Genome Sequencing Isn't Perfectclick to expand

In “Genome Assembly as Shortest Superstring”, we introduce the problem of assembling a genome from a collection of reads. Even though genome sequencing is a multi-billion dollar enterprise, sequencing machines that identify reads still produce errors a substantial percentage of the time. To make matters worse, these errors are unpredictable; it is difficult to determine if the machine has made an error, let alone where in the read the error has occurred. For this reason, error correction in reads is typically a vital first step in genome assembly.

Problem

As is the case with point mutations, the most common type of sequencing error occurs when a single nucleotide from a read is interpreted incorrectly.

Given: A collection of up to 1000 reads of equal length (at most 50 bp) in FASTA format. Some of these reads were generated with a single-nucleotide error. For each read $s$ in the dataset, one of the following applies:

• $s$ was correctly sequenced and appears in the dataset at least twice (possibly as a reverse complement);
• $s$ is incorrect, it appears in the dataset exactly once, and its Hamming distance is 1 with respect to exactly one correct read in the dataset (or its reverse complement).

Return: A list of all corrections in the form "[old read]->[new read]". (Each correction must be a single symbol substitution, and you may return the corrections in any order.)

Sample Dataset

>Rosalind_52
TCATC
>Rosalind_44
TTCAT
>Rosalind_68
TCATC
>Rosalind_28
TGAAA
>Rosalind_95
GAGGA
>Rosalind_66
TTTCA
>Rosalind_33
ATCAA
>Rosalind_21
TTGAT
>Rosalind_18
TTTCC

Sample Output

TTCAT->TTGAT
GAGGA->GATGA
TTTCC->TTTCA