In_vivo_analysis_steps.md

In vitro screen data analysis

0. Data compilation

• 0.1 Count collection
  
• 0.2 File inspection and filter (target constructs v.s. control constructs v.s. others according to reference file)
  
• 0.3 Rename files from barcode number to sample name
  

Script: 0_0_count_collection.py; 0_1_file_inspection_filter.py; 0_2_rename.sh
Source files: /InVivo/1_0_Raw/CRF_Screen_raw/ (Not uploaded)
Output files:
1. Counts
2. Non target filtered counts
2. Exp35 reads summary

1. Data normalization and conversion

• 1.0 Filter outliers by Z score
  
• 1.1 Combine Exp35 and Exp56 data
  
• 1.2 Filter bench contaminant constructs
  
• 1.3 Data conversion:
  
  • Calculate percentages of counts in each group
    
  • Combine percentage of counts * million in each file to create total distribution
    
  • Calculate percentile of counts in total distribution (negative binomial distribution)
    
  • Calculate gate percentile shift (e.g. for shX: Q4-Q1, Q3-average_of_others, etc.)
    
  • Compile results of different pools
    
  • Calculate z score
    

Script: Normalization and conversion; Z-Score
Source files: Non target filtered counts
Output files:
0. Outlier filtered counts
1. Exp35 Exp56 combined - outlier filtered counts
2. Exp35 Exp56 combined - outlier and contaminant filtered counts
3. Gate comparisons - seperated each pool
4. Gate comparisons - compiled + Z-Score

2. Target ranking & processing

• 2.1 Adjust gene RNAi z-score (gate comparison) by p-value
  
• 2.2 Plot adjusted RNAi z-score of genes
  

Script: z-score adjustment and plotting
Source files: Compiled z-score and p-value data
Output files:
1 Adjusted z-score
1_Sqrt adjusted z-score
2_Heatmap with gene names
2_Heatmap without gene names

3. Target gene interaction