[med-svn] [Git][med-team/tnseq-transit][upstream] New upstream version 3.2.1
Nilesh Patra
gitlab at salsa.debian.org
Thu Dec 24 18:32:42 GMT 2020
Nilesh Patra pushed to branch upstream at Debian Med / tnseq-transit
Commits:
ad0cdd39 by Nilesh Patra at 2020-12-24T23:40:37+05:30
New upstream version 3.2.1
- - - - -
11 changed files:
- CHANGELOG.md
- src/pytransit/__init__.py
- src/pytransit/analysis/gi.py
- src/pytransit/analysis/gumbel.py
- src/pytransit/analysis/hmm.py
- src/pytransit/analysis/rankproduct.py
- src/pytransit/analysis/resampling.py
- src/pytransit/analysis/tn5gaps.py
- src/pytransit/analysis/utest.py
- + src/pytransit/data/README.md
- + src/pytransit/data/smeg_GO_terms.txt
Changes:
=====================================
CHANGELOG.md
=====================================
@@ -1,6 +1,13 @@
# Change log
All notable changes to this project will be documented in this file.
+
+## Version 3.2.1 2020-12-22
+#### TRANSIT:
+ - maintenance release
+ - fixed a bug in the GUI caused by changes in wxPython 4.1.0
+ - added GO terms for M. smegmatis in the data directory for doing pathway analysis
+
## Version 3.2.0 2020-10-26
#### TRANSIT:
- improvements to pathway_enrichment analysis
=====================================
src/pytransit/__init__.py
=====================================
@@ -2,6 +2,6 @@
__all__ = ["transit_tools", "tnseq_tools", "norm_tools", "stat_tools"]
-__version__ = "v3.2.0"
+__version__ = "v3.2.1"
prefix = "[TRANSIT]"
=====================================
src/pytransit/analysis/gi.py
=====================================
@@ -115,19 +115,19 @@ class GIGUI(base.AnalysisGUI):
# Samples
(giSampleLabel, self.wxobj.giSampleText, sampleSizer) = self.defineTextBox(giPanel, u"Samples:", u"10000", "Number of samples to take when estimating the distributions of means. More samples give more accurate estimates at the cost of computation time.")
- mainSizer1.Add(sampleSizer, 1, wx.ALIGN_CENTER_HORIZONTAL|wx.EXPAND, 5 )
+ mainSizer1.Add(sampleSizer, 1, wx.EXPAND, 5 )
# ROPE
(giROPELabel, self.wxobj.giROPEText, ROPESizer) = self.defineTextBox(giPanel, u"ROPE:", u"0.5", "Region of Practical Equivalence. Area around 0 (i.e. 0.0 +/- ROPE) that defines changes in enrichment (delta-log2FC) that are NOT of interest. Can be thought of as the area representing a null-hypothesis.")
- mainSizer1.Add(ROPESizer, 1, wx.ALIGN_CENTER_HORIZONTAL|wx.EXPAND, 5 )
+ mainSizer1.Add(ROPESizer, 1, wx.EXPAND, 5 )
# Norm
giNormChoiceChoices = [ u"TTR", u"nzmean", u"totreads", u'zinfnb', u'quantile', u"betageom", u"nonorm" ]
(giNormLabel, self.wxobj.giNormChoice, normSizer) = self.defineChoiceBox(giPanel, u"Normalization:", giNormChoiceChoices, "Choice of normalization method. The default choice, 'TTR', normalizes datasets to have the same expected count (while not being sensative to outliers). Read documentation for a description other methods. ")
- mainSizer1.Add(normSizer, 1, wx.ALIGN_CENTER_HORIZONTAL|wx.EXPAND, 5 )
+ mainSizer1.Add(normSizer, 1, wx.EXPAND, 5 )
giSizer.Add( mainSizer1, 1, wx.EXPAND, 5 )
=====================================
src/pytransit/analysis/gumbel.py
=====================================
@@ -99,25 +99,25 @@ class GumbelGUI(base.AnalysisGUI):
# Samples
(gumbelSampleLabel, self.wxobj.gumbelSampleText, sampleSizer) = self.defineTextBox(gumbelPanel, u"Samples:", u"10000", "These are the number of samples to take when estimating the parameters. More samples give more accurate estimates of the parameters at the cost of computation time.")
- mainSizer1.Add(sampleSizer, 1, wx.ALIGN_CENTER_HORIZONTAL|wx.EXPAND, 5 )
+ mainSizer1.Add(sampleSizer, 1, wx.EXPAND, 5 )
# Burn-In
(gumbelBurninLabel, self.wxobj.gumbelBurninText, burninSizer) = self.defineTextBox(gumbelPanel, u"Burn-In:", u"500", "These are the number of samples to take before beginning to estimate the parameters. Allows the MCMC sampler to 'converge' to the true parameter space. More samples give more accurate estimates of the parameters at the cost of computation time.")
