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Please correct the “lefse_plot_cladogram.py” Line 270 in biobakery lefse online server

The shaded area in the cladogram has been shifted to the right side. I have ran the same data in the legacy website of galaxy which visualized the cladogram correctly. But this new biobakery site of LEfSe is shifting the shaded area of taxa to the right side automatically.
Then I run LEfSe with the command line after correcting “lefse_plot_cladogram.py” line 270
ax.bar(fr_0, clto, width = fr_1-fr_0, bottom = float(l-1)/float(de), alpha = params[‘alpha’], color=col, edgecolor=col)
to
ax.bar(fr_0, clto, width = fr_1-fr_0, bottom = float(l-1)/float(de), align=‘edge’, alpha = params[‘alpha’], color=col, edgecolor=col)

The shaded area showed in the right place. I think this will be helpful for everyone if you could correct this “lefse_plot_cladogram.py” line 270 in the BIOBAKERY website.

Images are added for the references.

Where is the tutorial ?

I am a green hand, so I don't know how to start with this program, What should I do ? Where can I find the tutorial for this program?
THANK YOU

subclass labels changed if they contain class characters

lefse_plot_subclass_labels.pdf

In making feature plots, if the subclass contains a character that is the same as the class name, it gets changed to an underscore. See Classes 2 and 3 in this plot. "28w" is changed to "_8w" in Class 2, for example.

Lefse Installation "No ctypes found" error

I am attempting to install lefse in a pyhton 3.7 shell (biom-format does not support my system python version 3.6) and am receiving an error upon installing lefse "from _ctypes import Union, Structure, Array
ModuleNotFoundError: No module named '_ctypes'" the libbfi-devel library is present in the global python environment too. I am unsure of why this issue is occuring.

plot missing groups or sample columns

this issue is replicated with the latest code at ff93a8b

(lefse1.1.2) $ lefse_format_input.py LEfSe.txt input.in -c 1 -o 1000000
(lefse1.1.2) $ lefse_run.py input.in input.res
Number of significantly discriminative features: 11 ( 115 ) before internal wilcoxon
Number of discriminative features with abs LDA score > 2.0 : 11
(lefse1.1.2) $ lefse_plot_res.py input.res input.png
(lefse1.1.2) $ lefse_plot_cladogram.py input.res input.cladogram.png --format png
clade_sep parameter too large, lowered to 0.15016937255859375
(lefse1.1.2) $ lefse_plot_features.py input.in input.res biomarkers_raw_images/
Exporting  Bacteria.Acidobacteria
/home/agean/anaconda3/envs/lefse1.1.2/lib/python3.10/site-packages/lefse/lefse_plot_features.py:99: UserWarning: color is redundantly defined by the 'color' keyword argument and the fmt string "k--" (-> color='k'). The keyword argument will take precedence.
  if params['subcl_median'] == 'y': ax.plot([fr,to-1],[median,median],"k--",linewidth=1,color=params['fore_color'])
Exporting  Bacteria.Acidobacteria.Acidobacteria
Exporting  Bacteria.Proteobacteria.Betaproteobacteria
Exporting  Bacteria.Acidobacteria.Acidobacteria.Subgroup_4
Exporting  Bacteria.Acidobacteria.Acidobacteria.Subgroup_4.Unknown_Family
Exporting  Bacteria.Firmicutes.Clostridia.Clostridiales.Clostridiaceae_1
Exporting  Bacteria.Acidobacteria.Acidobacteria.Subgroup_4.Unknown_Family.Blastocatella
Exporting  Bacteria.Firmicutes.Clostridia.Clostridiales.Clostridiaceae_1.Clostridium_sensu_stricto_1
Exporting  Bacteria.Firmicutes.Clostridia.Clostridiales.Clostridiaceae_1.Clostridium_sensu_stricto_5
Exporting  Bacteria.Proteobacteria.Gammaproteobacteria.Xanthomonadales.Xanthomonadaceae.Lysobacter
Exporting  Bacteria.Proteobacteria.Gammaproteobacteria.Xanthomonadales.Xanthomonadaceae.Thermomonas

and the header of the input.txt:

