Seqanswers Leaderboard Ad
Collapse
Announcement
Collapse
No announcement yet.
X
-
Detecting alignment collapse
Hi,
I want to check my genome sequence for collapsed, tandemly repeated genes. It seems to me that I could use software for detecting CNVs in that I am looking for significantly increased read depth. CNV-seq requires test and reference sequences, which makes sense to control for sequence-based noise in read depth however I only have my reference genome and one instance of Illumina data. Does anyone have any ideas?
Adam
Comment
-
CNV-seq input file is DNA-seq or RNA-seq?
Originally posted by xiechao View PostCNV-seq, a new method to detect copy number variation using high-throughput sequencing.
more details at BMC Bioinformatics :
Background DNA copy number variation (CNV) has been recognized as an important source of genetic variation. Array comparative genomic hybridization (aCGH) is commonly used for CNV detection, but the microarray platform has a number of inherent limitations. Results Here, we describe a method to detect copy number variation using shotgun sequencing, CNV-seq. The method is based on a robust statistical model that describes the complete analysis procedure and allows the computation of essential confidence values for detection of CNV. Our results show that the number of reads, not the length of the reads is the key factor determining the resolution of detection. This favors the next-generation sequencing methods that rapidly produce large amount of short reads. Conclusion Simulation of various sequencing methods with coverage between 0.1× to 8× show overall specificity between 91.7 – 99.9%, and sensitivity between 72.2 – 96.5%. We also show the results for assessment of CNV between two individual human genomes.
The package is at
http://tiger.dbs.nus.edu.sg/cnv-seq
Comment
-
Originally posted by louis7781x View PostHi,I want to know:CNV-seq input file is DNA-seq or RNA-seq?
CNV-seq input consists in just two files (reference & test) with just two columns each.
First column corresponds to the third column in a BAM file, that is the reference sequence name of the alignment (Chr1, Chr2, ..), the second column is the fourth column of a BAM file, that is the corresponding 1-based leftmost mapping position of that read. Input files can look like this:
1 999
1 1234
1 23456
1 25234
Full explanation of the input, how to get it, how to run CNV-seq, etc:
Jose Flores
Comment
-
Originally posted by roman.sergio View PostHello
Did you already found how to detect the CNV with your data from non control case study?
I am continuing seraching for a solution.
Regards,
Sergio
With CNV-seq in mind and for non-control-case studies you can basically choose whatever reference you want. There might be some issues to worry about like what population the reference you choose come from? or what's the coverage .. It will depend on your purpose and the features of your sample to analyze.
I’ve seen some studies taking the health individual NA10851 from the 1000 genomes data as a control/reference.
ftp://ftp.1000genomes.ebi.ac.uk/vol1/ftp/
Hope can help,
Jose Flores
Comment
-
Originally posted by jflores View PostHi Louis,
CNV-seq input consists in just two files (reference & test) with just two columns each.
First column corresponds to the third column in a BAM file, that is the reference sequence name of the alignment (Chr1, Chr2, ..), the second column is the fourth column of a BAM file, that is the corresponding 1-based leftmost mapping position of that read. Input files can look like this:
1 999
1 1234
1 23456
1 25234
Full explanation of the input, how to get it, how to run CNV-seq, etc:
Jose Flores
Comment
-
Hi,
how to view the level of a gene in CNV-seq ?
Script :
samtools view Patient_test/Parsed_X/chr17.fa/bam/sorted.bam | perl -lane 'print "$F[2]\t$F[3]"' > test.hits
samtools view Patient_ref/Parsed_X/chr17.fa/bam/sorted.bam | perl -lane 'print "$F[2]\t$F[3]"' > ref.hits
perl cnv-seq.pl --test test.hits --ref ref.hits --genome chrom17
data <- read.delim("test.hits-vs-ref.hits.log2-0.6.pvalue-0.001.minw-4.cnv")
cnv.print(data)
cnv.summary(data)
plot.cnv(data)
ggsave("sample.pdf")
[IMG]/home/labo/Sample1.pdf[/IMG]
Regards
Comment
-
Hi Tonio,
You can plot specific coordinates and try to infer from that if your gene of interest has or not gain/loss of copies.