- mainSizer1.Add(burninSizer, 1, wx.ALIGN_CENTER_HORIZONTAL|wx.EXPAND, 5 )
+ mainSizer1.Add(burninSizer, 1, wx.EXPAND, 5 )
# Trim
(gumbelTrimLabel, self.wxobj.gumbelTrimText, trimSizer) = self.defineTextBox(gumbelPanel, u"Trim:", u"1", "The MCMC sample will keep every i-th sample. A value of '1' will take all samples. Larger values will reduces autocorrelation at the cost of a substantial cost in computation time.")
- mainSizer1.Add(trimSizer, 1, wx.ALIGN_CENTER_HORIZONTAL|wx.EXPAND, 5 )
+ mainSizer1.Add(trimSizer, 1, wx.EXPAND, 5 )
# Min Read
gumbelReadChoiceChoices = [ u"1", u"2", u"3", u"4", u"5" ]
(gumbelReadLabel, self.wxobj.gumbelReadChoice, readSizer) = self.defineChoiceBox(gumbelPanel, u"Minimum Read:", gumbelReadChoiceChoices, "This is the minimum number of reads to consider a 'true' insertion. Value of 1 will consider all insertions. Larger values allow the method to ignore spurious insertions which might interrupt a run of non-insertions. Noisy datasets or those with many replicates can beneffit from increasing this.")
- mainSizer1.Add(readSizer, 1, wx.ALIGN_CENTER_HORIZONTAL|wx.EXPAND, 5 )
+ mainSizer1.Add(readSizer, 1, wx.EXPAND, 5 )
# Replicates
gumbelRepChoiceChoices = [ u"Sum", u"Mean" ]
(gumbelRepLabel, self.wxobj.gumbelRepChoice, repSizer) = self.defineChoiceBox(gumbelPanel, u"Replicates:", gumbelRepChoiceChoices, "Determines how to handle replicates, and their read-counts. When using many replicates, summing read-counts may make spurious counts appear to be significantly large and interrupt a run of non-insertions.")
- mainSizer1.Add(repSizer, 1, wx.ALIGN_CENTER_HORIZONTAL|wx.EXPAND, 5 )
+ mainSizer1.Add(repSizer, 1, wx.EXPAND, 5 )
gumbelSection.Add( mainSizer1, 1, wx.EXPAND, 5 )
=====================================
src/pytransit/analysis/hmm.py
=====================================
@@ -129,18 +129,18 @@ class HMMGUI(base.AnalysisGUI):
hmmSizer1 = wx.BoxSizer( wx.VERTICAL )
#(, , Sizer) = self.defineChoiceBox(hmmPanel, u"", hmmNormChoiceChoices, "")
- #hmmSizer1.Add(Sizer, 1, wx.ALIGN_CENTER_HORIZONTAL|wx.EXPAND, 5 )
+ #hmmSizer1.Add(Sizer, 1, wx.EXPAND, 5 )
# NORMALIZATION
hmmNormChoiceChoices = [ u"TTR", u"nzmean", u"totreads", u'zinfnb', u'quantile', u"betageom", u"nonorm" ]
(hmmNormLabel, self.wxobj.hmmNormChoice, normSizer) = self.defineChoiceBox(hmmPanel, u"Normalization:", hmmNormChoiceChoices, "Choice of normalization method. The default choice, 'TTR', normalizes datasets to have the same expected count (while not being sensative to outliers). Read documentation for a description other methods.")
- hmmSizer1.Add(normSizer, 1, wx.ALIGN_CENTER_HORIZONTAL|wx.EXPAND, 5 )
+ hmmSizer1.Add(normSizer, 1, wx.EXPAND, 5 )
# REPLICATE
hmmRepChoiceChoices = [ u"Sum", u"Mean" ]
(hmmRepLabel, self.wxobj.hmmRepChoice, repSizer) = self.defineChoiceBox(hmmPanel, u"Replicates:", hmmRepChoiceChoices, "Determines how to handle replicates, and their read-counts. When using many replicates, using 'Mean' may be recommended over 'Sum'")
- hmmSizer1.Add(repSizer, 1, wx.ALIGN_CENTER_HORIZONTAL|wx.EXPAND, 5 )
+ hmmSizer1.Add(repSizer, 1, wx.EXPAND, 5 )
# LOESS
=====================================
src/pytransit/analysis/rankproduct.py
=====================================
@@ -80,14 +80,14 @@ class RankProductGUI(base.AnalysisGUI):
# SAMPLES
(rankproductSampleLabel, self.wxobj.rankproductSampleText, sampleSizer) = self.defineTextBox(rankproductPanel, u"Samples:", u"10000", "Number of samples to take when estimating the theoretical rankproduct distribution. Larger samples give more accurate estimates at the cost of computation time.")
