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Author: danielle-pinto

docs/src/rosalind/10-cons.md

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+# Consensus and Profile
+
+🤔 [Problem link](https://rosalind.info/problems/cons/)
+
+!!! warning "The Problem"
+    A matrix is a rectangular table of values divided into rows and columns.   
+    An m×n matrix has m rows and ncolumns.   
+    Given a matrix A, we write Ai,j.  
+    to indicate the value found at the intersection of row i and column j.  
+
+    Say that we have a collection of DNA strings,   
+    all having the same length n.   
+    Their profile matrix is a 4×n matrix P in which P1,    
+    j represents the number of times that 'A' occurs in the jth position of one of the strings,   
+    P2,j represents the number of times that C occurs in the jth position,   
+    and so on (see below).
+
+    A consensus string c is a string of length n
+    formed from our collection by taking the most common symbol at each position;   
+    the jth symbol of c therefore corresponds to the symbol having the maximum value 
+    in the j-th column of the profile matrix.     
+    Of course, there may be more than one most common symbol, 
+    leading to multiple possible consensus strings.  
+
+    ### DNA Strings
+    A T C C A G C T
+    G G G C A A C T
+    A T G G A T C T
+    A A G C A A C C
+    T T G G A A C T
+    A T G C C A T T
+    A T G G C A C T
+
+    ### Profile
+
+    A   5 1 0 0 5 5 0 0
+	C   0 0 1 4 2 0 6 1
+    G   1 1 6 3 0 1 0 0
+    T   1 5 0 0 0 1 1 6
+
+    Consensus	A T G C A A C T
+
+    Given:     
+    A collection of at most 10 DNA strings of equal length (at most 1 kbp) in FASTA format.
+
+    Return:   
+    A consensus string and profile matrix for the collection. 
+    (If several possible consensus strings exist, then you may return any one of them.)
+
+    Sample Dataset
+    >Rosalind_1
+    ATCCAGCT
+    >Rosalind_2
+    GGGCAACT
+    >Rosalind_3
+    ATGGATCT
+    >Rosalind_4
+    AAGCAACC
+    >Rosalind_5
+    TTGGAACT
+    >Rosalind_6
+    ATGCCATT
+    >Rosalind_7
+    ATGGCACT
+
+    Sample Output
+    ATGCAACT
+    A: 5 1 0 0 5 5 0 0
+    C: 0 0 1 4 2 0 6 1
+    G: 1 1 6 3 0 1 0 0
+    T: 1 5 0 0 0 1 1 6
+
+
+The first thing we will need to do is read in the input fasta.  
+In this case, we will not be reading in a fasta file,   
+but a set of strings in fasta format.   
+Once it is read in, we can iterate over the strings and store the strings in a data matrix.
+
+From there, we can generate the profile matrix.  
+We'll need to sum the number of times each nucleotide appears at a particular row of the data matrix.  
+
+Then, we can identify the most common nucleotide at each column of the data matrix.  
+After we have done this for all columns of the data matrix,   
+we can generate the consensus string.  
+
+It is possible that there can be multiple consensus strings,  
+as some nucleotides may appear the same number of times  
+in each column of the data matrix.  
+If this is the case, we can return multiple consensus strings.
+
+
+```julia
+
+function consensus(fasta)
+    # read in strings in fasta format
+
+    data_matrix = []
+    # iterate over strings and store in matrix
+
+    # make consensus matrix
+
+
+    # make consensus string
+
+
+
+
+
+
+
+
+
+
+
+```