Seqanswers Leaderboard Ad

Collapse

Announcement

Collapse
No announcement yet.
X
 
  • Filter
  • Time
  • Show
Clear All
new posts

  • Dindel stage 3 issue

    HI,
    I have 2 question on DINDEL please.
    I am using DINDEL to identify short indels from ILLUMINA NextGen data generated from a custom pull down experiment. I have used exons from 34 genes to design 60pb baits library (custom library from agilent) , pulled down genomic DNA form diseased and normal samples with this library, and went through ILUMINA hiseq.
    Because of the small size of the pull down library , I have a very good coverage on my targets regions, when I calculate the coverage/baits , this is an example of coverage ( minimum 10000 reads per 60pb bait)
    Min. 1st Qu. Median Mean 3rd Qu. Max.
    0 10460 14220 13680 17590 30920

    I have used dindel-1.01. Reduced the bam to my target regions using samtools view command, and indexed the ref and the bam files.
    stage 1 ok:
    dindel --analysis getCIGARindels --bamFile sample.bam \
    --outputFile sample.dindel_output --ref ref.fa
    stage 2 OK ( realignment windows) using makeWindows.py. I create 18 windows form this point.
    Q1-stage 3 issue(first question)
    dindel-1.01 --analysis indels --doDiploid --bamFile / --ref / --varFile / --libFile / --outputFile /'
    causes problems may be due to my high coverage (?). this is the kind of error I get
    ##skipped Chr9 6032047 reason: error_above_read_count_threshold
    ##skipped Chr9 6032047 reason: error_above_read_count_threshold
    I have seen that there is a reads count options with --maxRead which is set to 10000 at the moment. Is that too small for very high coverage data? Is that Ok to push this up?

    Q2-Another question , I have 2 set of data, sample with disease and sample with no disease ( from the same individual). Is there a way to use the no disease sample as a reference to ignore those indels in the disease samples ( I hope I am making sense )

    many thanks

Latest Articles

Collapse

  • seqadmin
    Essential Discoveries and Tools in Epitranscriptomics
    by seqadmin




    The field of epigenetics has traditionally concentrated more on DNA and how changes like methylation and phosphorylation of histones impact gene expression and regulation. However, our increased understanding of RNA modifications and their importance in cellular processes has led to a rise in epitranscriptomics research. “Epitranscriptomics brings together the concepts of epigenetics and gene expression,” explained Adrien Leger, PhD, Principal Research Scientist...
    04-22-2024, 07:01 AM
  • seqadmin
    Current Approaches to Protein Sequencing
    by seqadmin


    Proteins are often described as the workhorses of the cell, and identifying their sequences is key to understanding their role in biological processes and disease. Currently, the most common technique used to determine protein sequences is mass spectrometry. While still a valuable tool, mass spectrometry faces several limitations and requires a highly experienced scientist familiar with the equipment to operate it. Additionally, other proteomic methods, like affinity assays, are constrained...
    04-04-2024, 04:25 PM

ad_right_rmr

Collapse

News

Collapse

Topics Statistics Last Post
Started by seqadmin, 04-25-2024, 11:49 AM
0 responses
19 views
0 likes
Last Post seqadmin  
Started by seqadmin, 04-24-2024, 08:47 AM
0 responses
17 views
0 likes
Last Post seqadmin  
Started by seqadmin, 04-11-2024, 12:08 PM
0 responses
62 views
0 likes
Last Post seqadmin  
Started by seqadmin, 04-10-2024, 10:19 PM
0 responses
60 views
0 likes
Last Post seqadmin  
Working...
X