cvanderaa

Robust summary aggregation is very slow for SCP data

1

For large data such single-cell proteomics data, the robust summary aggregation is very slow. You can test this with this example: ```r library(scpdata) library(scp) aggregateFeatures(specht2019v3(), i = "peptides", name =...

As requested by the Slavov lab: - [ ] Include another matrix in the assays to store (and eventually have the functionality to estimate) the different types of missing data....

As requested by the Slavov lab: - [ ] Start using spike in peptides for QC, see SCoPE2 section in DO-MS (?could not find section in article?). - [ ]...

feature request: set values below a threshold as NA

1

The normalization function in [`SCeptre`](https://github.com/bfurtwa/SCeptre/blob/29a1e5a778096e2c40261c50335471159569ac5f/sceptre/sceptre.py#L625-L631) (from Schoof et al. 2021 paper) performs at some moment an NA thresholding, that is quantitative values below a given threshold are set as `NA`....

New sweep method [was Enhance: allow to `normalize` rows]

5

Following the normalization procedure described in [Specht et al. 2019](https://www.biorxiv.org/content/10.1101/665307v3) for normalizing single-cell proteomics data, I need to normalize the rows of an assay. I think `Features::normalize` could quickly include...

The GHAs seem to generate new snap images through `vdiffr` everytime they are run. This is not supposed to happen, rather new snaps should be compared to previous snaps and...

## Context I tried to aggregate data to protein level using MaxQuant output. I forgot to remove unidentified proteins, which MaxQuant labels in the `Proteins` column as `""`. This leads...