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1c02f0c Bio.sequtils and Bio.SeqUtils were duplicated code, and even worse were ...
chapmanb authored
1 This file provides documentation for modules in Biopython that have been moved
2 or deprecated in favor of other modules. This provides some quick and easy
3 to find documentation about how to update your code to work again.
4
2669c4d - Updates to move from Numeric python to NumPy. Python modules have back...
chapmanb authored
5 Numeric support
6 ===============
76300d6 @peterjc Updates include deprecation of Martel/Mindy
peterjc authored
7 Following the release of 1.48, Numeric support in Biopython is discontinued.
8 Limited support is still available for python modules via back compatible
9 imports, but C modules will not work. Please move to NumPy.
2669c4d - Updates to move from Numeric python to NumPy. Python modules have back...
chapmanb authored
10
fb76593 @peterjc Labelling Martel and Bio.Mindy as obsolete, updating the news about this...
peterjc authored
11 Martel
12 ======
bbfff83 @peterjc Removing Bio.ECell which was deprecated in Biopython 1.47 (also added mi...
peterjc authored
13 Declared obsolete in Release 1.48, deprecated in Release 1.49.
fb76593 @peterjc Labelling Martel and Bio.Mindy as obsolete, updating the news about this...
peterjc authored
14
15 Bio.Mindy
16 =========
bbfff83 @peterjc Removing Bio.ECell which was deprecated in Biopython 1.47 (also added mi...
peterjc authored
17 Declared obsolete in Release 1.48, deprecated in Release 1.49.
76300d6 @peterjc Updates include deprecation of Martel/Mindy
peterjc authored
18
43419aa @peterjc Deprecating Martel/Mindy related modules Bio.Std, Bio.StdHandler and Bio...
peterjc authored
19 Bio.builders, Bio.Std, Bio.StdHandler, Bio.Decode
20 =================================================
bbfff83 @peterjc Removing Bio.ECell which was deprecated in Biopython 1.47 (also added mi...
peterjc authored
21 Part of the Martel/Mindy infrastructure, these were deprecated in Release 1.49.
fb76593 @peterjc Labelling Martel and Bio.Mindy as obsolete, updating the news about this...
peterjc authored
22
fd2e06b @peterjc Adding minimal module docstrings for the deprecated Bio.Writers/Bio.writ...
peterjc authored
23 Bio.Writer and Bio.writers
24 ==========================
bbfff83 @peterjc Removing Bio.ECell which was deprecated in Biopython 1.47 (also added mi...
peterjc authored
25 Deprecated in Release 1.48.
fd2e06b @peterjc Adding minimal module docstrings for the deprecated Bio.Writers/Bio.writ...
peterjc authored
26
6ce5052 @peterjc Bio.Emboss.Primer was deprecated in Biopython 1.48
peterjc authored
27 Bio.Emboss.Primer
28 =================
29 Deprecated in Release 1.48, this parser was replaced by Bio.Emboss.Primer3 and
30 Bio.Emboss.PrimerSearch instead.
31
fb76593 @peterjc Labelling Martel and Bio.Mindy as obsolete, updating the news about this...
peterjc authored
32 Bio.MetaTool
33 ============
bbfff83 @peterjc Removing Bio.ECell which was deprecated in Biopython 1.47 (also added mi...
peterjc authored
34 Deprecated in Release 1.48, this was a parser for the output of MetaTool 3.5
fb76593 @peterjc Labelling Martel and Bio.Mindy as obsolete, updating the news about this...
peterjc authored
35 which is now obsolete.
36
81015eb @peterjc Declaring Bio.PubMed and the online parts of Bio.GenBank as OBSOLETE, an...
peterjc authored
37 Bio.GenBank
38 ===========
39 The online functionality (search_for, download_many, and NCBIDictionary) was
40 declared obsolete in Release 1.48, with the intention of an official deprecation
41 in the following release. Please use Bio.Entrez instead.
42
43 Bio.PubMed
44 ==========
45 Declared obsolete in Release 1.48, with the intention of an official deprecation
46 in the following release. Please use Bio.Entrez instead.
