/
esl_distance.c
1782 lines (1578 loc) · 70.3 KB
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esl_distance.c
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/* Pairwise identities, distances, and distance matrices.
*
* Contents:
* 1. Pairwise distances for aligned text sequences.
* 2. Pairwise distances for aligned digital seqs.
* 3. Distance matrices for aligned text sequences.
* 4. Distance matrices for aligned digital sequences.
* 5. Average pairwise identity for multiple alignments.
* 6. Private (static) functions.
* 7. Unit tests.
* 8. Test driver.
* 9. Example.
*/
#include <esl_config.h>
#include <ctype.h>
#include <string.h>
#include <math.h>
#include "easel.h"
#include "esl_alphabet.h"
#include "esl_dmatrix.h"
#include "esl_random.h"
#include "esl_distance.h"
/* Forward declaration of our static functions.
*/
static int jukescantor(int n1, int n2, int alphabet_size, double *opt_distance, double *opt_variance);
/*****************************************************************
* 1. Pairwise distances for aligned text sequences.
*****************************************************************/
/* Function: esl_dst_CPairId()
* Synopsis: Pairwise identity of two aligned text strings.
* Incept: SRE, Mon Apr 17 20:06:07 2006 [St. Louis]
*
* Purpose: Calculates pairwise fractional identity between two
* aligned character strings <asq1> and <asq2>.
* Return this distance in <opt_pid>; return the
* number of identities counted in <opt_nid>; and
* return the denominator <MIN(len1,len2)> in
* <opt_n>.
*
* Alphabetic symbols <[a-zA-Z]> are compared
* case-insensitively for identity. Any nonalphabetic
* character is assumed to be a gap symbol.
*
* This simple comparison rule is unaware of synonyms and
* degeneracies in biological alphabets. For a more
* sophisticated and biosequence-aware comparison, use
* digitized sequences and the <esl_dst_XPairId()> function
* instead. Note that currently <esl_dst_XPairId()> does
* not correctly handle degeneracies, but is set up to.
*
* Args: as1 - aligned character string 1
* as2 - aligned character string 2
* opt_pid - optRETURN: pairwise identity, 0<=x<=1
* opt_nid - optRETURN: # of identities
* opt_n - optRETURN: denominator MIN(len1,len2)
*
* Returns: <eslOK> on success. <opt_pid>, <opt_nid>, <opt_n>
* contain the answers (for whichever were passed non-NULL).
*
* Throws: <eslEINVAL> if the strings are different lengths
* (not aligned).
*/
int
esl_dst_CPairId(const char *as1, const char *as2, double *opt_pid, int *opt_nid, int *opt_n)
{
int nid; /* total identical positions */
int len1, len2; /* lengths of seqs */
int i; /* position in aligned seqs */
int status;
nid = len1 = len2 = 0;
for (i = 0; as1[i] != '\0' && as2[i] != '\0'; i++)
{
if (isalpha(as1[i])) len1++;
if (isalpha(as2[i])) len2++;
if (isalpha(as1[i]) && isalpha(as2[i])
&& toupper(as1[i]) == toupper(as2[i]))
nid++;
}
len1 = ESL_MIN(len1, len2);
if (as1[i] != '\0' || as2[i] != '\0')
ESL_XEXCEPTION(eslEINVAL, "strings not same length, not aligned");
if (opt_pid != NULL) *opt_pid = ( len1==0 ? 0. : (double) nid / (double) len1);
if (opt_nid != NULL) *opt_nid = nid;
if (opt_n != NULL) *opt_n = len1;
return eslOK;
ERROR:
if (opt_pid != NULL) *opt_pid = 0.;
if (opt_nid != NULL) *opt_nid = 0;
if (opt_n != NULL) *opt_n = 0;
return status;
}
/* Function: esl_dst_CPairMatch()
* Synopsis: Pairwise matches of two aligned text strings.
* Incept: ER, Wed Oct 29 09:02:35 EDT 2014 [janelia]
*
* Purpose: Calculates pairwise fractional matches between two aligned
* character strings <asq1> and <asq2>, in the pairHMM
* sense, where a match state M is any aligned residue pair
* (not necessarily an identity), and I and D are X- and -X
* singlets.
*
* Return the fraction of matches, M / (M+I+D), in
* <opt_pmatch>; return the number of matches M counted in
* <opt_nmatch>; and return the denominator M+I+D, which is
* <alen - double_gaps>, in <*opt_n>.
*
* Alphabetic symbols <[a-zA-Z]> are compared
* case-insensitively for identity. Any nonalphabetic
* character is assumed to be a gap symbol.
*
* This simple comparison rule is unaware of synonyms and
* degeneracies in biological alphabets. For a more
* sophisticated and biosequence-aware comparison, use
* digitized sequences and the <esl_dst_XPairMatch()> function
* instead. Note that currently <esl_dst_XPairMatch()> does
* not correctly handle degeneracies, but is set up to.