Class	BS	BS	BS	BS	BS	BS	BS	BS	BS	BS	BS	BS	BS	BS	BS	BS	BS	BS	B	B	B	B	B	B	B	B	B	B	B	B	B	B	B	B	B	B	CK	CK	CK	CK	CK	CK	CK	CK	CK	CK	CK	CK	CK	CK	CK	CK	CK	CK	GB	GB	GB	GB	GB	GB	GB	GB	GB	GB	GB	GB	GB	GB	GB	GB	GB	GB	G	G	G	G	G	G	G	G	G	G	G	G	G	G	G	G	G	G	S	S	S	S	S	S	S	S	S	S	S	S	S	S	S	S	S
Bacteria	30.6630944407234	28.0821189235188	26.2622912439519	28.464878565641	34.0280283892698	24.8668178701408	22.8306348917591	31.542049846728	23.2917247712663	31.2347608627696	29.4716136471546	33.8675415407855	23.7967782722212	20.9295630477896	16.8389490772952	41.5306788511749	27.9520872441226	41.5160760384886	32.0162510953557	30.5940213210243	34.4588532746106	27.2795123771613	30.7127927313057	30.4716322664274	32.4128984432913	34.3659315147998	34.1582780535325	26.6592442798391	7.51135216952573	27.68968456948	26.8868323548818	27.1602061915718	33.0120737131964	31.2339943342776	27.3729269730603	30.3363761410529	28.8902074636038	28.4102670254606	39.7076572348129	32.3783972938295	29.5300601623964	33.4062458821979	33.1469209633102	35.9502682107585	36.2998335865712	24.3506352716708	23.7893388631373	23.256418251741	28.0696576151122	21.6789806996381	23.8571794215511	36.2356581152507	35.8637953914827	37.3437666915928	32.8514798366666	34.4840999708256	35.1296847853065	72.7115748820974	71.1305790044441	74.8551649646504	43.1020881670534	37.8530510585305	39.7420472592521	39.573396655135	13.5892681862799	40.7100192068216	43.8096802677783	34.1613101198359	25.9357010744197	61.0303454919648	65.8615798885897	64.4623346751006	37.0374356490699	39.2138401788867	33.2591449977964	72.4046368770435	72.6245608431811	74.7023809523809	37.3352244284999	41.5997726788378	44.1844532279315	26.6893642217452	27.5398071316439	32.6823014855592	28.6704100556357	28.2418676698385	21.1531816162314	66.9901899394698	69.2487698195735	60.8118064703387	31.4522599625568	31.8027103021078	24.6580792758741	23.507164544825	26.4721392160309	20.0196976149915	29.3584854263144	29.0867374695461	36.7328458560659	36.2979081847536	29.657192887931	21.7576749491643	25.3858360818968	25.2721021785988	37.7703724904935	44.7464562326465	39.7644054731162
Bacteria|Acidobacteria	0.116097343156955	0.0936070630783959	0.0916965818635867	0.0519394178630046	0.0390953927583303	0.0131863494910069	0.0254684373294524	0.0666400106624017	0.0748273868235774	0.112535167239762	0.0768726401229962	0.0849697885196375	0.206899949096044	0.13274902437464	0.115959314846105	0.0550750652741514	0.0774708739310509	0.058671673316123	0.220398842242226	0.175843499285636	0.280020661718729	0.0787826014844301	0.0575864863711982	0.0598265031408914	0.240919199406968	0.340975043528729	0.243540381314654	0.181772738633523	0.0567608476286579	0.381926683716965	0.504170402828768	0.372775722981041	0.431582291887312	0.0634560906515581	0.128162407402661	0.112542203326247	0.233105172815699	0.0672738563444421	0.301729918197667	0.08865041409075	0.132525558500568	0.0658848333113717	0.265071925004041	0.308317040156414	0.465475242987724	0.28402931355969	0.143327640888021	