47
01e6e76 @peterjc Bio.EUtils deprecated in favour of Bio.Entrez
peterjc authored
48 Bio.EUtils
49 ==========
bbfff83 @peterjc Removing Bio.ECell which was deprecated in Biopython 1.47 (also added mi...
peterjc authored
50 Deprecated in favor of Bio.Entrez in Release 1.48.
01e6e76 @peterjc Bio.EUtils deprecated in favour of Bio.Entrez
peterjc authored
51
fa7ab2d @peterjc Updating for recent deprecations
peterjc authored
52 Bio.Blast.NCBIWWW
53 =================
bbfff83 @peterjc Removing Bio.ECell which was deprecated in Biopython 1.47 (also added mi...
peterjc authored
54 The HTML BLAST parser was deprecated as of Release 1.48.
55 The deprecated functions blast and blasturl were removed in Release 1.44.
fa7ab2d @peterjc Updating for recent deprecations
peterjc authored
56
57 Bio.Saf
58 =======
59 Deprecated as of Release 1.48, as it appears to have no users, and relies
bbfff83 @peterjc Removing Bio.ECell which was deprecated in Biopython 1.47 (also added mi...
peterjc authored
60 on Martel which doesn't work properly with mxTextTools 3.0.
fa7ab2d @peterjc Updating for recent deprecations
peterjc authored
61
ad46521 @peterjc Deprecating Bio.NBRF in favour of the 'pir' format in Bio.SeqIO
peterjc authored
62 Bio.NBRF
63 ========
64 Deprecated as of Release 1.48 in favor of the "pir" format in Bio.SeqIO
65
5be4221 @peterjc Deprecating Bio.IntelliGenetics in favour of the ig format in Bio.SeqIO
peterjc authored
66 Bio.IntelliGenetics
67 ===================
fa7ab2d @peterjc Updating for recent deprecations
peterjc authored
68 Deprecated as of Release 1.48 in favor of the "ig" format in Bio.SeqIO
d01c450 Getting ready for release 1.46.
mdehoon authored
69
890dada @peterjc Removing deprecated Bio.SeqIO submodules (code was moved under Bio.Align...
peterjc authored
70 Bio.SeqIO submodules PhylipIO, ClustalIO, NexusIO and StockholmIO
71 =================================================================
72 You can still use the "phylip", "clustal", "nexus" and "stockholm" formats
73 in Bio.SeqIO, however these are now supported via Bio.AlignIO, with the
74 old code deprecated in Releases 1.46 or 1.47, and removed in Release 1.49.
75
5e507c9 Updating for release 1.47.
mdehoon authored
76 Bio.ECell
77 =========
78 Deprecated as of Release 1.47, as it appears to have no users, and the code
bbfff83 @peterjc Removing Bio.ECell which was deprecated in Biopython 1.47 (also added mi...
peterjc authored
79 does not seem relevant for ECell 3. Removed in Release 1.49.
5e507c9 Updating for release 1.47.
mdehoon authored
80
edb3ac6 @peterjc Removing modules Bio.SGMLExtractor, Bio.CDD, Bio.Gobase and Bio.Rebase w...
peterjc authored
81 Bio.SGMLExtractor
82 =================
83 Deprecated as of Release 1.46, removed in Release 1.49.
84
d01c450 Getting ready for release 1.46.
mdehoon authored
85 Bio.Rebase
86 ==========
edb3ac6 @peterjc Removing modules Bio.SGMLExtractor, Bio.CDD, Bio.Gobase and Bio.Rebase w...
peterjc authored
87 Deprecated as of Release 1.46, removed in Release 1.49.
d01c450 Getting ready for release 1.46.
mdehoon authored
88
89 Bio.Gobase
90 ==========
edb3ac6 @peterjc Removing modules Bio.SGMLExtractor, Bio.CDD, Bio.Gobase and Bio.Rebase w...
peterjc authored
91 Deprecated as of Release 1.46, removed in Release 1.49.
d01c450 Getting ready for release 1.46.
mdehoon authored
92
93 Bio.CDD
94 =======
edb3ac6 @peterjc Removing modules Bio.SGMLExtractor, Bio.CDD, Bio.Gobase and Bio.Rebase w...
peterjc authored
95 Deprecated as of Release 1.46, removed in Release 1.49.
d01c450 Getting ready for release 1.46.
mdehoon authored
96
21059b1 @peterjc Bio.biblio was deprecated for Biopython 1.45, but I didn't remember to u...
peterjc authored
97 Bio.biblio
98 ==========
b927439 @peterjc Bio.WWW deprecation, and updating old entries to say when they were remo...
peterjc authored
99 Deprecated as of Release 1.45, removed in Release 1.48
21059b1 @peterjc Bio.biblio was deprecated for Biopython 1.45, but I didn't remember to u...