*
* Args: as1 - aligned character string 1
* as2 - aligned character string 2
* opt_pm - optRETURN: fraction of M states, M/(M+D+I) [0..1]
* opt_nm - optRETURN: # of match states, M
* opt_n - optRETURN: denominator alen - double_gaps, M+D+1
*
* Returns: <eslOK> on success. <opt_pm>, <opt_nm>, <opt_n>
* contain the answers (for whichever were passed non-NULL).
*
* Throws: <eslEINVAL> if the strings are different lengths
* (not aligned).
*/
int
esl_dst_CPairMatch(const char *as1, const char *as2, double *opt_pm, int *opt_nm, int *opt_n)
{
int nm; // total matched positions
int len; // length of alignment (no double gaps)
int i; // position in aligned seqs
int status;
nm = len = 0;
for (i = 0; as1[i] != '\0' && as2[i] != '\0'; i++)
{
if (isalpha(as1[i]) || isalpha(as2[i])) len++;
if (isalpha(as1[i]) && isalpha(as2[i])) nm++;
}
if (as1[i] != '\0' || as2[i] != '\0')
ESL_XEXCEPTION(eslEINVAL, "strings not same length, not aligned");
if (opt_pm) *opt_pm = ( len==0 ? 0. : (double)nm / (double)len);
if (opt_nm) *opt_nm = nm;
if (opt_n) *opt_n = len;
return eslOK;
ERROR:
if (opt_pm) *opt_pm = 0.;
if (opt_nm) *opt_nm = 0;
if (opt_n) *opt_n = 0;
return status;
}
/* Function: esl_dst_CJukesCantor()
* Synopsis: Jukes-Cantor distance for two aligned strings.
* Incept: SRE, Tue Apr 18 14:00:37 2006 [St. Louis]
*
* Purpose: Calculate the generalized Jukes-Cantor distance between
* two aligned character strings <as1> and <as2>, in
* substitutions/site, for an alphabet of <K> residues
* (<K=4> for nucleic acid, <K=20> for proteins). The
* maximum likelihood estimate for the distance is
* optionally returned in <opt_distance>. The large-sample
* variance for the distance estimate is
* optionally returned in <opt_variance>.
*
* Alphabetic symbols <[a-zA-Z]> are compared
* case-insensitively to count the number of identities
* (<n1>) and mismatches (<n2>>). Any nonalphabetic
* character is assumed to be a gap symbol, and aligned
* columns containing gap symbols are ignored. The
* fractional difference <D> used to calculate the
* Jukes/Cantor distance is <n2/n1+n2>.
*
* Args: K - size of the alphabet (4 or 20)
* as1 - 1st aligned seq, 0..L-1, \0-terminated
* as2 - 2nd aligned seq, 0..L-1, \0-terminated
* opt_distance - optRETURN: ML estimate of distance d
* opt_variance - optRETURN: large-sample variance of d
*
* Returns: <eslOK> on success.
*
* Infinite distances are possible, in which case distance
* and variance are both <HUGE_VAL>. Caller has to deal
* with this case as it sees fit, perhaps by enforcing
* an arbitrary maximum distance.
*
* Throws: <eslEINVAL> if the two strings aren't the same length (and
* thus can't have been properly aligned).
* <eslEDIVZERO> if no aligned residues were counted.
* On either failure, distance and variance are both returned
* as <HUGE_VAL>.
*/
int
esl_dst_CJukesCantor(int K, const char *as1, const char *as2,
double *opt_distance, double *opt_variance)
{
int n1, n2; /* number of observed identities, substitutions */
int i; /* position in aligned seqs */
int status;
n1 = n2 = 0;
for (i = 0; as1[i] != '\0' && as2[i] != '\0'; i++)
{
if (isalpha(as1[i]) && isalpha(as2[i]))
{
if (toupper(as1[i]) == toupper(as2[i])) n1++; else n2++;
}
}
if (as1[i] != '\0' || as2[i] != '\0')
ESL_XEXCEPTION(eslEINVAL, "strings not same length, not aligned");
return jukescantor(n1, n2, K, opt_distance, opt_variance); /* can throw eslEDIVZERO */
ERROR:
if (opt_distance != NULL) *opt_distance = HUGE_VAL;
if (opt_variance != NULL) *opt_variance = HUGE_VAL;
return status;
}
/*------- end, pairwise distances for aligned text seqs ---------*/
/*****************************************************************
* 2. Pairwise distances for aligned digitized sequences.
*****************************************************************/
/* Function: esl_dst_XPairId()
* Synopsis: Pairwise identity of two aligned digital seqs.
* Incept: SRE, Tue Apr 18 09:24:05 2006 [St. Louis]
*
* Purpose: Digital version of <esl_dst_CPairId()>: <ax1> and
* <ax2> are digitized aligned sequences, in alphabet
* <abc>.
