772 | 6.576050 | NA | NA | NA |
| 50fmol | 3 | 10.60367 | 5.345717 | 10.612237 | 6.489340 | 8.222371 | 8.411847 | 8.013816 | 8.079752 | 16.67403 | 9.121908 | NA | 10.143559 | 8.010191 | 6.062055 | 9.596066 | 9.501729 | NA | NA | 10.032851 | 10.108303 | 10.109936 | 8.316336 | 7.002350 | 6.696528 | 11.86976 | 14.63679 | 7.575196 | 6.846958 | 8.143986 | 9.743188 | 6.489755 | 8.919981 | 8.287137 | 8.287868 | 6.960939 | 6.041769 | NA | NA | NA |
| 50fmol | 4 | 10.45092 | 9.758661 | 10.219694 | 8.183409 | 7.966386 | 8.538480 | 7.346957 | 8.562192 | 16.91736 | NA | 9.303066 | 10.289551 | 8.536331 | 4.793597 | 9.722454 | 14.046393 | 7.296901 | 7.907745 | 10.183775 | 9.672954 | 10.300261 | NA | 7.364202 | NA | 11.92845 | 14.86372 | 7.857094 | 7.778509 | 9.078169 | 9.965852 | 5.010268 | 9.009555 | 8.896037 | 7.505010 | 7.094798 | 7.037478 | NA | NA | NA |
Extension
Besides protein names, the function filterOutIn() can filter proteins using additional protein information.
For Spectronaut:
"PG.Genes","PG.ProteinAccession","PG.ProteinDescriptions", and"PG.ProteinName".For Scaffold:
"ProteinDescriptions","AccessionNumber", and"AlternateID".
dataFiltAnno4 <- filterOutIn(dataTran,
listName = c("Putative zinc finger protein 840",
"Bovine serum albumin"),
by = "PG.ProteinDescriptions",
removeList = FALSE)In this case, the proteins whose "PG.ProteinDescriptions" match with "Putative zinc finger protein 840" or "Bovine serum albumin" will be kept.
| R.Condition | R.Replicate | ZN840_HUMAN | ALBU_BOVIN |
|---|---|---|---|
| 100fmol | 1 | 8.387172 | 16.73148 |
| 100fmol | 2 | 8.804231 | 16.59264 |
| 100fmol | 3 | 7.965002 | 16.63252 |
| 100fmol | 4 | 8.554835 | 16.60032 |
| 200fmol | 1 | 8.288291 | 17.01166 |
| 200fmol | 2 | NA | 16.68193 |
| 200fmol | 3 | 8.506773 | 16.79798 |
| 200fmol | 4 | 8.604641 | 16.81152 |
| 50fmol | 1 | 7.888064 | 17.00833 |
| 50fmol | 2 | 8.487168 | 16.82764 |
| 50fmol | 3 | 6.489340 | 16.67403 |
| 50fmol | 4 | 8.183409 | 16.91736 |
Details
In some cases, a researcher may wish to filter out a specific protein or proteins from the dataset. The most common instance of this would be proteins identified from the common contaminants database, where we don’t want something like BSA to be matched to a human protein because the search algorithm didn’t have the correct option available, but we don’t actually care about BSA itself and want to leave it out of our visualization. Other examples may be filtering out entries from the decoy database (specific to a Scaffold file only, will not be present in a Spectronaut file), or a mixed-species experiment where the researcher wants to evaluate data from only one species at a time. This step allows you to set aside specific proteins from downstream analysis, using either an exact match identifier (the listName argument), or text-containing identifiers (the regexName argument).
Note: If both
Keep in mind: Removal of any proteins, including common contaminants, will affect any global calculations performed after this step (such as normalization). This should not be done without a clear understanding of how this will affect your results.
listName and regexName are defined, the proteins to be selected or removed is the union of the two terms.Keep in mind: Removal of any proteins, including common contaminants, will affect any global calculations performed after this step (such as normalization). This should not be done without a clear understanding of how this will affect your results.