A comprehensive investigation of genomic variants in Prostate Cancer reveals 30 regulatory variants with possible functional impact

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Table of Contents

• Description
• How To Use
• Author Info

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Description

Our pipeline utilized Prostate cancer related GWAS SNPs from GWAS Catalog , somatic point mutations and copy number variations from ICGC consortia . We then applied two different strategies that show in Supplementary figure S1 to detect hotspot regions from somatic mutation and copy number variation. These genomic variants (hotspot somatic mutation, CNVRs, and SNP) are then investigated to know the exact position of these genomic variants in the human genome. In the next step, our method integrates Hi-C data with enhancer mark (H3k27ac) to detect variants that are more likely to be regulatory variants. Finally, whole-genome sequencing of prostate cell lines can be used to approve the last genomic variants and report a list of functional variants.

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How To Use

Step 1: Identification of Hotspot regions

A. Hotspot somatic mutation(script Window-analysis):

Input file:

1. Somatic Mutations:

Mutation files contain all somatic mutations in the study in text format. text file should be tab delimited with the following 6 columns: 1. Chr: Chromosome information of Somatic mutation 2. Start: starting position of Somatic mutation 3. End: Ending position of Somatic mutation 4. Ref: Reference allele 5. Alt: Alternate allele 6. ID: Sample ID

Example text file:

Chr	start	End	Ref	Alt	ID
13	109318342	109318342	G	A	SA328537

Output files:

For each chromosome, two CSV file in the below format are generated:

Chr	start	End	Ref	Alt	ID	WindowNumber	#Sample
13	109318342	109318342	G	G	SA328537	5205635	1

Chr	Start	End	Ref	Alt	ID	WindowNumber	#Sample	P-value
13	109318342	109318342	G	G	SA328537	5205635	1	0.1

Furthermore, our pipeline generates two CSV files merging the information of all chromosomes.

Setting argument:

length_window: 21

can be set by other window length such as 9,50,5000bp

B. Copy number variation region:

Input files:

In order to process the CNV dataset, our pipleine requires two files as following:

1. significant cnvrs:

Chr	Start	End
1	6742281	6742903

2. Number: contains the number of samples in each cnvrs

Chr	#Sample	Start	End
1	15	6742281	6742903

3. intersect: list of interscted cnvrs with cnvs

Chr	Start	End	Chr	Start	End	Sample-ID
1	6742281	6742903	1	3652763	7562825	SP112877

Output file:

Selected cnvrs:

ID	#sample	start	Cluster-NO	Score	result(0/1)
chr1:16543346-16577163	21	16543346	1	225.86	0

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Step 2: Determining Functional variants

2.1. Whole genome sequencing data processing (script WGS)

Input files:

Fastq files:

Line	Description
1	Always begins with ‘@’ and then information about the read
2	The actual DNA sequence
3	Always begins with a ‘+’ and sometimes the same info in line 1
4	Has a string of characters which represent the quality scores; must have same number of characters as line 2

Output file:

1. SNP:

Chr	Pos	ID	REF	ALT	QUAL	FILTER	INFO	FORMAT
1	16533	.	C	T	118	PASS	DP=61;VDB=0.262654;SGB=-0.692352;RPB=0.965576;MQB=0.933072;MQSB=0.311291;BQB=0.541042;MQ0F=0.180328;ICB=1;HOB=0.5;AC=1;AN=2;DP4=16,20,16,5;MQ=21	GT:PL 0/1:151,0,243

column	info
Chr	Chromosome information
Pos	position where the variation occurs
REF	reference genotype
ALT	sample genotype
QUAL	Phred-scaled probability that the observed variant exists at this site
FILTER	a . if no quality filters have been applied, PASS if a filter is passed
INFO	lists in order the metrics presented in the final column

2. Indel:

Chr	Pos	ID	REF	ALT	QUAL	FILTER	INFO	FORMAT
6	13609052	.	GAAA	GAA	179	.	INDEL;IDV=11;IMF=0.916667;DP=12;VDB=0.974316;SGB=-0.676189;MQSB=0.95494;MQ0F=0;AC=2;AN=2;DP4=0,1,7,4;MQ=60	GT:PL 1/1:206,4,0

2.2. Identifying H3K27ac ChIP-seq peak regions (Script Chip-seq)

Input file:

Fastq files for ChIP-seq peak regions:

Line	Description
1	Always begins with ‘@’ and then information about the read
2	The actual DNA sequence
3	Always begins with a ‘+’ and sometimes the same info in line 1
4	Has a string of characters which represent the quality scores; must have same number of characters as line 2

Output file:

H3k27ac file:

Chr	Strat	End	Score
1	9750	10800	0089

Author Info

In case of queries, please email: mahdieh.labani@gmail.com

Reference

Please consider citing the follow paper when you use this code.
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