Script :
samtools view Patient_test/Parsed_X/chr17.fa/bam/sorted.bam | perl -lane 'print "$F[2]\t$F[3]"' > test.hits
samtools view Patient_ref/Parsed_X/chr17.fa/bam/sorted.bam | perl -lane 'print "$F[2]\t$F[3]"' > ref.hits
perl cnv-seq.pl --test test.hits --ref ref.hits --genome chrom17
data <- read.delim("test.hits-vs-ref.hits.log2-0.6.pvalue-0.001.minw-4.cnv"))
plot.cnv.chr(data, chromosome=NA, from=NA, to=NA)
... For more options about plotting using CNV-seq you can have a look at the cnv.R file
Regards,
Rodrigo
Comment
-
Dear all,
I have a couple of questions regarding CNV-seq.
I am having a play around with some DNA sequencing that is from custom capture. I have analysed some BAM files using the program. Some work fine, but some file combinations come up with an error, which is strange as all the data has been produced and analysed in exactly the same way. The error is;
"Can't use an undefined value as an ARRAY reference at /share/apps/cnv-seq_1.0/bin/cnv-seq.pl line 204, <REF> line 6460211."
I think this is some kind of Perl script error??
Also does anyone have any experience of using capture data with CNV-seq? any advice would be greatly appreciated.
Thanks for you help
Comment
-
Dear xiechao,
I am trying to use CNV-seq for 36 length Read size simulated data. I am not detecting any CNV.
While for the same data with 76bp Read Length, CNV-seq detects CNV.
Is the read length hard coded in the script?
Is there a way to use CNV-seq on 36 length read data.
Thanking you,
pg
Comment
-
Originally posted by louis7781x View PostThanks for your help,I want to know the input type because the coverage of DNA-seq and RNA-seq is different.So if I use RNA-seq aligned to ref genome and use output file bam to run CNV-seq,Does it apply to analyze copy number varivation?
Comment
Latest Articles
Collapse
-
by seqadmin
The field of immunogenetics explores how genetic variations influence immune responses and susceptibility to disease. In a recent SEQanswers webinar, Oscar Rodriguez, Ph.D., Postdoctoral Researcher at the University of Louisville, and Ruben Martínez Barricarte, Ph.D., Assistant Professor of Medicine at Vanderbilt University, shared recent advancements in immunogenetics. This article discusses their research on genetic variation in antibody loci, antibody production processes,...-
Channel: Articles
11-06-2024, 07:24 PM -
-
by seqadmin
Next-generation sequencing (NGS) and quantitative polymerase chain reaction (qPCR) are essential techniques for investigating the genome, transcriptome, and epigenome. In many cases, choosing the appropriate technique is straightforward, but in others, it can be more challenging to determine the most effective option. A simple distinction is that smaller, more focused projects are typically better suited for qPCR, while larger, more complex datasets benefit from NGS. However,...-
Channel: Articles
10-18-2024, 07:11 AM -
ad_right_rmr
Collapse
News
Collapse
Topics | Statistics | Last Post | ||
---|---|---|---|---|
Started by seqadmin, Today, 11:09 AM
|
0 responses
22 views
0 likes
|
Last Post
by seqadmin
Today, 11:09 AM
|
||
Started by seqadmin, Today, 06:13 AM
|
0 responses
20 views
0 likes
|
Last Post
by seqadmin
Today, 06:13 AM
|
||
Started by seqadmin, 11-01-2024, 06:09 AM
|
0 responses
30 views
0 likes
|
Last Post
by seqadmin
11-01-2024, 06:09 AM
|
||
New Model Aims to Explain Polygenic Diseases by Connecting Genomic Mutations and Regulatory Networks
by seqadmin
Started by seqadmin, 10-30-2024, 05:31 AM
|
0 responses
21 views
0 likes
|
Last Post
by seqadmin
10-30-2024, 05:31 AM
|
Comment