*
* Only exactly matching codes count as identities;
* canonical residues, of course, but also IUPAC degeneracy
* codes. (YY is an identity; YC is not.) It would be more
* sophisticated to use <esl_abc_Match()> to handle
* degeneracies, but doing that would require that
* <opt_nid> be changed to an expectation, and a double.
*
* Args: abc - digital alphabet in use
* ax1 - aligned digital seq 1
* ax2 - aligned digital seq 2
* opt_pid - optRETURN: pairwise identity, 0<=x<=1
* opt_nid - optRETURN: # of identities
* opt_n - optRETURN: denominator MIN(len1,len2)
*
* Returns: <eslOK> on success. <opt_pid>, <opt_nid>, <opt_n>
* contain the answers, for any of these that were passed
* non-<NULL> pointers.
*
* Throws: <eslEINVAL> if the strings are different lengths (not aligned).
*/
int
esl_dst_XPairId(const ESL_ALPHABET *abc, const ESL_DSQ *ax1, const ESL_DSQ *ax2,
double *opt_pid, int *opt_nid, int *opt_n)
{
int nid; /* total identical positions */
int len1, len2; /* lengths of seqs */
int i; /* position in aligned seqs */
int status;
nid = len1 = len2 = 0;
for (i = 1; ax1[i] != eslDSQ_SENTINEL && ax2[i] != eslDSQ_SENTINEL; i++)
{
if (esl_abc_XIsResidue(abc, ax1[i])) len1++;
if (esl_abc_XIsResidue(abc, ax2[i])) len2++;
if (esl_abc_XIsResidue(abc, ax1[i]) && esl_abc_XIsResidue(abc, ax2[i]) && ax1[i] == ax2[i]) nid++; // IUPAC degen only counts as identity if code exactly matches
}
len1 = ESL_MIN(len1, len2);
if (ax1[i] != eslDSQ_SENTINEL || ax2[i] != eslDSQ_SENTINEL)
ESL_XEXCEPTION(eslEINVAL, "strings not same length, not aligned");
if (opt_pid) *opt_pid = ( len1==0 ? 0. : (double) nid / (double) len1 );
if (opt_nid) *opt_nid = nid;
if (opt_n) *opt_n = len1;
return eslOK;
ERROR:
if (opt_pid) *opt_pid = 0.;
if (opt_nid) *opt_nid = 0;
if (opt_n) *opt_n = 0;
return status;
}
/* Function: esl_dst_XPairMatch()
* Synopsis: Pairwise matches of two aligned digital seqs.
* Incept: ER, Wed Oct 29 09:09:07 EDT 2014 [janelia]
*
* Purpose: Digital version of <esl_dst_CPairMatch()>: <ax1> and
* <ax2> are digitized aligned sequences, in alphabet
* <abc>.
*
* IUPAC degeneracy codes count as residues both in
* counting match (XX residue/residue) and delete/insert
* (X-, -X) states.
*
* Args: abc - digital alphabet in use
* ax1 - aligned digital seq 1
* ax2 - aligned digital seq 2
* opt_pm - optRETURN: pairwise fractional match states, M/(M+D+I), 0<=x<=1
* opt_nm - optRETURN: # of match states, M
* opt_n - optRETURN: denominator alen-double_gaps, (M+D+I)
*
* Returns: <eslOK> on success. <opt_pm>, <opt_nm>, <opt_n>
* contain the answers, for any of these that were passed
* non-<NULL> pointers.
*
* Throws: <eslEINVAL> if the strings are different lengths (not aligned).
*/
int
esl_dst_XPairMatch(const ESL_ALPHABET *abc, const ESL_DSQ *ax1, const ESL_DSQ *ax2, double *opt_pm, int *opt_nm, int *opt_n)
{
int nm; // total matched positions
int len; // length of alignment (no double gaps)
int i; // position in aligned seqs
int status;
nm = len = 0;
for (i = 1; ax1[i] != eslDSQ_SENTINEL && ax2[i] != eslDSQ_SENTINEL; i++)
{
if (esl_abc_XIsResidue(abc, ax1[i]) || esl_abc_XIsResidue(abc, ax2[i])) len++;
if (esl_abc_XIsResidue(abc, ax1[i]) && esl_abc_XIsResidue(abc, ax2[i])) nm++;
}
if (ax1[i] != eslDSQ_SENTINEL || ax2[i] != eslDSQ_SENTINEL)
ESL_XEXCEPTION(eslEINVAL, "strings not same length, not aligned");
if (opt_pm) *opt_pm = ( len==0 ? 0. : (double)nm / (double)len );
if (opt_nm) *opt_nm = nm;
if (opt_n) *opt_n = len;
return eslOK;
ERROR:
if (opt_pm) *opt_pm = 0.;
if (opt_nm) *opt_nm = 0;
if (opt_n) *opt_n = 0;
return status;
}
/* Function: esl_dst_XJukesCantor()
* Synopsis: Jukes-Cantor distance for two aligned digitized seqs.
