Unconfigured Ad

Collapse
X
 
  • Filter
  • Time
  • Show
Clear All
new posts
  • bioman1
    Member
    • May 2012
    • 80

    mpileup-varscan

    Hi all,
    I have aligned illumina reads to the reference genome using bowtie and then created mpileup file using sam tools. I have used varscan to call variants (SNPS) using mpileup2snp with min coverage 20, min reads2 4, min avg qual 20 and p-value 0.1 settings.I would like to determine heterozygosity & homozygosity.

    I get output from the varscan for some of the contigs repeated more than once showing showing different p-values, var frequency , strand filter, sample homo & sam hetero. I have counted the snps for each contig which shows strand filter-Pass. But I am confused how can i get p-value, var freq for each contig (if it is repeated more than twice)

    Is there any way filter the result in varscan to get values for each unique contig?
  • shyam_la
    Member
    • Mar 2012
    • 97

    #2
    Discussion of next-gen sequencing related bioinformatics: resources, algorithms, open source efforts, etc


    Check this out. It won't answer your question precisely, but will give a better understanding of the parameters in varscan..
    Did you run the mpileup with the -B parameter? Because if you didn't VarScan is bound to give faulty results..

    Comment

    • bioman1
      Member
      • May 2012
      • 80

      #3
      mpileup2snp

      Thanks you..I will try mpileup with -B option..
      I also get different results when I tried mpileup2snp with VCF format turned on/off in the options.

      I get more number of SNPs predicted when I put VCF format output turned on and get lower number of SNPs when I turned off VCF format off. Do u you know why varscan shows different results?

      Comment

      • shyam_la
        Member
        • Mar 2012
        • 97

        #4
        Nope.. My experience with VarScan is very limited. Sorry.

        Comment

        • bioman1
          Member
          • May 2012
          • 80

          #5
          Thanks a lot..now it is fixed.

          Now I get same no of SNPS predicted even when VCF option turned on/off in Varscan, when I create samtools mpileup creation with -B option.

          I hope this helps some one

          Comment

          • dkoboldt
            Member
            • Mar 2009
            • 62

            #6
            Bioman1,

            Thanks for your post, and glad you got it straightened out!

            ~Dan Koboldt

            Comment

            Latest Articles

            Collapse

            • SEQadmin2
              Advanced Sequencing Platforms Tackle Neuroscience’s Toughest Genomics Problems
              by SEQadmin2



              Genomics studies in neuroscience face a special challenge due to the brain’s complexity and scarcity of samples. Mapping changes in cell type and state using conventional next-generation sequencing methods remains challenging. Advances in technologies like single-cell sequencing, spatial transcriptomics, and long-read sequencing have opened the door to deeper studies of the brain and diseases like Alzheimer’s, amyotrophic lateral sclerosis (ALS), and schizophrenia.
              ...
              Yesterday, 11:10 AM
            • SEQadmin2
              Cancer Drug Resistance: The Lingering Barrier to Rising Survival
              by SEQadmin2



              Cancer survival rates have significantly increased in the last few decades in the United States, reaching a combined 70% 5-year survival rate by 2021. Behind this number, there are years of research to find new therapies, drug targets, and early detection methods. But there is one core challenge that keeps slowing down these advances, and it’s about drug resistance.

              There is no single reason why many patients don’t respond to treatment as expected. Cancer is...
              07-08-2026, 05:17 AM
            • GATTACAT
              Reply to Nine Things a Sample Prep Scientist Thinks About Before Sequencing
              by GATTACAT
              Love this - good data definitely starts from good input, and poor input can only give relatively poor data. I particularly like the mention of Nanodrop/absorbance based methods for quantification. It's such a toss up if you'll get an accurate reading or what amounts to a randomly generated number, and a lot of library/sequencing related issues can be traced back to poor quant.
              07-01-2026, 11:43 AM

            ad_right_rmr

            Collapse

            News

            Collapse

            Topics Statistics Last Post
            Started by SEQadmin2, Yesterday, 10:04 AM
            0 responses
            10 views
            0 reactions
            Last Post SEQadmin2  
            Started by SEQadmin2, 07-08-2026, 10:08 AM
            0 responses
            7 views
            0 reactions
            Last Post SEQadmin2  
            Started by SEQadmin2, 07-07-2026, 11:05 AM
            0 responses
            12 views
            0 reactions
            Last Post SEQadmin2  
            Started by SEQadmin2, 07-02-2026, 11:08 AM
            0 responses
            31 views
            0 reactions
            Last Post SEQadmin2  
            Working...