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  • bw.
    replied
    @swbarnes2 cool. never realized there was a difference.

    @oyvindbusk thanks, I also tried this and ended up with similar thresholds (male < 40% and female > 50%). I didn't try to filter out pseudoautosomal regions since their coordinates differ across species and assembly versions (based on PAR coordinates at:


    ).


    Looking at 322 CCLE samples, 233 were called Male, 73 Female, and 10 Unknown (which is >= 40% and <= 50%). Out of the 233 Male, only 5 would have been called differently with your thresholds. I will see if I can check the thresholds against a different approach. Also, a lot of the CCLE cells have copy number amplifications / deletions, so these results might be skewed by that.

    Here is the distribution of nHet / nHomo for chrX in CCLE samples (I used this instead of nHet/(nHet+nHomo)). The 2 vertical blue lines are equivalent to 40% and 50% thresholds, and the 30% threshold is the red line.

    Last edited by bw.; 02-12-2014, 11:48 PM.

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  • swbarnes2
    replied
    Gender = biological sex + culture. You don't care about people's gender, you care about their sex. (And even the biology is not black and white 100% of the time)

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  • oyvindbusk
    replied
    How about using % heterozygosity on X (without the pseudoautosomal regions (X:60000-2699520 and X:154931043-155260560). In our lab, male = < 30 % and female = > 50 %.

    Leave a comment:


  • bw.
    replied
    Testing sex determination with CCLE samples

    I've tried using [num reads mapped to chrX] / [num reads mapped to chrY]
    to determine sex in some CCLE exome-seq samples. The ratios turned out to be:

    9.4 -- s1
    304.6 -- s2
    272.9 -- s3
    168.3 -- s4
    220.6 -- s5
    297.8 -- s6
    226.1 -- s7
    257.1 -- s8
    241.9 -- s9
    287.0 -- s10
    278.6 -- s11
    260.3 -- s12
    9.7 -- s13
    8.7 -- s14
    261.2 -- s15
    279.3 -- s16
    9.0 -- s17
    8.5 -- s18
    260.7 -- s19
    297.4 -- s20
    8.7 -- s21
    261.8 -- s22
    189.0 -- s23
    147.4 -- s24
    291.2 -- s25
    So it looks like the difference is pretty wide -
    [num reads mapped to chrX] / [num reads mapped to chrY] is < 10 for all male samples and > 100 for all female samples.

    Still, I'm not sure whether these thresholds are stable across exome-seq kits, gene panels, etc. I wonder if there's a more robust way to determine sex.
    Last edited by bw.; 02-13-2014, 11:07 AM.

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  • husamia
    replied
    I also use the average depth of X and Y

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  • balaji
    replied
    in plink there is an option to check sex using X chr, I hope you are looking for this..
    plink --bfile data --impute-sex --make-bed --out newfile

    Leave a comment:


  • LiLin
    replied
    The average sequencing depth of chrY and chrX

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  • xied75
    replied
    But I have pure female reads that can map a lot Y?

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  • jgibbons1
    replied
    I would second that -- map reads against a panel of Y-chromosome genes/exons.

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  • vivek_
    replied
    To verify pedigree this post might help:

    The Center for Public Health Genomics at UVA is focused on translational and personalized medicine — moving gene discovery into the delivery of health care.


    To check gender, may be you could check the number of aligned reads to Y chromsome?

    Leave a comment:


  • kjaja
    started a topic gender check using sequencing data

    gender check using sequencing data

    Hi All,

    I have exome sequencing data from siblings and would like to confirm their gender and relationship using genetics to make sure they are in fact siblings. I also want to confirm that the gender information is correct. Are there tools out there that can do this using exome seq data?

    Thanks,

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