0.223469493815612	0.346141461843941	0.282720144752714	0.258510366009726	0.208843625112801	0.0965134515623115	0.0293772032902468	0.05066913057733	0.0486239424292522	0.0620501365103003	0.024137546882543	0.00850539029109698	0.0196386488609584	0.0603248259860789	0.0473225404732254	0.0794070937003706	0.0941638861026386	0.0581670120333006	0.160408619852677	0.112943302462164	0.0952873154817662	0.0768927035058916	0.0262731532162718	0.0308331106497564	0.0123223527478847	0.0627813951819764	0.0294221489937625	0.143234905244601	0.00990785693054592	0.00598850207601405	0.00220458553791887	0.0389343122531843	0.0449906466813478	0.0395256916996047	0.159129598105248	0.156985871271586	0.17595455345248	0.293632804450855	0.154901526886479	0.182652910105149	0.0438321853475266	0.0262438490978677	0.0379557480631405	0.130382455201926	0.103591890234879	0.172410934831982	0.0665849890800618	0.0615222358938302	0.0851788756388416	0.146417869790248	0.0898833881306621	0.162995494985625	0.0795544948289578	0.148168103448276	0.175238473110814	0.161802227892215	0.288579724602312	0.122664267898761	0.0730673681134006	0.0674503757949509
Bacteria|Actinobacteria	0.82830989060058	1.02329539410701	1.00085843608553	1.69322502233395	1.21496451341273	2.93264412679994	2.139348735674	1.25283220045315	1.65980748954117	0.803376055017193	1.14404576183047	1.13765105740181	0.821031544031922	0.799692917919519	0.977371367988603	1.56453981723238	1.38553678376687	1.50903543769068	1.30114979155049	1.79415320364875	1.21795394611641	4.48646183190281	2.86652732158853	2.84923721208495	1.48026315789474	1.69762042948346	1.5470612793988	1.80409443093772	0.113521695257316	2.13128729752771	0.795168084998393	0.765937618312607	0.680470239356069	1.88101983002833	2.46584471842719	2.32274602976116	0.436542414545763	0.507141378596564	1.0694649322784	4.05458999183483	3.22058142959317	3.50243773883252	1.20575400032326	1.43630621146037	1.2468948218894	1.22284376219592	1.69553549646255	1.58767279908533	1.0759901255769	1.34574788902292	1.27975428717686	1.08031455459585	1.57739172397153	2.28340989210554	1.16240946618581	0.717203150831469	1.38682055100521	0.271083218834713	0.433774904845946	0.375589159465829	1.42227378190255	1.27272727272727	1.7204870301747	1.40427012753065	0.737993965172502	1.01943899195846	1.10479084953899	0.702542071772344	0.442652590452836	0.823225467443184	0.628995457255031	0.751663517620965	0.89867082817629	1.23278804283865	1.01366240634641	0.34083027841078	0.461114659853082	0.440917107583774	1.07625563157017	1.00636972839857	1.45718050065876	2.30182814003405	1.70441803094864	1.45790915717769	1.79785699567278	0.146603230803275	1.37730167349558	0.540596952619495	0.376161837069437	0.875214896514769	0.775608451457609	0.471448806579142	0.606753866812553	2.35977201299739	2.55097556688346	1.03545570698467	1.00789975483519	1.39319251602526	0.830824259162837	0.807244138705602	0.737473060344828	0.704260278728364	0.847905905781318	0.575378092879919	1.3758842049311	1.12036631107214	1.75370977066872