* Incept: SRE, Tue Apr 18 15:26:51 2006 [St. Louis]
*
* Purpose: Calculate the generalized Jukes-Cantor distance between two
* aligned digital strings <ax1> and <ax2>, in substitutions/site,
* using alphabet <abc> to evaluate identities and differences.
* The maximum likelihood estimate for the distance is optionally returned in
* <opt_distance>. The large-sample variance for the distance
* estimate is optionally returned in <opt_variance>.
*
* Identical to <esl_dst_CJukesCantor()>, except that it takes
* digital sequences instead of character strings.
*
* Args: abc - bioalphabet to use for comparisons
* ax1 - 1st digital aligned seq
* ax2 - 2nd digital aligned seq
* opt_distance - optRETURN: ML estimate of distance d
* opt_variance - optRETURN: large-sample variance of d
*
* Returns: <eslOK> on success. As in <esl_dst_CJukesCantor()>, the
* distance and variance may be infinite, in which case they
* are returned as <HUGE_VAL>.
*
* Throws: <eslEINVAL> if the two strings aren't the same length (and
* thus can't have been properly aligned).
* <eslEDIVZERO> if no aligned residues were counted.
* On either failure, the distance and variance are set
* to <HUGE_VAL>.
*/
int
esl_dst_XJukesCantor(const ESL_ALPHABET *abc, const ESL_DSQ *ax1, const ESL_DSQ *ax2, double *opt_distance, double *opt_variance)
{
int n1, n2; // number of observed identities, substitutions
int i; // position in aligned seqs
int status;
n1 = n2 = 0;
for (i = 1; ax1[i] != eslDSQ_SENTINEL && ax2[i] != eslDSQ_SENTINEL; i++)
{
if (esl_abc_XIsCanonical(abc, ax1[i]) && esl_abc_XIsCanonical(abc, ax2[i]))
{
if (ax1[i] == ax2[i]) n1++;
else n2++;
}
}
if (ax1[i] != eslDSQ_SENTINEL || ax2[i] != eslDSQ_SENTINEL)
ESL_XEXCEPTION(eslEINVAL, "strings not same length, not aligned");
return jukescantor(n1, n2, abc->K, opt_distance, opt_variance);
ERROR:
if (opt_distance) *opt_distance = HUGE_VAL;
if (opt_variance) *opt_variance = HUGE_VAL;
return status;
}
/*---------- end pairwise distances, digital seqs --------------*/
/*****************************************************************
* 3. Distance matrices for aligned text sequences.
*****************************************************************/
/* Function: esl_dst_CPairIdMx()
* Synopsis: NxN identity matrix for N aligned text sequences.
* Incept: SRE, Thu Apr 27 08:46:08 2006 [New York]
*
* Purpose: Given a multiple sequence alignment <as>, consisting
* of <N> aligned character strings; calculate
* a symmetric fractional pairwise identity matrix by $N(N-1)/2$
* calls to <esl_dst_CPairId()>, and return it in
* <opt_D>.
*
* Args: as - aligned seqs (all same length), [0..N-1]
* N - # of aligned sequences
* ret_S - RETURN: symmetric fractional identity matrix
*
* Returns: <eslOK> on success, and <ret_S> contains the fractional
* identity matrix. Caller free's <S> with
* <esl_dmatrix_Destroy()>.
*
* Throws: <eslEINVAL> if a seq has a different
* length than others. On failure, <ret_D> is returned <NULL>
* and state of inputs is unchanged.
*
* <eslEMEM> on allocation failure.
*/
int
esl_dst_CPairIdMx(char **as, int N, ESL_DMATRIX **opt_S)
{
ESL_DMATRIX *S = NULL;
int status;
int i,j;
if (( S = esl_dmatrix_Create(N,N) ) == NULL) { status = eslEMEM; goto ERROR; }
for (i = 0; i < N; i++)
{
S->mx[i][i] = 1.;
for (j = i+1; j < N; j++)
{
status = esl_dst_CPairId(as[i], as[j], &(S->mx[i][j]), NULL, NULL);
if (status != eslOK)
ESL_XEXCEPTION(status, "Pairwise identity calculation failed at seqs %d,%d\n", i,j);
S->mx[j][i] = S->mx[i][j];
}
}
if (opt_S) *opt_S = S; else esl_dmatrix_Destroy(S);
return eslOK;
ERROR:
esl_dmatrix_Destroy(S);
if (opt_S) *opt_S = NULL;
return status;
}
/* Function: esl_dst_CDiffMx()
* Synopsis: NxN difference matrix for N aligned text sequences.
* Incept: SRE, Fri Apr 28 06:27:20 2006 [New York]
*
* Purpose: Same as <esl_dst_CPairIdMx()>, but calculates
* the fractional difference <d=1-s> instead of the
* fractional identity <s> for each pair.
*
* Args: as - aligned seqs (all same length), [0..N-1]
* N - # of aligned sequences
* opt_D - RETURN: symmetric fractional difference matrix
*
* Returns: <eslOK> on success, and <opt_D> contains the
* fractional difference matrix. Caller free's <D> with
* <esl_dmatrix_Destroy()>.