- mainSizer1.Add(sampleSizer, 1, wx.ALIGN_CENTER_HORIZONTAL|wx.EXPAND, 5 )
+ mainSizer1.Add(sampleSizer, 1, wx.EXPAND, 5 )
# NORMALIZATION
# Norm
rankproductNormChoiceChoices = [ u"TTR", u"nzmean", u"totreads", u'zinfnb', u'quantile', u"betageom", u"nonorm" ]
(rankproductNormLabel, self.wxobj.rankproductNormChoice, normSizer) = self.defineChoiceBox(rankproductPanel, u"Normalization:", rankproductNormChoiceChoices, "Choice of normalization method. The default choice, 'TTR', normalizes datasets to have the same expected count (while not being sensative to outliers). Read documentation for a description other methods. ")
- mainSizer1.Add(normSizer, 1, wx.ALIGN_CENTER_HORIZONTAL|wx.EXPAND, 5 )
+ mainSizer1.Add(normSizer, 1, wx.EXPAND, 5 )
rankproductSizer.Add( mainSizer1, 1, wx.EXPAND, 5 )
=====================================
src/pytransit/analysis/resampling.py
=====================================
@@ -119,21 +119,21 @@ class ResamplingGUI(base.AnalysisGUI):
mainSizer1 = wx.BoxSizer( wx.VERTICAL )
#(, , Sizer) = self.defineChoiceBox(resamplingPanel, u"", u"", "")
- #mainSizer1.Add(Sizer, 1, wx.ALIGN_CENTER_HORIZONTAL|wx.EXPAND, 5 )
+ #mainSizer1.Add(Sizer, 1, wx.EXPAND, 5 )
# Samples
(resamplingSampleLabel, self.wxobj.resamplingSampleText, sampleSizer) = self.defineTextBox(resamplingPanel, u"Samples:", u"10000", "Number of samples to take when estimating the resampling histogram. More samples give more accurate estimates of the p-values at the cost of computation time.")
- mainSizer1.Add(sampleSizer, 1, wx.ALIGN_CENTER_HORIZONTAL|wx.EXPAND, 5 )
+ mainSizer1.Add(sampleSizer, 1, wx.EXPAND, 5 )
# Pseudocount - changing the semantics on 3/5/20
#(resamplingPseudocountLabel, self.wxobj.resamplingPseudocountText, pseudoSizer) = self.defineTextBox(resamplingPanel, u"Pseudocount:", u"0.0", "Adds pseudo-counts to the each data-point. Useful to dampen the effects of small counts which may lead to deceptively high log-FC.")
(resamplingPseudocountLabel, self.wxobj.resamplingPseudocountText, pseudoSizer) = self.defineTextBox(resamplingPanel, u"Pseudocount:", u"0.0", "Pseudo-counts used in calculating log-fold-chnage. Useful to dampen the effects of small counts which may lead to deceptively high LFC.")
- mainSizer1.Add(pseudoSizer, 1, wx.ALIGN_CENTER_HORIZONTAL|wx.EXPAND, 5 )
+ mainSizer1.Add(pseudoSizer, 1, wx.EXPAND, 5 )
# Norm
resamplingNormChoiceChoices = [ u"TTR", u"nzmean", u"totreads", u'zinfnb', u'quantile', u"betageom", u"nonorm" ]
(resamplingNormLabel, self.wxobj.resamplingNormChoice, normSizer) = self.defineChoiceBox(resamplingPanel, u"Normalization: ", resamplingNormChoiceChoices, "Choice of normalization method. The default choice, 'TTR', normalizes datasets to have the same expected count (while not being sensative to outliers). Read documentation for a description other methods. ")
- mainSizer1.Add(normSizer, 1, wx.ALIGN_CENTER_HORIZONTAL|wx.EXPAND, 5 )
+ mainSizer1.Add(normSizer, 1, wx.EXPAND, 5 )
=====================================
src/pytransit/analysis/tn5gaps.py
=====================================
@@ -93,13 +93,13 @@ class Tn5GapsGUI(base.AnalysisGUI):
# Min Read
tn5GapsReadChoiceChoices = [ u"1", u"2", u"3", u"4", u"5" ]
(tn5GapsReadLabel, self.wxobj.tn5GapsReadChoice, readSizer) = self.defineChoiceBox(tn5GapsPanel, u"Minimum Read:", tn5GapsReadChoiceChoices, "This is the minimum number of reads to consider a 'true' insertion. Value of 1 will consider all insertions. Larger values allow the method to ignore spurious insertions which might interrupt a run of non-insertions. Noisy datasets or those with many replicates can beneffit from increasing this.")
