6. Alternative Matches

So far, we've seen how to perform very specific matching - literal string matching, using wildcards to match the same thing multiple times, etc - and how to match every substring that fits a particular pattern - e.g. all strings of at least six digits, every line starting or ending with a particular character, etc - but what if we only want to match under a limited number of set circumstances? For an example,consider again the FASTA file introduced in the previous chapter, a sample of which is reproduced below:

>GX3597KLM "Homo sapiens"

>GK9113FGH "Homo sapiens"

>GF7745PUP "Mus musculus"

>GD8332BAG "Homo sapiens"

>GK3091TFB "Mus musculus"

>GK3141YRK "Pan troglodytes"

This FASTA file is huge - containing many tens of thousands of sequences. We would like to know how many sequences belonging to either Pan troglodytes *or* Homo sapiens are contained in the file. We could count the two species separately and add the results together, but what if we wanted the count for three species? Or ten? In this case, it might be better (and would almost certainly be faster) to perform a count using a set of optional matches in a single regular expression.

A set of options for matching in a regex can be defined using the | pipe symbol. For example, to match either 'fish' or 'whale', we can construct the following expression:


So, to match only 'Homo sapiens' or 'Pan troglodytes' in the FASTA file mentioned above, we can construct the regex:

Homo sapiens|Pan troglodytes

which we can then use with grep or some other program to get a count of the matches. You can use this approach to selectively extract lines from a larger file, while preserving their order relative to each other. For example, this can be useful when subsetting a GFF annotation file based on feature type, source, etc.

Exercise 6.1

If you study the contents of the file person_info.csv, you will see that some variation exists in the address formatting. For example, some of the addresses use 'First Street' while others use '1st Street' or some other variation.
Can you find all the lines containing information on a person living on 1st/First Street/street, using a single reglar expression?

Exercise 6.2

The FASTQ file example.fastq contains sequence reads with quality scores, in the format

@sequence header line with barcode sequence
quality scores for basecalls

Unfortunately, the barcode sequences in the header lines are wrong, and the barcodes are still attached to the front of the sequences. There are three barcodes that we are interested in: AGGCCA, TGTGAC, and GCTGAC.

a) how many reads are there in the file for each of these barcodes?

b) write a regular expression that will find and these barcodes and a replacement string that will remove from the start of the sequences in which they are found

c) of course, the format of the file means that you should probably remove the quality scores associated with those sequence positions too. Rewrite your regex so that the barcode sequence AND its corresponding quality scores (i.e. the first six characters on the sequence and quality lines) are removed.

d) finally, can you build on the regex and replacement string from part c), to replace the incorrect index sequences in the header lines with the barcodes for each relevant sequence record?

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