peterjc authored
100
4556db2 @peterjc Bringing these up to date with changes since Biopython 1.44
peterjc authored
101 Bio.WWW
102 =======
b927439 @peterjc Bio.WWW deprecation, and updating old entries to say when they were remo...
peterjc authored
103 The modules under Bio.WWW were deprecated in Release 1.45, and removed in 1.48.
104 The remaining stub Bio.WWW was deprecated in Release 1.48.
105
4556db2 @peterjc Bringing these up to date with changes since Biopython 1.44
peterjc authored
106 The functionality in Bio.WWW.SCOP, Bio.WWW.InterPro and Bio.WWW.ExPASy
107 is now available from Bio.SCOP, Bio.InterPro and Bio.ExPASy instead.
108
5145a4d @peterjc Bringing this up to date for Biopython 1.44
peterjc authored
109 Bio.SeqIO
110 =========
111 The old Bio.SeqIO.FASTA and Bio.SeqIO.generic were deprecated in favour of
bbfff83 @peterjc Removing Bio.ECell which was deprecated in Biopython 1.47 (also added mi...
peterjc authored
112 the new Bio.SeqIO module as of Release 1.44, removed in Release 1.47.
5145a4d @peterjc Bringing this up to date for Biopython 1.44
peterjc authored
113
fe10992 @peterjc Mentioning a few old modules deprecated in 1.44 and removed in 1.46
peterjc authored
114 Bio.Medline.NLMMedlineXML
115 =========================
bbfff83 @peterjc Removing Bio.ECell which was deprecated in Biopython 1.47 (also added mi...
peterjc authored
116 Deprecated in Release 1.44, removed in 1.46.
fe10992 @peterjc Mentioning a few old modules deprecated in 1.44 and removed in 1.46
peterjc authored
117
118 Bio.MultiProc
119 =============
bbfff83 @peterjc Removing Bio.ECell which was deprecated in Biopython 1.47 (also added mi...
peterjc authored
120 Deprecated in Release 1.44, removed in 1.46.
fe10992 @peterjc Mentioning a few old modules deprecated in 1.44 and removed in 1.46
peterjc authored
121
122 Bio.MarkupEditor
123 ================
bbfff83 @peterjc Removing Bio.ECell which was deprecated in Biopython 1.47 (also added mi...
peterjc authored
124 Deprecated in Release 1.44, removed in 1.46.
fe10992 @peterjc Mentioning a few old modules deprecated in 1.44 and removed in 1.46
peterjc authored
125
5145a4d @peterjc Bringing this up to date for Biopython 1.44
peterjc authored
126 Bio.lcc
127 =======
bbfff83 @peterjc Removing Bio.ECell which was deprecated in Biopython 1.47 (also added mi...
peterjc authored
128 Deprecated in favor of Bio.SeqUtils.lcc in Release 1.44, removed in 1.46.
5145a4d @peterjc Bringing this up to date for Biopython 1.44
peterjc authored
129
130 Bio.crc
131 =======
bbfff83 @peterjc Removing Bio.ECell which was deprecated in Biopython 1.47 (also added mi...
peterjc authored
132 Deprecated in favor of Bio.SeqUtils.CheckSum in Release 1.44, removed in 1.46.
5145a4d @peterjc Bringing this up to date for Biopython 1.44
peterjc authored
133
134 Bio.FormatIO
135 ============
bbfff83 @peterjc Removing Bio.ECell which was deprecated in Biopython 1.47 (also added mi...
peterjc authored
136 This was removed in Release 1.44 (a deprecation was not possible).
5145a4d @peterjc Bringing this up to date for Biopython 1.44
peterjc authored
137
fa7ab2d @peterjc Updating for recent deprecations
peterjc authored
138 Bio.expressions (and therefore Bio.config, Bio.dbdefs, Bio.formatdefs, Bio.dbdefs)
5145a4d @peterjc Bringing this up to date for Biopython 1.44
peterjc authored
139 ===============
bbfff83 @peterjc Removing Bio.ECell which was deprecated in Biopython 1.47 (also added mi...
peterjc authored
140 These were deprecated in Release 1.44, and removed in Release 1.49.
5145a4d @peterjc Bringing this up to date for Biopython 1.44
peterjc authored
141
142 Bio.Kabat
143 =========
bbfff83 @peterjc Removing Bio.ECell which was deprecated in Biopython 1.47 (also added mi...
peterjc authored
144 This was deprecated in Release 1.43 and removed in Release 1.44.
5145a4d @peterjc Bringing this up to date for Biopython 1.44
peterjc authored
145
34b4f31 Added the functions 'complement' and 'reverse_complement' to Bio.Seq's S...
mdehoon authored
146 Bio.SeqUtils
147 ============
148 The functions 'complement' and 'antiparallel' in Bio.SeqUtils have been
76300d6 @peterjc Updates include deprecation of Martel/Mindy
peterjc authored
149 deprecated as of Release 1.31, and removed in Release 1.43.