the output res and cladogram only show 4 groups:

the feature plot is ok.

kruskal screening p-values and fdr

I was wondering why isn't there a correction for multiple testing after the kruskal selection step at all?

thanks

How to use LDA when the number of samples is smaller than the number of features?

Hello, I currently have a confusion. When conducting differential analysis of bacteria, I often face the challenge of having a limited number of samples (only around twenty) and an excessive number of annotated species, making it difficult to decide which method to use. In my understanding, LDA may require a large number of samples, greater than the number of annotated species, for optimal use. If my sample size is small, can tools like yours still be used?

An error in lefse v1.1.2

Hi, thank you for developing the lefse.
An error may be encountered, when run "lefse_plot_res.py" as follows:

lefse_plot_res.py --feature_font_size 8 --format pdf --class_legend_font_size 8 lefse.output lefse.pdf

File "lefse_plot_res.py", line 102, in plot_histo_hor
if len(rr) > params['max_feature_len']: rr = rr[:params['max_feature_len']/2-2]+" [..]"+rr[-params['max_feature_len']/2+2:]
TypeError: slice indices must be integers or None or have an index method

It should be
"if len(rr) > params['max_feature_len']: rr = rr[:int(params['max_feature_len']/2-2)]+" [..]"+rr[int(-params['max_feature_len']/2+2):]"

lefse galaxy server

Thank you for developing such useful tool. I used lefse galaxy service but gut the following error:

/galaxy_venv/local/lib/python2.7/site-packages/rpy2/rinterface/__init__.py:185: RRuntimeWarning: Error in (function (file = "", n = NULL, text = NULL, prompt = "?", keep.source = getOption("keep.source"),  : 
  <text>:1:71: unexpected input
1: z <- suppressWarnings(lda(as.formula(class ~ Streptococcus_infantis + _
                                                                          ^

  warnings.warn(x, RRuntimeWarning)
Traceback (most recent call last):
  File "/shed_tools/testtoolshed.g2.bx.psu.edu/repos/george-weingart/lefse/a6284ef17bf3/lefse/run_lefse.py", line 89, in <module>
    if params['rank_tec'] == 'lda': lda_res,lda_res_th = test_lda_r(cls,feats,class_sl,params['n_boots'],params['f_boots'],params['lda_abs_th'],0.0000000001,params['nlogs'])
  File "/export/shed_tools/testtoolshed.g2.bx.psu.edu/repos/george-weingart/lefse/a6284ef17bf3/lefse/lefse.py", line 189, in test_lda_r
    z = robjects.r('z <- suppressWarnings(lda(as.formula('+f+'),data=sub_d,tol='+str(tol_min)+'))')
  File "/galaxy_venv/local/lib/python2.7/site-packages/rpy2/robjects/__init__.py", line 358, in __call__
    p = _rparse(text=StrSexpVector((string,)))
rpy2.rinterface.RRuntimeError: Error in (function (file = "", n = NULL, text = NULL, prompt = "?", keep.source = getOption("keep.source"),  : 
  <text>:1:71: unexpected input
1: z <- suppressWarnings(lda(as.formula(class ~ Streptococcus_infantis + _
                                                                          ^

And I checked the taxa names there are no special chars. And the abundance values are in normal float value notation (not scientific notation). Could you help me out?

argument parsing for lefse_format_input

line 393 ignores the parsed arguments and requires the first argument to be the input file:

lefse/lefse/lefse_format_input.py

Line 393 in 200aa6a

 CommonArea = read_input_file(sys.argv[1], CommonArea) #Pass The CommonArea to the Read 

How best to integrate results from multiple marker genes

Hello
I am reaching out for some advice on using lefse with multiple marker genes for the same set of samples. Should I concatenate all the otu tables and then run lefse or run lefse on each marker gene's otu table separately and then combine the results?
Thanks!
Laura

reproducibility of results between github, galaxy instance and biobakery's LEfSe scripts

Dear developers,

Hope everything's ok.

I write because I'm having trouble trying to reproduce locally the results of the galaxy instance here https://huttenhower.sph.harvard.edu/galaxy/ (because I have a file bigger than the allowed size in the galaxy instance).

Firstly, I'm confused because the galaxy instance has the stricter all-against-all option (See image below), while the lefse_run.py --help reports that the stricter option is one-against-one, with no all-against-all option:

-y {0,1}        (for multiclass tasks) set whether the test is performed in a one-against-one ( 1 - more strict!) or in a one-against-all setting ( 0 - less strict) (default 0)

Secondly. after running LEfSe from galaxy and biobakery locally with python2.7 (ubuntu 20.04 and rpy2 compatible, R3.6.3) and from GitHub with python3, I have found that LDA scores differ subtly, but enough to drop one or two features below the threshold, while the galaxy instance reports them. I used abs(LDA) > 2. Do you have any clue about what interferes with reproducibility? I see that you set a random number seed here https://github.com/biobakery/galaxy_lefse/blob/2ca4bf39cbbe588b979873b234636670565b4caf/lefse.py#L9, but many other things can change things.

