Comments (18)
Hi I have same problem here.
How did you extract that sequence from fastq and determine the start trim point?
do we use R2 fastq for it?
Thank you
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Thanks for your quick reply but in my case they are not in the same position...
Here I looked for my hashtag nucleotide in the raw R2 fastq files, and it turned out like this.
Or did I use wrong fastq file as input?
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Happy to see fellow users help each other.
@dianitasusilo maybe a sliding window approach might help yes: --sliding-window
is the option you are looking for.
@sopenaml Could you check out of your barcodes in R1 are overlapping? It might be a mapping between barcodes similar to totalSeqB.
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Hi Patrick,
I've checked my cite-seq ab barcodes agains R1 and I don't see any matches. If I check my cell hashing barcodes, there's one that finds few (7 ) matches on R1, but the rest none. So it's not that my barcodes are overlapping with cell barcodes. Any other ideas of what the problem may be? Thanks
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Hi,
I have the same problem, where I can grep my HTO out of read 2 but still get 100% reads unmapped. I am running 1.4.5 using Python 3.9. Do we know what the solution to this issue is?
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Hey @sopenaml,
I need to rephrase what I mentioned earlier.
Depending on what chemistry kit you used, it's possible that your R1 barcodes(cell barcodes) linked to one library (GEX, VDJ, ADTs) are linked to one cell barcode and your HTOs are linked to another cell barcode in the same cell.
This means that when you do your overlap, it's going to be very low because the barcodes need to be translated.
Here is the translation matrix.
https://github.com/10XGenomics/cellranger/blob/master/lib/python/cellranger/barcodes/translation/3M-february-2018.txt.gz
Is it a bit clearer?
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Hi everyone,
I am running into an issue, where I do have about ~35% unmapped reads. Is there a way to bring that number up? Grepping the R2 file, shows that start trim needs to be --start-trim 0
I used 10xv3
Attached are the tags
tags.csv
Here is the is what I run to get such output:
CITE-seq-Count -T ${numThreads} \ -R1 ${fastq_path}${nova_id}outs/fastq_path/${fcid}/sham_hto/${outname[$index]}_KS220601_batch1_HTO_${snum[$index]}_L001_R1_001.fastq.gz,${fastq_path}${nova_id}outs/fastq_path/${fcid}/sham_hto/${outname[$index]}_KS220601_batch1_HTO_${snum[$index]}_L002_R1_001.fastq.gz,${fastq_path}${nova_id}outs/fastq_path/${fcid}/sham_hto/${outname[$index]}_KS220601_batch1_HTO_${snum[$index]}_L003_R1_001.fastq.gz,${fastq_path}${nova_id}outs/fastq_path/${fcid}/sham_hto/${outname[$index]}_KS220601_batch1_HTO_${snum[$index]}_L004_R1_001.fastq.gz \ -R2 ${fastq_path}${nova_id}outs/fastq_path/${fcid}/sham_hto/${outname[$index]}_KS220601_batch1_HTO_${snum[$index]}_L001_R2_001.fastq.gz,${fastq_path}${nova_id}outs/fastq_path/${fcid}/sham_hto/${outname[$index]}_KS220601_batch1_HTO_${snum[$index]}_L002_R2_001.fastq.gz,${fastq_path}${nova_id}outs/fastq_path/${fcid}/sham_hto/${outname[$index]}_KS220601_batch1_HTO_${snum[$index]}_L003_R2_001.fastq.gz,${fastq_path}${nova_id}outs/fastq_path/${fcid}/sham_hto/${outname[$index]}_KS220601_batch1_HTO_${snum[$index]}_L004_R2_001.fastq.gz \ -t tags.csv -cbf 1 -cbl 16 -umif 17 -umil 28 -cells 5000 --sliding-window --start-trim 0 \ -o /project/CiteSeq7_sham \
Here is the the output I get:
Date: 2022-07-13
Running time: 6.0 minutes, 37.25 seconds
CITE-seq-Count Version: 1.4.5
Reads processed: 3575668
Percentage mapped: 64
Percentage unmapped: 36
Uncorrected cells: 0
Correction:
Cell barcodes collapsing threshold: 1
Cell barcodes corrected: 16075
UMI collapsing threshold: 2
UMIs corrected: 12836
Run parameters:
Read1_paths: _S17_L004_R1_001.fastq.gz
Read2_paths: _S17_L004_R2_001.fastq.gz
Cell barcode:
First position: 1
Last position: 16
UMI barcode:
First position: 17
Last position: 28
Expected cells: 5000
Tags max errors: 2
Start trim: 0
Thank you in advance!
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I am able to bring the number of mapped reads above 90, by setting --max-error 6 or higher. However, I do not think that is it a good solution as I get plenty of doublets and negatives Doublet 1868 Negative 35 Singlet 394 . Any idea what else I can do?
Thank you!
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Would you be able to send me a sample of your data so that I can run it and have a look?
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I asked for access
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results/unmapped.csv
tag,count
AAGCAGTGGTATCAA,38893
GGGGGGGGGGGGGGG,20759
CCGTACCTCAAAAAA,17644
GCAGTGGTATCAACG,10879
TTCCTGCCAAAAAAA,5855
GTGGTATCAACGCAG,5442
AGCAGTGGTATCAAC,4087
CCGTACCCCAAAAAA,3959
CAGTGGTATCAACGC,3894
It seems pretty reasonable from what I see in the first sample. The unmapped.csv gives you the top sequences that are not mapping. 22% of polyG, means no sequence there or could not be read
Why do you need to get higher?
I want to make sure about the translation issue. Do you have a high overlap between the cells from the RNA side and the HTO?
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Hi, is the translation matrix used only with v3 chemistry? I seem to have a similar problem where grep doesnt return barcodes in my fastq R2 for which I know exist in my data after cellranger. I used the 5' v2 chemistry with gex, vdj and feature barcode libs.
Thanks
Leeana
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Related Issues (20)
- Different "UMIs corrected" results between v1.4.3 and v1.4.5 HOT 2
- Code for running multiple lanes
- ValueError: columns cannot be a set HOT 5
- Python error when there are too many cells? Script never finishes HOT 2
- Cell Hashing on Multiome samples HOT 11
- bug in preprocessing.py -> get_read_paths() (version 1.4.3) HOT 1
- method keeps looking for whitelist when not provided. HOT 8
- 100% unmapped
- Discussion question -- is it normal to take so long? HOT 3
- Include path to tag file in run report HOT 1
- barcodes with 0s in all protein tags and unmapped roll HOT 2
- Running Cite-Seq-count with next GEM protocol HOT 2
- Pandas error after correcting UMIs HOT 1
- Allow to split fastq or get list of readID per cell HOT 2
- Unable to locate temp file while merging results
- Does not compile using Python version > 3.9.x please fix.
- Gene and Antibody both have a pair of fastq files, how to run CITE-seq-Count?
- Please, trim all sequences at the same length.
- CITE-seq-Count run gets stuck HOT 2
- ValueError: columns cannot be a set HOT 3
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