Danie:Notebook/Haplotyping/Genotyping
Genotyping[edit]
This page focuses on my work regarding genotyping the different data sets from the haplotyping project. Genotyping is, in a sense, the first step in haplotyping, because you need to be able to identify heterozygous SNPs. Most programs, like HAPCUT, require a vcf that already states the locations of the heterozygous SNPs before running.
Analyzing Genotyping Abilities of Different Data Sets[edit]
In the final step, I use the following MATLAB code to create the ROC curve. You can view the master file as media on the wiki.
The steps are:
- Read in the infofile, which is a file that lists all the files you'd like to use for the analysis. The files may also have a tag, which is used for labeling. One file must be labeled "true" in order to analyze everything against a true VCF
- Next loads in position data for true file, and position and quality data for the test data
- Compares true positions against test positions, overlaps with the true data are considered "true" and all others are "false"
- False discovery rate and sensitivity are calculated using the "false" and "true" data sets, respectively.
Individual Data Sets[edit]
BAC[edit]
BAC was able to be analyzed by freebayes using its standard bam files. Since each bam was sorted by index, not chromosome, I used every bam file, extracting each chromosome for analysis individually. script
Hi-C[edit]
Hi-C was able to be analyzed by freebayes using its standard bam files. Since each bam was sorted by chromosome, I simply looped through each. script