Yeah or do a de novo assembly first (before blast). Since it's viral it is not that tough for most computers.
I am doing some annotation work. I am having two sets of genes. Set one is my reference database and set 2 is my query sequence. I did a local blast on an online server. It gives me output similar to that shown in the picture. My query database contains about 10 million reads and is annotated with a large number of reference viruses.
I want to know 2 things:
How many of my query reads match to each reference. The output resembling like X query reads matched to virus Y and X query reads matched to virus alpha and so on. As there are so many reads and so many viruses to which my reads matched. How can I do this in R? Which reads matched to virus. Can you please provide me ready to do commands to work in R.

2 answers
The query IDs look like Illumina read IDs. Instead of the blast approach, I'd go for aligning the reads with Bowtie2, BWA, or BBmap against the combined virus-genomes, you detected. On this alignment, you can do a lot of statistics.
If you import your txt file in R:
df <- read.table("file.txt", sep = "\t", header=T)
you can simply summarize it with the table function:
table(df[,2])
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