Salmon Quant /SubRead featureCounts Results Total Aligments:0
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4 months ago
santos48 ▴ 30

Hello everyone, I have human Rna-Seq data reading by MiniOn.I aligned with the human reference genome (GRCh38.p13) from that website= https://www.gencodegenes.org/human/ using minimap2.

I download annotation from the same website. I used SubRead for quantification and feature count. On the SubRead results, there is a problem with one of the bam files. I aligned again that fastq files with the same reference genome of the first one and same gtf file and also I checked fastq file of second one but I didn't see any problem. Only differences are these bam file has a different barcode

Do you have any suggestions for that problem?

featureCounts -T 8 -a gencode.v38.chr_patch_hapl_scaff.annotation.gtf -g 'transcript_id' -o readcouts.txt bam/*.bam

||    Total alignments : 11214480                                             ||
||    Successfully assigned alignments : 4051945 (36.1%)                      ||
||    Running time : 2.67 minutes

||    Total alignments : 0                                                    ||
||    Successfully assigned alignments : 0                                    ||
||    Running time : 2.89 minutes


Salmon Quant Alignment Based results

salmon quant  --ont -t reference.fa -l A -a first.bam -o salmon_quant1


Total # of mapped reads : 5465357

of uniquely mapped reads : 328808350000000

salmon quant  --ont -t reference.fa -l A -a second.bam -o salmon_quant2


Completed first pass through the alignment file.

Total # of mapped reads : 3843632

of uniquely mapped reads : 2552463

Annotation Genome HG38 Rna-Seq SubRead • 409 views
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Not answering your question but have a suggestion. Take a look at https://github.com/nanoporetech/pipeline-transcriptome-de if you are analyzing RNAseq data on MinION.

Have you looked at your alignments using IGV or some other browser? Are reads aligning to right areas of the genome?

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Actually, I am following that pipeline but I am also trying other tools. I looked at alignments using IGV, it is also true.

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On the SubRead results, there is a problem with one of the bam files.

Are the reads here overlapping multiple genes? Or are the reads short and are multi-mapping and thus not counted? Does QC look similar for two samples?

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It's similar QC reports and both bam files have the same headers. I tried to extract the region of my interest from the second one and tried again Subread feature count now its results 5%. But I need to count whole for differential expression.

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Does anyone have a different idea?

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Show code please, it is completely unclear which command run ran.

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featureCounts -T 8 -a gencode.v38.chr_patch_hapl_scaff.annotation.gtf -g 'transcript_id' -o readcouts.txt bam/*.bam