150 Use the functions 'complement' and 'reverse_complement' in Bio.Seq instead.
34b4f31 Added the functions 'complement' and 'reverse_complement' to Bio.Seq's S...
mdehoon authored
151
152 Bio.GFF
153 =======
154 The functions 'forward_complement' and 'antiparallel' in Bio.GFF.easy have been
76300d6 @peterjc Updates include deprecation of Martel/Mindy
peterjc authored
155 deprecated as of Release 1.31, and removed in Release 1.43.
156 Use the functions 'complement' and 'reverse_complement' in Bio.Seq instead.
efd9b60 Added blast to qblast change to DEPRECATED file
chapmanb authored
157
1c02f0c Bio.sequtils and Bio.SeqUtils were duplicated code, and even worse were ...
chapmanb authored
158 Bio.sequtils
b0acc00 Added instructions on how to move to Bio.Cluster from Bio.kMeans and
mdehoon authored
159 ============
bbfff83 @peterjc Removing Bio.ECell which was deprecated in Biopython 1.47 (also added mi...
peterjc authored
160 Deprecated as of Release 1.30, removed in Release 1.42.
1c02f0c Bio.sequtils and Bio.SeqUtils were duplicated code, and even worse were ...
chapmanb authored
161 Use Bio.SeqUtils instead.
b0acc00 Added instructions on how to move to Bio.Cluster from Bio.kMeans and
mdehoon authored
162
909bae9 Deprecated Bio.SVM and recommend usage of libsvm.
chapmanb authored
163 Bio.SVM
164 =======
bbfff83 @peterjc Removing Bio.ECell which was deprecated in Biopython 1.47 (also added mi...
peterjc authored
165 Deprecated as of Release 1.30, removed in Release 1.42.
909bae9 Deprecated Bio.SVM and recommend usage of libsvm.
chapmanb authored
166 The Support Vector Machine code in Biopython has been superceeded by a
167 more robust (and maintained) SVM library, which includes a python
168 interface. We recommend using LIBSVM:
169
170 http://www.csie.ntu.edu.tw/~cjlin/libsvm/
b0acc00 Added instructions on how to move to Bio.Cluster from Bio.kMeans and
mdehoon authored
171
23b046b Removed internal references to RecordFile, which are really not needed.
chapmanb authored
172 Bio.RecordFile
173 ==============
bbfff83 @peterjc Removing Bio.ECell which was deprecated in Biopython 1.47 (also added mi...
peterjc authored
174 Deprecated as of Release 1.30, removed in Release 1.42.
23b046b Removed internal references to RecordFile, which are really not needed.
chapmanb authored
175 RecordFile wasn't completely implemented and duplicates the work
176 of most standard parsers. We recommend using a specific iterator
177 (Bio.Fasta.Iterator for example) without a parser to get back
178 text records.
179
b0acc00 Added instructions on how to move to Bio.Cluster from Bio.kMeans and
mdehoon authored
180 Bio.kMeans and Bio.xkMeans
181 ==========================
bbfff83 @peterjc Removing Bio.ECell which was deprecated in Biopython 1.47 (also added mi...
peterjc authored
182 Deprecated as of Release 1.30, removed in Release 1.42.
b0acc00 Added instructions on how to move to Bio.Cluster from Bio.kMeans and
mdehoon authored
183
184 The k-Means algorithm is an algorithm for unsupervised clustering of data.
185 Biopython includes an implementation of the k-means clustering algorithm
186 in kMeans.py. Recently, a larger set of clustering algorithms entered
187 Biopython as Bio.Cluster. As the kcluster routine in Bio.Cluster also implements
188 the k-means clustering algorithm, the kMeans.py module has been deprecated.
