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How to identify large scale genomic variations

This recipe demonstrates the effects that large scale genomic variations have on the alignments.

1 result • updated 4.5 years ago by Istvan Albert

This recipe demonstrates the effects that large scale genomic variations have on the alignments.

For more information see the

Bioinformatics Data Analysis online course.
Biostar Handbook for system setup and other information.

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# Stop on errors.
set -uex

# The accession number of the genome.
ACC=AF086833

# The number of reads to generate.
COUNT=10000

# The resulting BAM file.
BAM=align.bam

# The name of the reference file.
REF=refs/${ACC}.fa

# The directory for the reference genome.
mkdir -p refs

# Fetch the reference genome from NCBI.
efetch -db nuccore -format fasta -id ${ACC} > $REF

# Index the reference genome for bwa.
bwa index $REF 2>> runlog.txt

# Index the reference genome for IGV.
samtools faidx $REF

# This will be our "real" genome that we will introduce mutations into.
REAL=real.fa

# Create the REAL genome that has the mutation.

# Extract the first 2000 bases.
cat $REF | seqret --filter -sbegin 1 -send 2000 > part1

# Extract the bases from 3000 and on.
cat $REF | seqret --filter -sbegin 3000 > part2

# Combine the two pieces as the "real" genome.
# The net effect is that we lost the 2000-3000 region from the genome.
cat part1 part2 | union -filter  > ${REAL}

# The read pairs that will hold the simulation results.
R1=r1.fq
R2=r2.fq

# Generate sequencing reads.
# We will set other mutation rates to zero so that only our variation is present.
wgsim -e 0 -r 0 -R 0 -N $COUNT ${REAL} ${R1} ${R2} > mutations.txt 2>> runlog.txt

# Align the simulated reads against the genome.
bwa mem ${REF} ${R1} ${R2} 2>> log.txt | samtools sort > ${BAM}

# Index the resulting BAM file.
samtools index ${BAM}

# Generate flag statistics.
samtools flagstat ${BAM} > flagstat.txt

#
# Here are a few other mutations you may want to explore.
# Apply these before the wgsim step then visualize the results.
#

# Experiment 2. Large deletion. Deletion applied from 2000-3000
# cat $REF | seqret --filter -sbegin 1 -send 2000 > part1
# cat $REF | seqret --filter -sbegin 3000 > part2
# cat part1 part2 | union -filter  >  ${REAL}

# Experiment 3. Copy number variation. The first 2000 bases are present three times.
# cat $REF | seqret --filter -sbegin 1 -send 2000 > part1
# cat part1 part1 $REF | union -filter  >  ${REAL}

# Experiment 4. Swap the genome. First 5000 bp  go last.
# cat $REF | seqret --filter -send 5000 > part1
# cat $REF  | seqret --filter -sbegin 5000 > part2
# cat part2 part1 | union -filter  >  ${REAL}

# Experiment 5. Reverse complement a region of the genome (1000 to 2000).
# cat $REF | seqret --filter -sbegin 1 -send 1000 > part1
# cat $REF | seqret --filter -sbegin 1000 -send 2000 -sreverse1 > part2
# cat $REF | seqret --filter -sbegin 2000 > part3
# cat part1 part2 part3 | union -filter  >  ${REAL}

# Experiment 6. Ten unknown mutations, both point and block mutations.
# cat $REF | msbar -filter -count 10 -point 1 -block 1 -minimum 10 -maximum 500 >  ${REAL}

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[acc]
label = "Genome accession number"
display = "TEXTBOX"
value = "AF086833"
regex = "^\\w{1,20}$"
help = "Must be an NCBI accession number"

[N]
label = "The number of reads"
display = "INTEGER"
value = 10000
range = [ 1, 100000,]
help = "How many simulated read pairs to generate."

[settings]
id = 71
recipe_uid = "recipe-variation"
uid = "recipe-variation"
name = "How to identify large scale genomic variations"
template = "How_to_identify_large_scale_genomic_variations_bio-data-analysis_71.sh"
image = "How_to_identify_large_scale_genomic_variations_bio-data-analysis_71.png"
project_uid = "2a988f7f"
url = "http://localhost8000"
help = "This recipe demonstrates the effects that large scale genomic variations have on the alignments.\n\nFor more information see the\n\n* [Bioinformatics Data Analysis][link]  online course.\n* [Biostar Handbook][book] for system setup and other information.\n\n[link]: https://www.biostarhandbook.com/edu/course/4/\n[book]: https://www.biostarhandbook.com"

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