And example of the iSNV data that comes out of the variant_calling_pipeline.
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a data frame with 24 rows and 33 variables.
The Id of the indexed sample for sequencing - can be multiple Id/ SPECID
The average MapQ of reads with the variant
The average Phred of the variant base
The average position of the variant base on the read
Chromosome - genomic segment
The coverage of the plasmid control at the position in the reverse read
The coverage of the plasmid control at the position in the forward read
The coverage of the sample at the position in the reverse read
The coverage of the sample at the position in the forward read
Frequency of the variant
mutation as chr_refPosVar
The number of variant bases in the plasmid control in the reverse read
The number of variant bases in the plasmid control in the forwad read
The number of variant bases in the sample in the reverse read
The number of variant bases in sample in the forward read
DeepSNV p.val
position on genomic segment
Uncorrected deepSNV p.val
nucleotide in the plasmid control
Estimated variance of frequency measurement
nucleotide in the sample
The sequencing run the sample was on
A list of the open reading frames overlapping this position
A list of the positions relative to the start of the in the ORs
Reference amino acid - either sample or plasmid consensus depending on pipeline variables
Codon of the ORs - a list
Variant amino acid
List of variant classifications in each relative OR
Sample ID used in processing - akin to SPECID
Sequencing sample duplicate - if applicable
Total coverage at this position
Position in concatenated genome - segments in the order used in alignment fasta file
genome copy/ul of sample
@source data-raw/variants.R
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