189 Below you will find a description of how to switch from kMeans.py to
190 Bio.Cluster's kcluster.
191
192 The function kcluster in Bio.Cluster performs k-means or k-medians clustering.
193 The corresponding function in kMeans.py is called cluster. This function takes
194 the following arguments:
195
196 o data
197 o k
198 o distance_fn
199 o init_centroids_fn
200 o calc_centroid_fn
201 o max_iterations
202 o update_fn
203
204 The function kcluster in Bio.Cluster takes the following arguments:
205
206 o data
207 o nclusters
208 o mask
209 o weight
210 o transpose
211 o npass
212 o method
213 o dist
214 o initialid
215
216
217 Arguments for kMeans.py's cluster, and their equivalents in Bio.Cluster
218 -----------------------------------------------------------------------
219
220
221 o data:
222
223 In kMeans.py, data is a list of vectors, each containing the same number of
224 data points. Within the context of clustering genes based on their gene
225 expression values, each vector would correspond to the gene expression data of
226 one particular gene, and the values in the vector would correspond to the
227 measured gene expression value by the different microarrays. The cluster
228 routine in kMeans.py always performs a row-wise clustering by grouping vectors.
229
230 The argument data to Bio.Cluster's kcluster has the same structure as in
231 kMeans.py. However, Bio.Cluster allows row-wise and column-wise clustering by
232 the transpose argument. If transpose==0 (the default value), kcluster performs
233 row-wise clustering, consistent with kMeans.py. If transpose==1, kcluster
234 performs column-wise clustering. The same behavior can be obtained, of course,
235 by transposing the data array before calling kcluster.
236
237
238 o k:
239
240 The desired number of clusters is specified by the input argument k in
241 kMeans.py. The corresponding argument in Bio.Cluster's kcluster is nclusters.
242
243 o distance_fn:
244
245 In kMeans.py, the argument distance_fn represents the distance function to
246 calculate the distances between items and cluster centroids. This argument
247 corresponds to a true Python function. The default value is the Euclidean
248 distance, implemented as distance.euclidean in distance.py. User-defined
249 distance functions can also be used.
250
251 The k-means routine in Bio.Cluster does not allow user-specified distance
252 functions. Instead, it provides the following nine built-in distance functions,
253 depending on the argument dist:
254
255 dist=='e': Euclidean distance
256 dist=='h': Harmonically summed Euclidean distance
257 dist=='b': City-block distance
258 dist=='c': Pearson correlation
259 dist=='a': absolute value of the Pearson correlation
260 dist=='u': uncentered correlation
261 dist=='x': absolute uncentered correlation
262 dist=='s': Spearmans rank correlation
263 dist=='k': Kendalls tau
264
265 User-defined distance functions are possible only by modifying the C code in
266 cluster.c (which may not be as hard as it sounds). The default distance function
267 is the Euclidean distance (distance=='e'). Note that in Bio.Cluster the
268 Euclidean distance is defined as the sum of squared differences, whereas in
269 kMeans.py the square root of this quantity is taken. This does not affect the
270 clustering result.
271
272 o init_centroids_fn:
273
274 This function specifies the initial choice for the cluster centroids. By
275 default, cluster in kMeans.py uses a random initial choice of cluster centroids
276 by randomly choosing k data vectors from the input vectors in the data input
277 argument. Alternatively, the user can specify a user-defined function to choose
278 the initial cluster centroids.
279
280 In Bio.Cluster, the k-means algorithm in kcluster starts from an initial cluster
281 assignment instead of an initial choice of cluster centroids. As far as I know,
282 these two initialization methods are equivalent in practice. Similar to the
283 cluster routine in kMeans.py, Bio.Cluster's kcluster performs a random initial
284 assignment of items to clusters. Alternatively, users can specify a
285 (deterministic) initial clustering via the initialid argument. This argument is
286 None by default. If not None, it should be a 1D array (or list) containing the
287 number (between 0 and nclusters-1) of the cluster to which each item is
288 assigned initially.
289
290 Note that the k-means routine in Bio.Cluster performs automatic repeats of the
291 algorithm, each time starting from a different random initial clustering. See
292 the comment for the npass argument below.
293
294 o calc_centroid_fn:
295
296 This argument specifies how to calculate the cluster centroids, given the data
297 vectors of the items that belong to each cluster. By default, the mean over the
298 vectors is calculated. A user-defined function can also be used.
