The document describes analyzing data sets of patients diagnosed with Familial Dilated Cardiomyopathy. The analysis involved aligning the data sets to a reference genome, marking duplicates, calling variants using GATK, quality filtering results, annotating variants using Annovar and 1000g project. Familial Dilated Cardiomyopathy is characterized by thinning of the heart muscle and chamber enlargement which can lead to heart failure. More than 30 genes are associated with the condition, with the TTN gene associated with 20% of cases. The next steps outlined are to investigate annotation results, research alternative views on variant relevance, create a script to extract specific filtered results, and prepare a list of around 10 variants stating their details

1. By Tammy Alsop

2. 1. Obtained data sets of patients diagnosed with Familial Dilated
Cardiomyopathy, from European nucleotide archive
2. Ran alignment to a reference genome after finding out which chromosome
my data sets were ran on. (ref genome = human_g1k_v37.fasta)
3. Post alignment processing
4. Marked duplicates
5. Used GATK haplotype caller to call variants
6. Quality filtered the results (summary of alignment and depth of coverage)
7.Annotation using Annovar and 1000g project and then acquired the fastqc
information
8. Picked out some databases and used these for further annotation

3. FAMILIAL DILATED CARDIOMYOPATHY
• Genetic form of heart disease
• Characterised by thinning of cardiac muscle /chamber
(left)
• Can lead to heart failure
• Autosomal dominant inheritance pattern (1 copy of
altered gene)
• Reduced penetrance in some
• Systolic dysfunction and left ventricular enlargement
• Reduction of myocardial force of contraction leading
to reduced cardiac output
More than 30 genes associated with symptoms such as
Arrhythmia, dyspnoea, syncope, oedema and fatigue
Most important gene associated with 20% of cases is TTN
(titin gene)

4. 1. Going to look at results of annotations and investigate what each section means
so that I can filter the variants (starting with Clinvar)
2. Continue to research and find alternative views on gene variant relevance
3. Plan to make a Perl script to pull out specific information from the filtered
results and figure out which variants may be responsible for cardiomyopathy
4. Prepare a list of around 10 if possible stating their chromosome, gene, position,
why they were called, their phenotype, variant class and any reference to the
literature.
Need to consider Prioritisation of variants in the functional filtering script.