*
* Throws: <eslEINVAL> if any seq has a different
* length than others. On failure, <opt_D> is returned <NULL>
* and state of inputs is unchanged.
*/
int
esl_dst_CDiffMx(char **as, int N, ESL_DMATRIX **opt_D)
{
ESL_DMATRIX *D = NULL;
int status;
int i,j;
if ((status = esl_dst_CPairIdMx(as, N, &D)) != eslOK) goto ERROR;
for (i = 0; i < N; i++)
{
D->mx[i][i] = 0.;
for (j = i+1; j < N; j++)
{
D->mx[i][j] = 1. - D->mx[i][j];
D->mx[j][i] = D->mx[i][j];
}
}
if (opt_D) *opt_D = D; else esl_dmatrix_Destroy(D);
return eslOK;
ERROR:
esl_dmatrix_Destroy(D);
if (opt_D) *opt_D = NULL;
return status;
}
/* Function: esl_dst_CJukesCantorMx()
* Synopsis: NxN Jukes/Cantor distance matrix for N aligned text seqs.
* Incept: SRE, Tue Apr 18 16:00:16 2006 [St. Louis]
*
* Purpose: Given a multiple sequence alignment <aseq>, consisting of
* <nseq> aligned character sequences in an alphabet of
* <K> letters (usually 4 for DNA, 20 for protein);
* calculate a symmetric Jukes/Cantor pairwise distance
* matrix for all sequence pairs, and optionally return the distance
* matrix in <ret_D>, and optionally return a symmetric matrix of the
* large-sample variances for those ML distance estimates
* in <ret_V>.
*
* Infinite distances (and variances) are possible; they
* are represented as <HUGE_VAL> in <D> and <V>. Caller must
* be prepared to deal with them as appropriate.
*
* Args: K - size of the alphabet (usually 4 or 20)
* as - aligned sequences [0.nseq-1][0..L-1]
* N - number of aseqs
* opt_D - optRETURN: [0..nseq-1]x[0..nseq-1] symmetric distance mx
* opt_V - optRETURN: matrix of variances.
*
* Returns: <eslOK> on success. <D> and <V> contain the
* distance matrix (and variances); caller frees these with
* <esl_dmatrix_Destroy()>.
*
* Throws: <eslEINVAL> if any pair of sequences have differing lengths
* (and thus cannot have been properly aligned).
* <eslEDIVZERO> if some pair of sequences had no aligned
* residues. On failure, <D> and <V> are both returned <NULL>
* and state of inputs is unchanged.
*
* <eslEMEM> on allocation failure.
*/
int
esl_dst_CJukesCantorMx(int K, char **as, int N, ESL_DMATRIX **opt_D, ESL_DMATRIX **opt_V)
{
ESL_DMATRIX *D = NULL;
ESL_DMATRIX *V = NULL;
int i,j;
int status;
if (( D = esl_dmatrix_Create(N, N) ) == NULL) { status = eslEMEM; goto ERROR; }
if (( V = esl_dmatrix_Create(N, N) ) == NULL) { status = eslEMEM; goto ERROR; }
for (i = 0; i < N; i++)
{
D->mx[i][i] = 0.;
V->mx[i][i] = 0.;
for (j = i+1; j < N; j++)
{
if ((status = esl_dst_CJukesCantor(K, as[i], as[j], &(D->mx[i][j]), &(V->mx[i][j]))) != eslOK)
ESL_XEXCEPTION(status, "J/C calculation failed at seqs %d,%d", i,j);
D->mx[j][i] = D->mx[i][j];
V->mx[j][i] = V->mx[i][j];
}
}
if (opt_D) *opt_D = D; else esl_dmatrix_Destroy(D);
if (opt_V) *opt_V = V; else esl_dmatrix_Destroy(V);
return eslOK;
ERROR:
esl_dmatrix_Destroy(D);
esl_dmatrix_Destroy(V);
if (opt_D) *opt_D = NULL;
if (opt_V) *opt_V = NULL;
return status;
}
/*----------- end, distance matrices for aligned text seqs ---------*/
/*****************************************************************
* 4. Distance matrices for aligned digital sequences.
*****************************************************************/
/* Function: esl_dst_XPairIdMx()
* Synopsis: NxN identity matrix for N aligned digital seqs.
* Incept: SRE, Thu Apr 27 09:08:11 2006 [New York]
*
* Purpose: Given a digitized multiple sequence alignment <ax>, consisting
* of <N> aligned digital sequences in alphabet <abc>; calculate
* a symmetric pairwise fractional identity matrix by $N(N-1)/2$
* calls to <esl_dst_XPairId()>, and return it in <ret_S>.
