/sma_carrier_detection

Primary LanguagePythonMIT LicenseMIT

SMA Carrier Detection

The scripts in this repository can be used to implement the methods described in Larson et al. 2015 (https://www.ncbi.nlm.nih.gov/pubmed/26510457) for detecting SMA carriers. This technique utilizes both carrier probabilities and coverage at SMN1 loci to investigate SMA carrier status. (in beta)

run_smn_doc.sh

Calculate coverge per gene and at three SMN loci that distinguish SMN1 from SMN2

Input Files:
  1. bam_list # file with one line per sample (tab delimited: absolute bam path and whether ice/agilent was used)
  2. GATKjar # location of GATK jar installation
  3. reference # path to reference hg37
  4. sma_intervals # smn loci interval file
  5. output_dir #name of output directory
  6. picard #location of picard jar installation
  7. scripts_dir #location of sma scripts

merge_smn_doc.py

Merge SMN coverage results from all samples into one file

Input Files:
  1. bam_list # file with one line per sample (tab delimited: absolute bam path and whether ice/agilent was used)
  2. output_dir #name of output directory (keep consistent with previous scripts)

calculate_coef_var.py

Calculate theta, di, ri, pi

Input Files:
  1. cov_directory #name of output directory (keep consistent with previous scripts)
  2. bam_files # file with one line per sample (tab delimited: absolute bam path and whether ice/agilent was used)
  3. interval_of_interest #specify if should run on ice or agilent
  4. datamash #path to datamash

calculate_carrier_probability.R

Calculates the carrier probabilitiy and plots credible intervals

Input Files:
  1. the ice/agilent_sma_sample_stat.txt file
  2. output directory

Requirements:

GATK Picard datamash