Finally, I don't know if you maintain the LEfSe versions at https://toolshed.g2.bx.psu.edu/, however, I installed both available versions in a local galaxy server and couldn't run Format Data for LEfSe because my local instance has python3 instead of python2. The biobakery's LEfSe for galaxy also needs python2 to run properly.

If you need more details or a better explanation, please don't hesitate and ask me.

Best regards

The result is not replicated from the same command

I thought that it could be a problem that lefse may not reproduce the result. Here, it used python wrapper to call R function. Although python set seed is here but not for R at the Linear Discriminant Analysis step. I add r_objects.r("set.seed(123)"). But the replication is still different. I don't know why, but could you help me to clarify whether your team preferred to have random results or your team missed this function. If so, please help to fix this issue. Thank you.

Error in OTU without subclass and subject

python3 format_input.py input.txt output.in

Traceback (most recent call last):
  File "format_input.py", line 453, in <module>
    class_sl,subclass_sl,class_hierarchy = get_class_slices(list(zip(cls['class'], cls['subclass'], cls['subject'])))
KeyError: 'subject'

Broken link

lefse/example/bioconda-lefse_run.sh

Line 11 in 200aa6a

 wget https://github.com/biobakery/biobakery/raw/master/demos/biobakery_demos/data/lefse/input/hmp_small_aerobiosis.txt -O hmp_aerobiosis_small.txt 

It should probably be https://github.com/biobakery/biobakery/tree/master/test_suite/biobakery_tests/data/lefse/input/hmp_small_aerobiosis.txt and the file was also renamed.

lefse doesn't work with python 3

When trying to install in a conda environment:

:~$ conda install -c biobakery lefse
Collecting package metadata (current_repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: failed with repodata from current_repodata.json, will retry with next repodata source.
Collecting package metadata (repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: | 
Found conflicts! Looking for incompatible packages.
This can take several minutes.  Press CTRL-C to abort.
failed                                                                                                                                                                                                     

UnsatisfiableError: The following specifications were found
to be incompatible with the existing python installation in your environment:

Specifications:

  - lefse -> python[version='>=2.7,<2.8.0a0']

Your python: python=3.8

If python is on the left-most side of the chain, that's the version you've asked for.
When python appears to the right, that indicates that the thing on the left is somehow
not available for the python version you are constrained to. Note that conda will not
change your python version to a different minor version unless you explicitly specify
that.

The following specifications were found to be incompatible with your system:

  - feature:/linux-64::__glibc==2.31=0
  - feature:|@/linux-64::__glibc==2.31=0

Your installed version is: 2.31

I saw that the code on GitHub was recently updated to work with python 3 but this doesn't seem to work.
Any idea how to resolve this ?

Thanks,
Rudy

lefse.error

I met something wrong when i run the 'lefse_run.py' in lefse1.1.2_r4.0.3_py3, like this

but when I run in python2,it worked. looking forward for your reply!

Lefse Installation Issue

Hello,

I have been trying for the last two days to install lefse on a cluster at my university. I have verified that all R libraries have been installed along with conda / python / etc. However, every time I try to install lefse, there are conflicts at the 'solving environment' phase. I have tried different versions of python following similar troubleshooting posts to no avail. Does anyone have a suggestion? Thank you!

(base) [gfh16@compt341 ~]$ conda create -n thelefse python=3.7
.
.
.

(base) [gfh16@compt341 ~]$ conda activate thelefse
(thelefse) [gfh16@compt341 ~]$ conda install -c bioconda lefse
Collecting package metadata (current_repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: failed with repodata from current_repodata.json, will retry with next repodata source.
Collecting package metadata (repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: |
Found conflicts! Looking for incompatible packages.
This can take several minutes. Press CTRL-C to abort.
failed

UnsatisfiableError: The following specifications were found to be incompatible with each other:

Output in format: Requested package -> Available versions

Package libgcc-ng conflicts for:
sqlite -> libgcc-ng[version='>=10.3.0|>=12|>=9.4.0|>=9.3.0|>=7.5.0|>=7.3.0|>=4.9|>=11.2.0|>=7.2.0']
libzlib -> libgcc-ng[version='>=10.3.0|>=12|>=7.5.0']
setuptools -> python[version='>=3.7'] -> libgcc-ng[version='>=10.3.0|>=12|>=9.4.0|>=9.3.0|>=7.5.0|>=7.3.0|>=4.9|>=11.2.0|>=7.2.0']
xz -> libgcc-ng[version='>=11.2.0|>=12|>=7.5.0|>=7.3.0|>=4.9|>=7.2.0']
libgcc-ng
.
.
.

