Functions to Work with BLAST Output Files

Share:

Description

Read and filter BLAST tabular output files, make taxonomic identifications of the BLAST hits using gi numbers, write trimmed-down BLAST files.

Usage

1
2
3
4
5
6
  read.blast(file, similarity = 30, evalue = 1e-5, max.hits = 1, 
    min.length = NA, quiet = FALSE)
  id.blast(blast, gi.taxid, taxid.names, min.taxon = 0, 
    min.query = 0, min.phylum = 0, take.first = TRUE)
  write.blast(blast, outfile)
  def2gi(def)

Arguments

file

character, name of BLAST tabular output file

similarity

numeric, hits above this similarity score are kept

evalue

character, hits below this E value are kept

max.hits

numeric, up to this many hits are kept for each query sequence

min.length

numeric, hits with at least this alignment length are kept

quiet

logical, produce fewer messages?

blast

dataframe, BLAST table

gi.taxid

list, first component is sequence identifiers (gi numbers), second is taxon ids (taxids)

taxid.names

dataframe, with at least columns taxid (taxon id), phylum (name of phylum), species (name of species)

min.taxon

numeric, this taxon is kept if it makes up at least this fraction of total

min.query

numeric, query sequence is counted if a single phylum makes up this fraction of its hits

min.phylum

numeric, this phylum is kept if it makes up at least this fraction of total

take.first

logical, keep only first hit after all other filtering steps?

outfile

character, name of output file

def

character, FASTA defline(s)

Details

read.blast reads a BLAST (Altschul et al., 1997) tabular output file (such as generated using the -m 8 switch to the ‘blastall’ command), keeping only those hits with greater than or equal to similarity and less than or equal to evalue (expectation value). Furthermore, for each query sequence, only the top number of hits specified by max.hits are kept, and only hits with an alignment length of at least min.length are kept. One or more of these filters can be disabled by setting similarity, evalue and/or max.hits to NA.

id.blast takes a BLAST table (i.e., the output of read.blast) and finds the taxonomic ID, phylum and species name for each hit (subject sequence). The BLAST results are tied to taxids using gi.taxid, which is a list consisting of gi and taxid numeric vectors. Any subject sequence identifiers appearing in the BLAST file that do not match gi numbers in the gi.taxid list are dropped. The taxid.names dataframe lists the phylum and species names for each taxid.

id.blast furthermore performs three possible filtering steps, which are all disabled by default. If one or more of the arguments is set to a non-zero value, its operation is performed, in this order. Any taxon that does not initially make up at least the fraction of total hits given by min.taxon is removed. Any query sequence that does not have a single phylum making up at least the fraction of hits (for each query sequence) given by min.query is removed. Finally, any phylum that does not make up at least the fraction of total hits given by min.phylum is removed.

By default, for take.first equal to TRUE, id.blast performs a final filtering step (but min.query must be disabled). Only the first hit for each query sequence is kept.

write.blast takes a BLAST table (the output of read.blast) and writes to outfile a stripped-down BLAST file with empty values in the columns except for columns 1 (query sequence ID), 2 (hit sequence ID), 3 (similarity), 11 (E value). In the process, def2gi is used to extract the GI numbers for the hit sequences that are then kept in the second column. This function is used to reduce the size of the example BLAST files that are packaged with CHNOSZ (see the ‘bison’ section in extdata).

def2gi extracts the GI number from a FASTA defline.

Value

read.blast returns a dataframe with as many columns (12) as the BLAST file. id.blast returns a dataframe with columns query, subject (i.e., sequence id or gi number), similarity, evalue, taxid, phylum and species. write.blast invisible-y returns the results (that are also written to outfile).

References

Altschul, S. F., Madden, T. L., Schaffer, A. A., Zhang, J. H., Zhang, Z., Miller, W. and Lipman, D. J. (1997) Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 25, 3389–3402. http://dx.doi.org/doi:10.1093/nar/25.17.3389

See Also

The extdata/refseq directory contains the taxid_names.csv.xz file for microbial taxa, which can be used for the taxid.names in id.blast.

Examples

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
## using def2gi
def <- "gi|218295810|ref|ZP_03496590.1|"
stopifnot(all.equal(def2gi(def), "218295810"))

## process some of the BLAST output for proteins
## from Bison Pool metagenome (JGI, 2007)
# read the file that connects taxids with the sequence identifier
tfile <- system.file("extdata/bison/gi.taxid.txt.xz", package="CHNOSZ")
gi.taxid <- scan(tfile, what=as.list(character(2)), flush=TRUE)
# read the file that connects names with the taxids
nfile <- system.file("extdata/refseq/taxid_names.csv.xz", package="CHNOSZ")
taxid.names <- read.csv(nfile)
# the BLAST files
sites <- c("N","S","R","Q","P")
bfile <- paste("extdata/bison/bison", sites, "_vs_refseq57.blastp.xz", sep="")
for(i in 1:5) {
  file <- system.file(bfile[i], package="CHNOSZ")
  # read the blast file, with default filtering settings
  bl <- read.blast(file)
  # process the blast file -- get taxon names
  ib <- id.blast(bl, gi.taxid, taxid.names, min.taxon=2^-7)
  # count each of the phyla
  bd <- as.matrix(sapply(unique(ib$phylum), function(x) (sum(x==ib$phylum))))
  colnames(bd) <- sites[i]
  # make a matrix -- each column for a different file
  if(i==1) bardata <- bd else {
    bardata <- merge(bardata, bd, all=TRUE, by="row.names")
    rownames(bardata) <- bardata$Row.names
    bardata <- bardata[,-1]
  }
}
# normalize the counts
bardata[is.na(bardata)] <- 0
bardata <- t(t(bardata)/colSums(bardata))
# make a bar chart
bp <- barplot(as.matrix(bardata), col=rainbow(nrow(bardata)),
  xlab="location", ylab="fractional abundance")
# add labels to the bars
names <- substr(row.names(bardata), 1, 3)
for(i in 1:5) {
  bd <- bardata[,i]
  ib <- bd!=0
  y <- (cumsum(bd) - bd/2)[ib]
  text(bp[i], y, names[ib])
}
title(main=paste("Phylum Classification of Protein Sequences",
  "in Part of the Bison Pool Metagenome", sep="\n"))

Want to suggest features or report bugs for rdrr.io? Use the GitHub issue tracker.