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imputation_pipeline's Introduction

imputation_pipeline

Author: Nathan Yang

Purpose: Master Thesis Project

#This project includes all the shell and python scripts used in my imputation pipeline

sorted_Rice_download_links.txt contains all the FTP links of the 3000 individual Rice samples

1st_1500_samples.txt contains the FTP links for the first 1500 individual Rice samples

2nd_1500_samples.txt contains the FTP links for the second 1500 individual Rice samples

------------------- shell scripts ---------------------

prep_1st_half.sh is the shell script used to download and merge the first 1500 individual samples

prep_2nd_half.sh is the shell script used to download and merge the second 1500 individual samples

mv_1st_half_vcf.sh was used to remove duplicate downloaded VCF files and bring all the unique VCF files together under the current directory

merge_1st_half.sh: this shell is to merge all the sub-merged VCF files from the first 1500 samples into one by chromosomes

check.sh checks if there are undownloaded VCF files and download the undownloaded VCF file(s) accordingly.

phasing.sh: this shell is to phase reference VCF files with shapeit. the input is the chromosome number in format "chr#", e.g., chr1

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------------------- python scripts ---------------------

mask.py: to mask SNPs according to a randomly generated rate (0.0--1.0) at any genetic loci within a target dataset

three mandatory parameters: --filename sample.vcf.gz

--prefix output-prefix

--directory output-directory

two files will be generated after running this script: .vcf --masked VCF file

.mask.txt --masking info file (this file should be used to simplify the accuracy evaluation process)

get_samples.py: to randomly select samples to be put into either reference panel or target dataset.

usage: one input is required: directory where the output files should be placed

output: five directories each with 20 txt files will be generated (10 reference samples txt files and 10 target samples txt files)

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