*
* Args: abc - digital alphabet in use
* ax - aligned dsq's, [0..N-1][1..alen]
* N - number of aligned sequences
* opt_S - RETURN: NxN matrix of fractional identities
*
* Returns: <eslOK> on success, and <opt_S> contains the distance
* matrix. Caller is obligated to free <S> with
* <esl_dmatrix_Destroy()>.
*
* Throws: <eslEINVAL> if a seq has a different
* length than others. On failure, <opt_S> is returned <NULL>
* and state of inputs is unchanged.
*
* <eslEMEM> on allocation failure.
*/
int
esl_dst_XPairIdMx(const ESL_ALPHABET *abc, ESL_DSQ **ax, int N, ESL_DMATRIX **opt_S)
{
ESL_DMATRIX *S = NULL;
int i,j;
int status;
if (( S = esl_dmatrix_Create(N,N) ) == NULL) { status = eslEMEM; goto ERROR; }
for (i = 0; i < N; i++)
{
S->mx[i][i] = 1.;
for (j = i+1; j < N; j++)
{
status = esl_dst_XPairId(abc, ax[i], ax[j], &(S->mx[i][j]), NULL, NULL);
if (status != eslOK)
ESL_XEXCEPTION(status, "Pairwise identity calculation failed at seqs %d,%d\n", i,j);
S->mx[j][i] = S->mx[i][j];
}
}
if (opt_S) *opt_S = S; else esl_dmatrix_Destroy(S);
return eslOK;
ERROR:
esl_dmatrix_Destroy(S);
if (opt_S) *opt_S = NULL;
return status;
}
/* Function: esl_dst_XDiffMx()
* Synopsis: NxN difference matrix for N aligned digital seqs.
* Incept: SRE, Fri Apr 28 06:37:29 2006 [New York]
*
* Purpose: Same as <esl_dst_XPairIdMx()>, but calculates fractional
* difference <1-s> instead of fractional identity <s> for
* each pair.
*
* Args: abc - digital alphabet in use
* ax - aligned dsq's, [0..N-1][1..alen]
* N - number of aligned sequences
* opt_D - RETURN: NxN matrix of fractional differences
*
* Returns: <eslOK> on success, and <opt_D> contains the difference
* matrix; caller is obligated to free <D> with
* <esl_dmatrix_Destroy()>.
*
* Throws: <eslEINVAL> if a seq has a different
* length than others. On failure, <opt_D> is returned <NULL>
* and state of inputs is unchanged.
*/
int
esl_dst_XDiffMx(const ESL_ALPHABET *abc, ESL_DSQ **ax, int N, ESL_DMATRIX **opt_D)
{
ESL_DMATRIX *D = NULL;
int i,j;
int status;
if ((status = esl_dst_XPairIdMx(abc, ax, N, &D)) != eslOK) goto ERROR;
for (i = 0; i < N; i++)
{
D->mx[i][i] = 0.;
for (j = i+1; j < N; j++)
{
D->mx[i][j] = 1. - D->mx[i][j];
D->mx[j][i] = D->mx[i][j];
}
}
if (opt_D) *opt_D = D; else esl_dmatrix_Destroy(D);
return eslOK;
ERROR:
esl_dmatrix_Destroy(D);
if (opt_D) *opt_D = NULL;
return status;
}
/* Function: esl_dst_XJukesCantorMx()
* Synopsis: NxN Jukes/Cantor distance matrix for N aligned digital seqs.
* Incept: SRE, Thu Apr 27 08:38:08 2006 [New York City]
*
* Purpose: Given a digitized multiple sequence alignment <ax>,
* consisting of <nseq> aligned digital sequences in
* bioalphabet <abc>, calculate a symmetric Jukes/Cantor
* pairwise distance matrix for all sequence pairs;
* optionally return the distance matrix in <ret_D> and
* a matrix of the large-sample variances for those ML distance
* estimates in <ret_V>.
*
* Infinite distances (and variances) are possible. They
* are represented as <HUGE_VAL> in <D> and <V>. Caller must
* be prepared to deal with them as appropriate.
*
* Args: abc - bioalphabet for <aseq>
* ax - aligned digital sequences [0.nseq-1][1..L]
* N - number of aseqs
* opt_D - optRETURN: [0..nseq-1]x[0..nseq-1] symmetric distance mx
* opt_V - optRETURN: matrix of variances.
*
* Returns: <eslOK> on success. <opt_D> and <opt_V>, if provided, contain the
* distance matrix and variances. Caller frees these with
* <esl_dmatrix_Destroy()>.
*
* Throws: <eslEINVAL> if any pair of sequences have differing lengths
* (and thus cannot have been properly aligned).
* <eslEDIVZERO> if some pair of sequences had no aligned
* residues. On failure, <opt_D> and <opt_V> are both returned <NULL>
* and state of inputs is unchanged.
*
* <eslEMEM> on allocation failure.