- mainSizer1.Add(readSizer, 1, wx.ALIGN_CENTER_HORIZONTAL|wx.EXPAND, 5 )
+ mainSizer1.Add(readSizer, 1, wx.EXPAND, 5 )
# Replicates
tn5GapsRepChoiceChoices = [ u"Sum", u"Mean" ]
(tn5GapsRepLabel, self.wxobj.tn5GapsRepChoice, repSizer) = self.defineChoiceBox(tn5GapsPanel, u"Replicates:", tn5GapsRepChoiceChoices, "Determines how to handle replicates, and their read-counts. When using many replicates, summing read-counts may make spurious counts appear to be significantly large and interrupt a run of non-insertions.")
- mainSizer1.Add(repSizer, 1, wx.ALIGN_CENTER_HORIZONTAL|wx.EXPAND, 5 )
+ mainSizer1.Add(repSizer, 1, wx.EXPAND, 5 )
tn5GapsSection.Add( mainSizer1, 1, wx.EXPAND, 5 )
=====================================
src/pytransit/analysis/utest.py
=====================================
@@ -107,12 +107,12 @@ class UTestGUI(base.AnalysisGUI):
mainSizer1 = wx.BoxSizer( wx.VERTICAL )
#(, , Sizer) = self.defineChoiceBox(utestPanel, u"", u"", "")
- #mainSizer1.Add(Sizer, 1, wx.ALIGN_CENTER_HORIZONTAL|wx.EXPAND, 5 )
+ #mainSizer1.Add(Sizer, 1, wx.EXPAND, 5 )
# Norm
utestNormChoiceChoices = [ u"TTR", u"nzmean", u"totreads", u'zinfnb', u'quantile', u"betageom", u"nonorm" ]
(utestNormLabel, self.wxobj.utestNormChoice, normSizer) = self.defineChoiceBox(utestPanel, u"Normalization:", utestNormChoiceChoices, "Choice of normalization method. The default choice, 'TTR', normalizes datasets to have the same expected count (while not being sensative to outliers). Read documentation for a description other methods. ")
- mainSizer1.Add(normSizer, 1, wx.ALIGN_CENTER_HORIZONTAL|wx.EXPAND, 5 )
+ mainSizer1.Add(normSizer, 1, wx.EXPAND, 5 )
utestSizer.Add( mainSizer1, 1, wx.EXPAND, 5 )
=====================================
src/pytransit/data/README.md
=====================================
@@ -0,0 +1,39 @@
+Transit Data directory
+======================
+
+Files for Pathway Enrichment analysis
+-------------------------------------
+
+These files can be used for pathway_enrichment analysis.
+
+```
++----------+---------+--------------------+--------------------------------------+--------------------------------+
+| system | num cats| applicable methods | associations of genes with roles | pathway definitions/role names |
++==========+=========+====================+======================================+================================+
+| COG | 20 | FET*, GSEA | H37Rv_COG_roles.dat | COG_roles.dat |
++----------+---------+--------------------+--------------------------------------+--------------------------------+
+| Sanger | 153 | FET*, GSEA* | H37Rv_sanger_roles.dat | sanger_roles.dat |
++----------+---------+--------------------+--------------------------------------+--------------------------------+
+| GO | 2545 | FET, GSEA | H37Rv_GO_terms.txt | GO_term_names.dat |
++----------+---------+--------------------+--------------------------------------+--------------------------------+
+| | | ONT* | GO_terms_for_each_Rv.obo-3-11-18.txt | gene_ontology.1_2.3-11-18.obo |
++----------+---------+--------------------+--------------------------------------+--------------------------------+
+```
+
+These file are to be used as inputs for the transit pathway_enrichment
+command (see the [documentation](https://transit.readthedocs.io/en/latest/transit_methods.html#pathway-enrichment-analysis)).
+
+
+A file with GO terms for Mycobacterium smegmatis is also included: smeg_GO_terms.txt.
+
+
+
+Test files for resampling
+-------------------------
+
+These wig files are from the
+[Griffin et al (2011) paper in PLOS Pathogens](http://www.ncbi.nlm.nih.gov/pubmed/21980284).
+on M. tuberculosis genes required for growth on glycerol.
+
+ * glycerol_H37Rv_rep1.wig, glycerol_H37Rv_rep2.wig, glycerol_H37Rv_rep3.wig
+ * cholesterol_H37Rv_rep1.wig, cholesterol_H37Rv_rep2.wig, cholesterol_H37Rv_rep3.wig
=====================================
src/pytransit/data/smeg_GO_terms.txt
=====================================
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View it on GitLab: https://salsa.debian.org/med-team/tnseq-transit/-/commit/ad0cdd39e7e088baebd489d0a1d59125bde320e4
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