Seqanswers Leaderboard Ad

Collapse

Announcement

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

  • dpryan
    replied
    It won't much matter if you align them separately and then merge or concatenate the files and then align the results (if you have paired-end reads, some aligners re-estimate the insert-size distribution throughout the alignment, so that could change things a bit). Whatever you do, don't create multiple BAM files from the same sample and then treat them as multiple biological samples.

    Leave a comment:


  • guang918
    replied
    Thanks very much for your reply.

    I have one biological sample. And the Illumina sequencing will give me several FASTQ files, 1.fq, 2.fq... If I want to identify SNPs to reference genome, should I align them to genome separately, or combine the sequence first and align them as a single file?

    Thanks a million.

    Leave a comment:


  • dpryan
    replied
    Well, in one case you're calling SNPs on multiple samples and in the other on a single sample with higher depth. I wouldn't expect them to give the same results.

    Leave a comment:


  • guang918
    started a topic samtools help

    samtools help

    Hi,

    I had two Bam (1.bam, 2.bam) files from Bowtie2 and tried to call variants by Samtools. I have tried two procedures and they gave me different answers.

    Procedure #1:
    samtools mpileup -uf reference.fa bam1 bam2 | bcftools view -bvcg - > 12.bcf
    bcftools view 12.bcf | vcfutils.pl varFilter -D100 12.flt.vcf

    Procedure #2:
    samtools merge 12_merged.bam 1.bam 2.bam
    samtools mpileup -uf reference.fa 12_merged.bam | bcftools view -bvcg - > 12_merged.bcf
    bcftools view 12_merged.bcf | vcfutils.pl varFilter -D100 12_merged.vcf

    I can't figure out why. Please give some suggestions.

    Thanks very much. Happy Thanks giving day.

Latest Articles

Collapse

  • seqadmin
    Best Practices for Single-Cell Sequencing Analysis
    by seqadmin



    While isolating and preparing single cells for sequencing was historically the bottleneck, recent technological advancements have shifted the challenge to data analysis. This highlights the rapidly evolving nature of single-cell sequencing. The inherent complexity of single-cell analysis has intensified with the surge in data volume and the incorporation of diverse and more complex datasets. This article explores the challenges in analysis, examines common pitfalls, offers...
    06-06-2024, 07:15 AM

ad_right_rmr

Collapse

News

Collapse

Topics Statistics Last Post
Started by seqadmin, 06-21-2024, 07:49 AM
0 responses
14 views
0 likes
Last Post seqadmin  
Started by seqadmin, 06-20-2024, 07:23 AM
0 responses
14 views
0 likes
Last Post seqadmin  
Started by seqadmin, 06-17-2024, 06:54 AM
0 responses
16 views
0 likes
Last Post seqadmin  
Started by seqadmin, 06-14-2024, 07:24 AM
0 responses
25 views
0 likes
Last Post seqadmin  
Working...
X