Seqanswers Leaderboard Ad

Collapse

Announcement

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

  • genotype calling & low coverage

    Hi,
    I have a general question concerning genotype calling and thought that maybe some of you have encountered the same problem as me and could give opinion on this. I have a number of sequences, each with reads mapped to it. References come from an assembly of transcriptome from single individual. I would like to call heterozygous sites in each sequence, I don't want to get only a set of most likely SNPs but give the most probable genotype to each site so I could further estimate for example diversity. Unfortunately some parts of sequences have poor coverage. I used samtools and than I ran into some problems (although I think the software doesn’t really matter here, it could be a problem with any software which calls genotypes using probabilistic method). Since the qualities of heterozygotes are much lower than of homozygotes in the same low- covered regions I am hesitant to apply any quality threshold because I will underestimate the diversity. If I apply coverage threshold (take e.g. only sites covered with more than x reads) I may exclude low-expressed sequences in favor of highly expressed sequences and that could also bias the results (and also I will lose a lot of data). On the other hand if I choose the genotype with highest posterior probability I may have quite a lot of false positives especially in low-covered regions. I am not sure if there is the only right solution to this, but maybe I’m missing something that is already taken into account in the model. If anyone has already experienced similar dilemma and has maybe an idea how to properly deal with it I would like to hear it.

Latest Articles

Collapse

  • seqadmin
    Recent Advances in Sequencing Analysis Tools
    by seqadmin


    The sequencing world is rapidly changing due to declining costs, enhanced accuracies, and the advent of newer, cutting-edge instruments. Equally important to these developments are improvements in sequencing analysis, a process that converts vast amounts of raw data into a comprehensible and meaningful form. This complex task requires expertise and the right analysis tools. In this article, we highlight the progress and innovation in sequencing analysis by reviewing several of the...
    05-06-2024, 07:48 AM
  • 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

ad_right_rmr

Collapse

News

Collapse

Topics Statistics Last Post
Started by seqadmin, 05-07-2024, 06:57 AM
0 responses
12 views
0 likes
Last Post seqadmin  
Started by seqadmin, 05-06-2024, 07:17 AM
0 responses
16 views
0 likes
Last Post seqadmin  
Started by seqadmin, 05-02-2024, 08:06 AM
0 responses
22 views
0 likes
Last Post seqadmin  
Started by seqadmin, 04-30-2024, 12:17 PM
0 responses
24 views
0 likes
Last Post seqadmin  
Working...
X