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View Code? Open in Web Editor NEWA pipeline to identify pathogenic microorganisms from scRNA-seq raw data.
License: MIT License
A pipeline to identify pathogenic microorganisms from scRNA-seq raw data.
License: MIT License
Hi! First of all, thank you for the amazing tool.
I am processing some scRNA-seq data and I'm getting a lot of hits for Bacillus thuringiensis. It turns out that these reads align with human mithocondrial genes when I run nt-BLAST. Is there a way to filter out these mitochondrial reads that are being classified as bacteria? Thank you.
Hello! It was nice to discover your tool. I was wondering if it is possible to use it on 5' RNA-seq data. What adjustments should be done if you think it is possible ?
Thank you!
Appreciations for your wonderful job in "PathogenTrack and Yeskit: tools for identifying intracellular pathogens from single-cell RNA-sequencing datasets as illustrated by application to COVID-19" !
I noticed that the input of PathogenTrack (count) includes a pair of fastq files (read1 and read2). I wonder how should I use PathogenTrack when a sample has multiple pairs of fastq files?
For example, Sample01_S1_L001_R1_001.fastq.gz, Sample01_S1_L001_R2_001.fastq.gz, Sample01_S1_L002_R1_001.fastq.gz, Sample01_S1_L002_R2_001.fastq.gz.
Best wishes
Hi,
In your paper, I saw that you have analysis on virus.
But this part is missing in the tutorial to run virus detection?
Are there any option that we can switch to call virus?
Regards,
Junyi
Dear PathogenTrack team,
Thanks for your excellent work,
I installed your package and it ran smoothly with your test data.
However, when I used my own data, the Fastq files for read1 and read2 are multiple as below, all the reads belong to one sample HC1. What can I do with my data?
I am very appreciative of your help.
HC1-1_S1_L003_R1_001.fastq.gz HC1-5_S1_L003_R1_001.fastq.gz
HC1-1_S1_L003_R2_001.fastq.gz HC1-5_S1_L003_R2_001.fastq.gz
HC1-2_S1_L003_R1_001.fastq.gz HC1-6_S1_L003_R1_001.fastq.gz
HC1-2_S1_L003_R2_001.fastq.gz HC1-6_S1_L003_R2_001.fastq.gz
HC1-3_S1_L003_R1_001.fastq.gz HC1-7_S1_L003_R1_001.fastq.gz
HC1-3_S1_L003_R2_001.fastq.gz HC1-7_S1_L003_R2_001.fastq.gz
HC1-4_S1_L003_R1_001.fastq.gz HC1-8_S1_L003_R1_001.fastq.gz
HC1-4_S1_L003_R2_001.fastq.gz HC1-8_S1_L003_R2_001.fastq.gz
Question regarding the unclassified reads via Kraken 2, per our previous 16 S analysis with Silva, we try to limit unclassified reads to < 10% however, via Pathogen Track this is coming up between 85-91% including your own tutorial.. Is this worrisome for incomplete capture ?
91.20 15487988 15487988 U 0 unclassified
8.80 1494822 18457 R 1 root
8.69 1476358 23863 R1 131567 cellular organisms
8.55 1452457 0 D 2759 Eukaryota
8.55 1452457 0 D1 33154 Opisthokonta
8.55 1452457 0 K 33208 Metazoa
8.55 1452457 0 K1 6072 Eumetazoa
8.55 1452457 0 K2 33213 Bilateria
8.55 1452457 0 K3 33511 Deuterostomia
8.55
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