*/
int
esl_dst_XJukesCantorMx(const ESL_ALPHABET *abc, ESL_DSQ **ax, int N, ESL_DMATRIX **opt_D, ESL_DMATRIX **opt_V)
{
ESL_DMATRIX *D = NULL;
ESL_DMATRIX *V = NULL;
int status;
int i,j;
if (( D = esl_dmatrix_Create(N, N) ) == NULL) { status = eslEMEM; goto ERROR; }
if (( V = esl_dmatrix_Create(N, N) ) == NULL) { status = eslEMEM; goto ERROR; }
for (i = 0; i < N; i++)
{
D->mx[i][i] = 0.;
V->mx[i][i] = 0.;
for (j = i+1; j < N; j++)
{
if ((status = esl_dst_XJukesCantor(abc, ax[i], ax[j], &(D->mx[i][j]), &(V->mx[i][j]))) != eslOK)
ESL_XEXCEPTION(status, "J/C calculation failed at digital aseqs %d,%d", i,j);
D->mx[j][i] = D->mx[i][j];
V->mx[j][i] = V->mx[i][j];
}
}
if (opt_D) *opt_D = D; else esl_dmatrix_Destroy(D);
if (opt_V) *opt_V = V; else esl_dmatrix_Destroy(V);
return eslOK;
ERROR:
esl_dmatrix_Destroy(D);
esl_dmatrix_Destroy(V);
if (opt_D) *opt_D = NULL;
if (opt_V) *opt_V = NULL;
return status;
}
/*------- end, distance matrices for digital alignments ---------*/
/*****************************************************************
* 5. Average pairwise identity for multiple alignments
*****************************************************************/
/* Function: esl_dst_CAverageId()
* Synopsis: Calculate avg identity for multiple alignment
* Incept: SRE, Fri May 18 15:02:38 2007 [Janelia]
*
* Purpose: Calculates the average pairwise fractional identity in
* a multiple sequence alignment <as>, consisting of <N>
* aligned character sequences of identical length.
*
* If an exhaustive calculation would require more than
* <max_comparisons> pairwise comparisons, then instead of
* looking at all pairs, calculate the average over a
* stochastic sample of <max_comparisons> random pairs.
* This allows the routine to work efficiently even on very
* deep MSAs.
*
* Each fractional pairwise identity (range $[0..$ pid $..1]$
* is calculated using <esl_dst_CPairId()>.
*
* Returns: <eslOK> on success, and <*opt_avgid> contains the average
* fractional identity.
*
* Throws: <eslEMEM> on allocation failure.
* <eslEINVAL> if any of the aligned sequence pairs aren't
* of the same length.
* In either case, <*opt_avgid> is set to 0.
*/
int
esl_dst_CAverageId(char **as, int N, int max_comparisons, double *opt_avgid)
{
ESL_RANDOMNESS *rng = NULL;
double avgid = 0.;
double id;
int i,j,k;
int status;
if (N <= 1) // by convention, with no pairwise comparisons for N=0|1, set pid = 1.0
{
avgid = 1.0;
}
else if (N <= max_comparisons && // if N is small enough that we can average exhaustively over all pairwise comparisons...
N <= sqrt(2. * max_comparisons) && // (beware numerical overflow of N^2)
(N * (N-1) / 2) <= max_comparisons)
{
for (i = 0; i < N; i++)
for (j = i+1; j < N; j++)
{
if ((status = esl_dst_CPairId(as[i], as[j], &id, NULL, NULL)) != eslOK) return status;
avgid += id;
}
avgid /= (double) (N * (N-1) / 2);
}
else // If nseq is large, calculate average over a stochastic sample.
{
if (( rng = esl_randomness_Create(42) ) == NULL) { status = eslEMEM; goto ERROR; } // fixed seed, suppress stochastic variation
for (k = 0; k < max_comparisons; k++)
{
do { i = esl_rnd_Roll(rng, N); j = esl_rnd_Roll(rng, N); } while (j == i); // make sure j != i
if ((status = esl_dst_CPairId(as[i], as[j], &id, NULL, NULL)) != eslOK) return status;
avgid += id;
}
avgid /= (double) max_comparisons;
}
esl_randomness_Destroy(rng);
if (opt_avgid) *opt_avgid = avgid;
return eslOK;
ERROR:
esl_randomness_Destroy(rng);
if (opt_avgid) *opt_avgid = 0.;
return status;
}
/* Function: esl_dst_CAverageMatch()
* Synopsis: Calculate avg matches for multiple alignment
* Incept: ER, Wed Oct 29 09:25:09 EDT 2014 [Janelia]
*
* Purpose: Calculates the average pairwise fractional matches M/(M+D+I) in
* a multiple sequence alignment <as>, consisting of <N>
* aligned character sequences of identical length. M,D,I
* are in the pair-HMM state sense: M means any aligned pair,
* including both mismatches and identities.
*
* If an exhaustive calculation would require more than
* <max_comparisons> pairwise comparisons, then instead of
* looking at all pairs, calculate the average over a
* stochastic sample of <max_comparisons> random pairs.
* This allows the routine to work efficiently even on very
* deep MSAs.
