https://github.com/cpanse/specter
Specter: linear deconvolution for targeted analysis of data-independent acquisition mass spectrometry proteomics
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Specter: linear deconvolution for targeted analysis of data-independent acquisition mass spectrometry proteomics
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Created about 8 years ago
· Last pushed about 8 years ago
https://github.com/cpanse/Specter/blob/master/
# Specter
Specter is an algorithm for the targeted analysis of data-independent acquisition mass spectrometry proteomics experiments, which is described in detail in our paper in [*Nature Methods*](http://dx.doi.org/10.1038/nmeth.4643). It can analyze data from any instrument type and window acquisition scheme. The required user inputs are a DIA data file in centroided mzML format, a spectral library in blib format, and a mass accuracy parameter, specified in parts-per-million.
The raw output of Specter is a .csv file describing the total ion intensities (= sum of fragment ion intensities) of each precursor in the spectral library at each retention time point of the experiment. A snippet of the typical raw output file looks like this:
```
Scan index Retention time (s) Precursor sequence Precursor charge Total ion intensity
10032 268.3763 ETLDASLPSDYLK 2 1,569,034
10032 268.3763 NPAADAGSNNASKK 2 3,112,580
10033 268.4273 IVLVDDSIVR 2 722,175
```
with the identifications and quantifications based on these scan-by-scan total ion intensities reported separately:
```
Precursor sequence Precursor charge Quant
ETLDASLPSDYLK 2 148,110,338
NPAADAGSNNASKK 2 32,234,856
IVLVDDSIVR 2 11,768,772
```
Specter currently requires the cluster-computing framework Apache Spark; a cloud framework and accompanying website will appear in the future. See ```SpecterUserGuide.pdf``` for detailed instructions on how to set up and use Specter.
Owner
- Name: Christian Panse
- Login: cpanse
- Kind: user
- Location: 47N 008E
- Company: Swiss federal institute of technology in Zurich
- Website: https://fgcz.ch/compms
- Repositories: 72
- Profile: https://github.com/cpanse
proteome informatics; ms comp; visualization; maps; code; reproducible research @hb9feb@fosstodon.org