An interaction network of RNA-binding proteins involved in Drosophila oogenesis

Prashali Bansal; Johannes Madlung; Kristina Schaaf; Boris Macek; Fulvia Bono

MaxLFQ algorithm was activated and the minimum number of peptide ratio count was set to 1 (73) . All peptide and protein identifications were filtered using a target-decoy approach with a false discovery rate (FDR) set . CC-BY-NC-ND 4.0 International license author/funder. It is made available under a The copyright holder for this preprint (which was not peer-reviewed) is the . https://doi.org/10.1101/2020.01.08.899146 doi: bioRxiv preprint 9 to 0.01 at peptide and protein level (Supplementary peptides table) (74) . A valid protein identification required at least one peptide with a posterior error probability (PEP) value of 0.01 or smaller. To transfer peptide identifications to unidentified or unsequenced peptides between samples, for quantification, matching between runs option was selected, with a match time window of 0.7 min and an alignment time window of 20 min. Matching was performed only between replicates by controlling the fraction numbers. The same parameters were used to process the raw data from the experiments applying dimethyl labeling, except for The copyright holder for this preprint (which was not peer-reviewed) is the . https://doi.org/10.1101/2020.01.08.899146 doi: bioRxiv preprint for dimethylMS). Normalized ratios were Log2-transformed and ratios from duplicates were plotted against each other. Statistically significant differences in abundance were determined by applying an arbitrary ratio threshold of 1 in Log2 scale (twofold).