Open hirokomatsui opened 4 years ago
Yes, correct.
On Thu, Nov 7, 2019, 6:33 PM hirokomatsui notifications@github.com wrote:
Hello,
I've read the same topic previously posted, but am still interested in running demuxlet for snATAC-Seq which don't have UMI. Actually I've ran demuxlet for snATAC-Seq sample, and the result looks reasonable. In the source code, you're assigning random UMI for the reads without UMI, then the reads processed. Is that right? If so, I think the behavior of demuxlet does make sense for me.
Thanks! Hiroko Matsui
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Hi,
I also have a similar question regarding to using demuxlet for processing scATAC-seq data.
"In the source code, you're assigning random UMI for the reads without UMI, then the reads processed"
Does this mean demuxlet can handle 10x scATAC-seq data (without UMIs)?
However according to this thread (https://github.com/statgen/demuxlet/issues/45), at present demuxlet couldn't deal with 10x ATAC data yet.
Has the packaged been updated, or still not for 10x ATAC data?
We just ran demuxlet on 10x scATAC-seq data with default settings and got no result (empty output).
Thank you! Guangshuai
you can use it for scATAC-seq data.
On Dec 8, 2019, at 7:56 PM, Guangshuai Jia notifications@github.com wrote:
Hi,
I also have a similar question regarding to using demuxlet for processing scATAC-seq data.
"In the source code, you're assigning random UMI for the reads without UMI, then the reads processed"
Does this mean demuxlet can handle 10x scATAC-seq data (without UMIs)?
However according to this thread (#45 https://github.com/statgen/demuxlet/issues/45), at present demuxlet couldn't deal with 10x ATAC data yet.
Has the packaged been updated, or still not for 10x ATAC data?
Thank you! Guangshuai
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you can use it for scATAC-seq data. …
Thank you! Should I directly use the BAM generated by 10x CellRanger pipeline and default settings of demuxlet?
I just tried but get an empty output file. Do I need to make any modification for 10x ATAC data? (I could successfully run 10x scRNA-seq data.)
The flag for atacseq is different. Anton and George ccd here can chime in.
Sent from a phone. Excuse the typos.
On Dec 9, 2019, at 3:59 AM, Guangshuai Jia notifications@github.com wrote:
you can use it for scATAC-seq data. …
Thank you! Should I directly use the BAM generated by 10x CellRanger pipeline and default settings of demuxlet?
I just tried but get an empty output file. Do I need to make any modification for 10x ATAC data?
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Anton and George
Thank you! Looking forward to Anton and George's help :)
The flag for atacseq is different. Anton and George ccd here can chime in. Sent from a phone. Excuse the typos. … On Dec 9, 2019, at 3:59 AM, Guangshuai Jia @.***> wrote: you can use it for scATAC-seq data. … Thank you! Should I directly use the BAM generated by 10x CellRanger pipeline and default settings of demuxlet? I just tried but get an empty output file. Do I need to make any modification for 10x ATAC data? — You are receiving this because you commented. Reply to this email directly, view it on GitHub, or unsubscribe.
Hi, we are stuck at this step -- to demultiplex pooled 10x scATAC-seq from several clinical samples and looking forward to any kind help.
Could you please kindly tell me what modifications should I do for this purpose, e.g., use a different flag settings?
Any help is appreciated!
Hello,
I've read the same topic previously posted, but am still interested in running demuxlet for snATAC-Seq which don't have UMI. Actually I've ran demuxlet for snATAC-Seq sample, and the result looks reasonable. In the source code, you're assigning random UMI for the reads without UMI, then the reads processed. Is that right? If so, I think the behavior of demuxlet does make sense for me.
Thanks! Hiroko Matsui
Hello Dr. Hiroko Matsui,
Could you please kindly tell me did you do any modifications to run scATAC-seq data using demuxlet? Thank you!
Best regards Guangshuai
Hi! I'm Anton of the 'Anton and George':)
I've created pull request, a README_atac.md
should be in tutorial directory as soon as devs have time to attend to the matter.
But basically:
Demuxlet works for single cell ATACseq data out of the box. In most cases you can use the same .vcf
you would use
for the RNAseq. However, we also recommend using a broader .vcf
file which contains regions from the entire genome.
Try to stick to the best practices of .vcf
filtering as described in the README_vcf.md
.
There are slight adjustments that have to be made with the arguments for the running command.
Specifically, there is no need to specify --tag-UMI
because 10x platform does not have UMI sequence associated with any read.
Of note, tutorial
directory has a BED
file with the sites we used for RNA seq applications (hg19)
Hi, I have been using the program to analyze my sn-ATAC-seq data, but it seems that the stringency of the Demuxlet program is too high, and I detected much more doublets than expected. I even used the data from one sample and detected lots of doublets (2%). do you think it's reasonable to decrease the cutoff? and how can I achieve that? Thank you!
Hi, @Gvaihir thanks for clarifying this!
Has anyone used demuxlet to demultiplex ATAC-seq without genotype data? i.e. would freemuxlet work on ATAC?
Which version of the software should I use, the one in this repo or the demuxlet under popscle ? https://github.com/statgen/popscle/wiki
thank you!
@bio-la - you certainly can. You still need a vcf with allele frequency (can estimate one from the 1kG). Also you will have to stringently filter it because sometimes doublets can be falsely assigned to individuals as singlets if vcf is too large and your read coverage is a bit low. https://github.com/statgen/popscle/wiki has all necessary soft and documentation.
Hello,
I've read the same topic previously posted, but am still interested in running demuxlet for snATAC-Seq which don't have UMI. Actually I've ran demuxlet for snATAC-Seq sample, and the result looks reasonable. In the source code, you're assigning random UMI for the reads without UMI, then the reads processed. Is that right? If so, I think the behavior of demuxlet does make sense for me.
Thanks! Hiroko Matsui