Interaction Viewer
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Interaction Details
Accession
EBI-11131799Type
Detection Method
Host Organism
Homo sapiens HeLa epitheloid cervical carcinoma cellPositive Interaction
✔️Annotations (9)
Topic | Description |
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Cell line id: MCP_ky_0006193 | |
http://www.biochem.mpg.de/mann/interactome/MCP_ky_0006193 | |
Author confidence calculation Protein identifications as obtained from MS spectra processing were filtered, removing hits to the reverse decoy database as well as proteins only identified by modified peptides. It was required that each protein be quantified in all replicates from the AP-MS samples of at least one cell line. Protein LFQ intensities were logarithmized and missing values imputed by values simulating noise around the detection limit. For each protein, a non-parametric method was used to select a subset of samples that provide a distribution of background intensities for this protein. This subset was used first to normalize all protein intensities to represent relative enrichment, and then to serve as the control group for a two-tailed Welch’s t test. Specific outliers in the volcano plots of logarithmized p values against enrichments were determined by an approach making use of the asymmetry in the outlier population (see url links for each interaction). Two cut-offs of different stringencies, representing 1 and 5% of enrichment false discovery rate (FDR), respectively, were used. Correlation coefficients between the intensity profiles of interacting proteins were calculated as additional quality parameters. Enrichment FDR (classes A, B and C) and profile correlation (modifier + or –) define the confidence class of an interaction (see author assigned scores). Relative abundance and interaction stoichiometry estimations: Estimating interaction stoichiometries requires the comparison of the amounts of different proteins relative to each other in one IP. To this end, the authors first subtracted the median intensity across all samples to account for the proportion due to unspecific binding. Then LFQ intensities were divided by the number of theoretically observable peptides for this protein. This corrects for biases introduced by different lengths of the protein sequences and the frequency and distribution of proteolytic cleavage sites. Finally, interaction stoichiometries were expressed relative to the bait protein. Cellular copy numbers and relative abundances were calculated using a similar approach on the whole proteome data and brought to absolute scale by normalization to a total protein amount of 200 pg in a cell volume of 1 pl for a HeLa cell. | |
Accepted 2015-OCT-15 AT 13:40 BST AT 13:40 BST by ORCHARD | |
Corrected. SILAC data situation explained in data processing comment.; All done and silac data explained as data-processing comment. | |
imex curation | |
Suppl. table S2. For bait details see supp. table S1 | |
21-10-2015: Contacted by IntAct-Help. | |
PAM-SILAC experiments mentioned in the text and summarized in figure 5 were not added since the authors stated that the SILAC data just confirmed the large screening results for a set of selected baits and did not provide further detail on the interactions. The cell lines tested with PAM-SILAC were MCP_ky_0002211 (interaction id EBI-11003881), MCP_ky_0006158 (interaction id EBI-11131339) and MCP_ky_0003099 (interaction id EBI-11029579). |
Publication
Title
A human interactome in three quantitative dimensions organized by stoichiometries and abundances.Journal
CellAuthors
Hein MY.,Hubner NC.,Poser I.,Cox J.,Nagaraj N.,Toyoda Y.,Gak IA.,Weisswange I.,Mansfeld J.,Buchholz F.,Hyman AA.,Mann M.Publication date
01/01/2015Publication reference
PubMed: 26496610External Cross References (1)
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Annotations (2)
Topic | Description |
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hein@biochem.mpg.de,mmann@biochem.mpg.de | |
09-06-2015: Submitted by Marco Hein, Max Planck Institute of Biochemistry, Martinsried. |
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