Package wheel conflicts for:
python=3.7 -> pip -> wheel
wheel
pip -> wheelThe following specifications were found to be incompatible with your system:

- feature:/linux-64::__glibc==2.28=0
- feature:|@/linux-64::__glibc==2.28=0
- libffi -> libgcc-ng[version='>=9.4.0'] -> __glibc[version='>=2.17']
- libgcc-ng -> __glibc[version='>=2.17']
- libnsl -> libgcc-ng[version='>=9.4.0'] -> __glibc[version='>=2.17']
- libstdcxx-ng -> __glibc[version='>=2.17']
- libzlib -> libgcc-ng[version='>=10.3.0'] -> __glibc[version='>=2.17']
- ncurses -> libgcc-ng[version='>=10.3.0'] -> __glibc[version='>=2.17']
- python=3.7 -> libgcc-ng[version='>=9.4.0'] -> __glibc[version='>=2.17']
- readline -> libgcc-ng[version='>=9.3.0'] -> __glibc[version='>=2.17']
- sqlite -> libgcc-ng[version='>=10.3.0'] -> __glibc[version='>=2.17']
- tk -> libgcc-ng[version='>=9.4.0'] -> __glibc[version='>=2.17']
- xz -> libgcc-ng[version='>=7.5.0'] -> __glibc[version='>=2.17']

Your installed version is: 2.28

Note that strict channel priority may have removed packages required for satisfiability.

installation problem

When I install lefse with conda, I found that it conflicted with the newest python3.9. I found it should be installed in the environment (python3.7) which it could be pre created.
{
conda create -n lefse -c bioconda python=3.7
conda activate lefse
conda install -c bioconda lefse
}

lefse galaxy server does not work

Lefse galaxy server does not work. Any alternative server? Many thanks.

Python 3 or 2.7?

The scripts on GitHub seem to indicate that LEfSE should use python3. However, when I try to install via conda, I have see the following error.

UnsatisfiableError: The following specifications were found to be in conflict:
  - lefse -> python[version='>=2.7,<2.8.0a0']
  - python=3

There also seem to be issues with the docker image. I have tried to run "plot_cladogram.py" within the biobakery/lefse image and receive the following error message.

Traceback (most recent call last):
  File "/export/local_tools/lefse/plot_cladogram.py", line 3, in 
    import os,sys,matplotlib,argparse,string
ImportError: No module named matplotlib

Any help would be greatly appreciated!

Thanks!

error with plot_cladogram.py

Hello,

I have found a problem running the plot_cladogram.py with the hmp_aerobiosis_small.txt test data:

Traceback (most recent call last):
  File "/opt/repositories/git-reps/lefse.SegataLab/plot_cladogram.py", line 340, in <module>
    clad_tree = read_data(params['input_file'],params)    
  File "/opt/repositories/git-reps/lefse.SegataLab/plot_cladogram.py", line 106, in read_data
    abundances = [float(v) for v in zip(*rows)[1] if v >= 0.0]
TypeError: 'zip' object is not subscriptable

Best regards.

PS: Also, the link http://huttenhower.sph.harvard.edu/webfm_send/129 shows a 404 error. I downloaded the hmp_aerobiosis_small.txt from https://raw.githubusercontent.com/xiucz/metagenome1/master/LEfSe/lefse/example/hmp_aerobiosis_small.txt

Plot only genus

How can I have only the genus plotted

rpy2.rinterface_lib.embedded.RRuntimeError: Error: protect(): protection stack overflow

Hi,
I met this error information, when I run this code: lefse_run.py. I found the cause is maybe my input file is too large, 247,727 rows.
So how can I do to solve it?
lefse.type.ms2.log.txt

KW/Wilcoxon tests stratification

Hi all,

We want to cite lefse as a paper in our methods and have 2 questions. Your paper says that:

"The factorial KW rank sum test is applied to each feature with respect to the class factor; the subclass and subject information are used as stratifying subgroups when present."

