Issue merging many large bsseq objects with biscuiteer::unionize() about biscuiteer HOT 5 OPEN

________________________________________ From: deanpettinga <[email protected]> Sent: Sunday, April 19, 2020 10:41 PM To: trichelab/biscuiteer Cc: Subscribed Subject: [External] [trichelab/biscuiteer] Issue merging many large bsseq objects with biscuiteer::unionize() (#25) Working on my first analysis w/ BISCUIT/biscuiteer, but I’ve encountered some issues handling the data. I have 20 gzip/tabix’d VCFs (15-20Gb each) with accompanying bed.gz files. Biscuiteer seems to be working just fine with small/toy datasets. However, I’ve been having issues merging all these samples into a single bsseq object. I think part of the issue is simply due to the large sample number and the amount of data for each sample. I have attempted to solve this issue with two approaches that have failed thus far: 1. biscuiteer::readBiscuit() for each sample individually and then use biscuiteer::unionize() to get a single object. 2. Merge vcf.gz and bed.gz files on the command line and then import together using biscuiteer::readBiscuit() Do you have any advice for a better/ideal approach in this situation? thanks in advance! — You are receiving this because you are subscribed to this thread. Reply to this email directly, view it on GitHub<#25>, or unsubscribe<https://github.com/notifications/unsubscribe-auth/AAABCIRSUFBUXNXOHSW2CMDRNOY5HANCNFSM4MMCHOFA>. CAUTION: This email was sent from outside of the organization ([email protected]). Do not click links or open attachments unless you recognize the sender and know the content is safe. If you have any questions, please contact [email protected]<mailto:[email protected]>.

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________________________________________ From: deanpettinga <[email protected]> Sent: Sunday, April 19, 2020 10:41 PM To: trichelab/biscuiteer Cc: Subscribed Subject: [External] [trichelab/biscuiteer] Issue merging many large bsseq objects with biscuiteer::unionize() (#25) Working on my first analysis w/ BISCUIT/biscuiteer, but I’ve encountered some issues handling the data. I have 20 gzip/tabix’d VCFs (15-20Gb each) with accompanying bed.gz files. Biscuiteer seems to be working just fine with small/toy datasets. However, I’ve been having issues merging all these samples into a single bsseq object. I think part of the issue is simply due to the large sample number and the amount of data for each sample. I have attempted to solve this issue with two approaches that have failed thus far: 1. biscuiteer::readBiscuit() for each sample individually and then use biscuiteer::unionize() to get a single object. 2. Merge vcf.gz and bed.gz files on the command line and then import together using biscuiteer::readBiscuit() Do you have any advice for a better/ideal approach in this situation? thanks in advance! — You are receiving this because you are subscribed to this thread. Reply to this email directly, view it on GitHub<#25>, or unsubscribe<https://github.com/notifications/unsubscribe-auth/AAABCIRSUFBUXNXOHSW2CMDRNOY5HANCNFSM4MMCHOFA>. CAUTION: This email was sent from outside of the organization ([email protected]). Do not click links or open attachments unless you recognize the sender and know the content is safe. If you have any questions, please contact [email protected]<mailto:[email protected]>.

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________________________________________ From: deanpettinga <[email protected]> Sent: Monday, April 20, 2020 11:25 AM To: trichelab/biscuiteer Cc: Tim Triche, Jr.; Comment Subject: [External] Re: [trichelab/biscuiteer] Issue merging many large bsseq objects with biscuiteer::unionize() (#25) Tim, I suppose this isn't so much of an issue as a question, hence, my lack of sessionInfo() and error message. I think the package is working as intended. I was just hoping to understand best-practice when it comes to improving performance/speed. I'll move forward with your suggestion of jointly calling variants with BISCUIT into a single VCF. Feel free to close this issue unless you'd like further info from my experience. thanks much! Dean — You are receiving this because you commented. Reply to this email directly, view it on GitHub<#25 (comment)>, or unsubscribe<https://github.com/notifications/unsubscribe-auth/AAABCISFYNASEP2V3OSNNULRNRSOLANCNFSM4MMCHOFA>. CAUTION: This email was sent from outside of the organization ([email protected]). Do not click links or open attachments unless you recognize the sender and know the content is safe. If you have any questions, please contact [email protected]<mailto:[email protected]>.