299
300 Bio.Cluster's kcluster does not allow user-defined functions. Instead, the
301 method to calculate the cluster centroid is determined by the argument method,
302 which can be either 'a' (arithmetic mean) or 'm' (median). The default is to
303 calculate the mean ('a').
304
305 o max_iterations:
306
307 The cluster routine in kMeans.py has an argument max_iterations, which is used
308 to stop the iteration it the routine does not converge after the given number of
309 iterations.
310
311 The kcluster routine in Bio.Cluster does not have such an argument. The failure
312 of a k-means algorithm to converge is due to the occurrence of periodic
313 clustering solutions during the course of the k-means algorithm. The kcluster
314 routine in Bio.Cluster automatically checks for the occurrence of such a
315 periodicity in the solutions. If a periodic behavior is detected, the algorithm
316 is interrupted and the last clustering solution is returned. Accordingly, the
317 kcluster routine is guaranteed to return a clustering solution. Also see the
318 discussion of the npass argument below.
319
320 o update_fn:
321
322 The argument update_fn to cluster in kMeans.py is a hook function that is
323 called at the beginning of every iteration and passed the iteration number,
324 cluster centroids, and current cluster assignments. It is used by xkMeans.py,
325 which provides a visualization of k-means clustering. Currently there is no
326 equivalent in Bio.Cluster.
327
328
329 Other arguments for Bio.Cluster's kcluster.
330 -------------------------------------------
331
332 Three arguments in Bio.Cluster's kcluster do not have a direct equivalent in
333 kMeans.py's cluster.
334
335 o mask:
336
337 Microarray experiments tend to suffer from a large number of missing data. The
338 argument mask to Bio.Cluster's kcluster lets the user specify which data are
339 missing. This argument is an array with the same shape as data, and contains
340 a 1 for each data point that is present, and a 0 for a missing data point:
341
342 mask[i,j]==1: data[i,j] is valid
343 mask[i,j]==0: data[i,j] is a missing data point
344
345 Missing data points are ignored by the clustering algorithm. By default, mask
346 is an array containing 1's everywhere.
347
348 o weight:
349
350 The weight argument is used to put different weights on different data point.
351 For example, when clustering genes based on their gene expression profile, we
352 may want to attach a bigger weight to some microarrays compared to others. By
353 default, the weight argument contains equal weights of 1.0 for all data points.
354 Note that for row-wise clustering, the weight argument is a 1D vector whose
355 length is equal to the number of columns. For column-wise clustering, the length
356 of this argument is equal to the number of rows.
357
358 o npass:
359
360 Typical implementations of the k-means clustering algorithm rely on a random
361 initialization. Unlike Self-Organizing Maps, however, the k-means algorithm has
362 a clearly defined goal, which is to minimize the within-cluster sum of
363 distances. Different k-means clustering solutions (based on different initial
364 clusterings) can therefore be compared to each other directly. In order to
365 increase the chance of finding the optimal k-means clustering solution, the
366 k-means routine in Bio.Cluster automatically repeats the algorithm npass times,
367 each time starting from a different initial random clustering. The best
368 clustering solution, as well as in how many of the npass attempts it was found,
369 is returned to the user. For more information, see the output variable nfound
370 below.
371
372
373 Return values
374 -------------
375
376 The cluster routine in kMeans.py returns two values:
377
378 o centroids
379 o clusters
380
381 The kcluster routine in Bio.Cluster returns four values:
382
383 o clusterid
384 o centroids
385 o error
386 o nfound
387
388
389 o centroids:
390
391 The centroids return value contains the centroids of the k clusters that were
392 found, and corresponds to the centroids return value from Bio.Cluster's
393 kcluster routine.
394
395 o clusters:
396
397 The clusters return value contains the number of the cluster to which each
398 vector was assigned. The corresponding return value in Bio.Cluster's kcluster
399 is clusterid.
400
401 o error:
402
403 The error return value from Bio.Cluster's kcluster is the within-cluster sum of
404 distances for the optimal clustering solution that was found. This value can be
405 used to compare different clustering solutions to each other.
406
407 o nfound:
408
409 The nfound return value from Bio.Cluster's kcluster shows in how many of the
410 npass runs the optimal clustering solution was found. Accordingly, nfound is at
411 least 1 and at most equal to npass. A large value for nfound is an indication
412 that the clustering solution that was found is optimal. On the other hand, if
413 nfound is equal to 1, it is very well possible that a better clustering solution
414 exists than the one found by kcluster.
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