Does this refer to the KW test? because in the code it only looks like there's a comparison between classes (and subclass is only taken into account in the Wilcoxon step portion; while subject is used in the LDA model)

And finally, if there is not subclass, is the Wilcoxon test performed between classes or skipped altogether?

Thanks so much, great tool you guys have here!!!

Best,
John

issue with wilcoxon signed rank test

Hi
I am trying to run lefse on an OTU dataset, but it keeps failing at the wilcoxon signed rank step.
Do you have any advice?

Thanks
Laura

lefse_run.py OTU_Sample2.in samples_16S_otu.res


Number of significantly discriminative features: 5307 ( 84201 ) before internal wilcoxon
R[write to console]: Error in .Primitive("[")(c(72519.717356904, 53305.4470592899, 43080.6615065647,  :
  subscript out of bounds
Traceback (most recent call last):
  File "/fs/ess/PAS1212/bioinformatic_tools/miniconda3/envs/lefse-1.1.2/bin/lefse_run.py", line 10, in <module>
    sys.exit(lefse_run())
  File "/fs/ess/PAS1212/bioinformatic_tools/miniconda3/envs/lefse-1.1.2/lib/python3.7/site-packages/lefse/lefse_run.py", line 90, in lefse_run
    if params['rank_tec'] == 'lda': lda_res,lda_res_th = test_lda_r(cls,feats,class_sl,params['n_boots'],params['f_boots'],params['lda_abs_th'],0.0000000001,params['nlogs'])
  File "/fs/ess/PAS1212/bioinformatic_tools/miniconda3/envs/lefse-1.1.2/lib/python3.7/site-packages/lefse/lefse.py", line 225, in test_lda_r
    res = dict([(pp,[float(ff) for ff in rres.rx(pp,True)] if pp in rowns else [0.0]*lenc ) for pp in [p[0],p[1]]])
  File "/fs/ess/PAS1212/bioinformatic_tools/miniconda3/envs/lefse-1.1.2/lib/python3.7/site-packages/lefse/lefse.py", line 225, in <listcomp>
    res = dict([(pp,[float(ff) for ff in rres.rx(pp,True)] if pp in rowns else [0.0]*lenc ) for pp in [p[0],p[1]]])
  File "/fs/ess/PAS1212/bioinformatic_tools/miniconda3/envs/lefse-1.1.2/lib/python3.7/site-packages/rpy2/robjects/vectors.py", line 79, in __call__
    res = fun(*conv_args, **kwargs)
  File "/fs/ess/PAS1212/bioinformatic_tools/miniconda3/envs/lefse-1.1.2/lib/python3.7/site-packages/rpy2/rinterface_lib/conversion.py", line 45, in _
    cdata = function(*args, **kwargs)
  File "/fs/ess/PAS1212/bioinformatic_tools/miniconda3/envs/lefse-1.1.2/lib/python3.7/site-packages/rpy2/rinterface.py", line 680, in __call__
    raise embedded.RRuntimeError(_rinterface._geterrmessage())
rpy2.rinterface_lib.embedded.RRuntimeError: Error in .Primitive("[")(c(72519.717356904, 53305.4470592899, 43080.6615065647,  :
  subscript out of bounds

import lefse.lefse error

It's a good news to hear lefse support python3.
I have already installed the new-lefse with command "python3 setup.py install"
The installed message like these,I think it means it success installed

Then I run the command
format_input.py ----ok
run_lefse.py lefse_plot_res.py all appear mes :"ModuleNotFoundError: No module named 'lefse.lefse'; 'lefse' is not a package"
I try to change the import module lefse.lefse to lefse and can run the lefse
I'm not sure if I'm using the right method to solve this even,please help me to confirm it
Thans alot

ValueError: could not convert string to float: "whole"?

hello could you please let me know why I am getting this error when I try to convert my data file into lefse input?
$ lefse_format_input.py lefsegalaxy.txt lefsegalaxy.in -c 1 -s 2 -u 3 -o 1000000

attached the file
lefseGalaxy.txt

segatalab / lefse Goto Github PK

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