*
* Each fractional pairwise matches (range $[0..$ pm $..1]$
* is calculated using <esl_dst_CPairMatch()>.
*
* Returns: <eslOK> on success, and <*ret_avgpm> contains the average
* fractional matches.
*
* Throws: <eslEMEM> on allocation failure.
* <eslEINVAL> if any of the aligned sequence pairs aren't
* of the same length.
* In either case, <*ret_avgpm> is set to 0.
*/
int
esl_dst_CAverageMatch(char **as, int N, int max_comparisons, double *opt_avgpm)
{
ESL_RANDOMNESS *rng = NULL;
double avgpm = 0.;
double pmatch;
int i,j,k;
int status;
if (N <= 1) // Edge case: a single sequence by itself has no pairwise comparisons
{ // Set a convention of id = 1.0 for the case of no pairwise comparisons
avgpm = 1.0;
}
else if (N <= max_comparisons && // Is N small enough that we can average over all pairwise comparisons?
N <= sqrt(2. * max_comparisons) && // Watch out for numerical overflow in this: for large MSAs, N(N-1)/2 can overflow.
(N * (N-1) / 2) <= max_comparisons)
{
for (i = 0; i < N; i++)
for (j = i+1; j < N; j++)
{
if ((status = esl_dst_CPairMatch(as[i], as[j], &pmatch, NULL, NULL)) != eslOK) return status;
avgpm += pmatch;
}
avgpm /= (double) (N * (N-1) / 2);
}
else /* If nseq is large, calculate average over a stochastic sample. */
{
if (( rng = esl_randomness_Create(42) ) == NULL) { status = eslEMEM; goto ERROR; } // fixed seed, suppress stochastic variation
for (k = 0; k < max_comparisons; k++)
{
do { i = esl_rnd_Roll(rng, N); j = esl_rnd_Roll(rng, N); } while (j == i); // make sure j != i
if ((status = esl_dst_CPairMatch(as[i], as[j], &pmatch, NULL, NULL)) != eslOK) return status;
avgpm += pmatch;
}
avgpm /= (double) max_comparisons;
}
esl_randomness_Destroy(rng);
if (opt_avgpm) *opt_avgpm = avgpm;
return eslOK;
ERROR:
esl_randomness_Destroy(rng);
if (opt_avgpm) *opt_avgpm = 0.;
return status;
}
/* Function: esl_dst_XAverageId()
* Synopsis: Calculate avg identity for digital MSA
* Incept: SRE, Fri May 18 15:19:14 2007 [Janelia]
*
* Purpose: Calculates the average pairwise fractional identity in
* a digital multiple sequence alignment <ax>, consisting of <N>
* aligned digital sequences of identical length.
*
* If an exhaustive calculation would require more than
* <max_comparisons> pairwise comparisons, then instead of
* looking at all pairs, calculate the average over a
* stochastic sample of <max_comparisons> random pairs.
* This allows the routine to work efficiently even on very
* deep MSAs.
*
* Each fractional pairwise identity (range $[0..$ pid $..1]$
* is calculated using <esl_dst_XPairId()>.
*
* Returns: <eslOK> on success, and <*ret_id> contains the average
* fractional identity.
*
* Throws: <eslEMEM> on allocation failure.
* <eslEINVAL> if any of the aligned sequence pairs aren't
* of the same length.
* In either case, <*ret_id> is set to 0.
*/
int
esl_dst_XAverageId(const ESL_ALPHABET *abc, ESL_DSQ **ax, int N, int max_comparisons, double *opt_avgid)
{
ESL_RANDOMNESS *rng = NULL;
double avgid = 0.;
double id;
int i,j,k;
int status;
if (N <= 1) // Edge case: a single sequence by itself has no pairwise comparisons
{ // Set a convention of id = 1.0 for the case of no pairwise comparisons
avgid = 1.;
}
else if (N <= max_comparisons && // Is N small enough that we can average over all pairwise comparisons?
N <= sqrt(2. * max_comparisons) && // Watch out for numerical overflow in this: for large MSAs, N(N-1)/2 can overflow.
(N * (N-1) / 2) <= max_comparisons)
{
for (i = 0; i < N; i++)
for (j = i+1; j < N; j++)
{
if ((status = esl_dst_XPairId(abc, ax[i], ax[j], &id, NULL, NULL)) != eslOK) return status;
avgid += id;
}
avgid /= (double) (N * (N-1) / 2);
}
else /* If nseq is large, calculate average over a stochastic sample. */
{
if (( rng = esl_randomness_Create(42) ) == NULL) { status = eslEMEM; goto ERROR; } // fixed seed, suppress stochastic variation
for (k = 0; k < max_comparisons; k++)
{
do { i = esl_rnd_Roll(rng, N); j = esl_rnd_Roll(rng, N); } while (j == i); // make sure j != i
if ((status = esl_dst_XPairId(abc, ax[i], ax[j], &id, NULL, NULL)) != eslOK) return status;