---
title: "README"
author: "RLionheart"
date: "2/25/2021"
output: html_document
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
*THIS IS AN OLD README FROM THE PROJECT BUILD. PLEASE GO TO THE PHOBOS PACKAGE ON GITHUB FOR CURRENT INFORMATION.*
[Phobos](https://github.com/IngallsLabUW/phobos)
---
## MARS
### Metabolite Annotation, Rank and Sort
The MARS project is a way to easily identify unknown mass features (MFs) in your data. It consists of three major sections:
- A central database containing unknown mass features (MFs) with mz, rt and ms2 data detected by the Ingalls lab
- A series of processes and functions for annotating, ranking, and scoring those MFs
- A central database containing annotated MFs from previous MARS missions
Flexible, updatable, searchable, rankable, exportable.
---
### Use Case Crash Course
The scripts are used in the following order:
Annotate_Confidence_Level1.R
Annotate_Confidence_Level2_MoNA.R
*The Metlin confidence level annotation is currently under review*
1. Start with a csv of experimental data. **Columns must be in the following format:**
- "MassFeature": Your unique mass feature, character.
- "mz": The mz value, numeric.
- "rt": The retention time, in seconds, numeric.
- "column": Column the mass feature was run on, character.
- "z": The ion mode, numeric.
- "MS2": MS2 data for those compounds that have it, character.
- **Important**: The MS2 data must be in the concatenated format of "mz, intensity;", as below.
```{r MS2, include=FALSE}
library(tidyverse)
Experimental.Values <- read.csv("data_extra/Example_Experimental_Data.csv")
```
```{r}
library(knitr)
kable(Experimental.Values[1, 6])
```
For an example csv, see "data_extra/Example_Experimental_Data.csv"
2. Run through Annotate_Confidence_Level1.R script. All required extra data (Ingalls standards and MS2) are included in this repository. When you have produced your confidence level 1 datasheet, write the csv and save it for the next step.
3. Move to Annotate_Confidence_Level2_MoNA.R. As in the previous step, all the required extra data (scraped MoNA sheets) are available in the data_extra/MoNA_RelationalSpreadsheets directory.
- Be aware that some of the column selections/renaming are to avoid explosion joins. If you want to see more data included in your joins, adjust the selections as you need. This will cause your datasheet to balloon!