Software on M3¶
M3 uses a modular system to manage software.
Modules¶
Modules is software installed on M3 that provides an easy mechanism for updating your environment variables, so that your environment uses the correct
version of software and libraries installed on M3.
Installed software modules¶
Jump to software beginning with A B C D E F G H I J K L M N O P Q R S T U V W X Y Z.
Attention
Some software packages on M3 have license conditions that restrict
access to the software to certain user groups. These software packages are
marked with the restricted keyword. To apply for access to restricted
software,
log in to the HPC ID system and
navigate to the Software section of your profile. To enquire about
restricted software contact the MASSIVE Help Desk
Note
Software packages with a version named ansto are copies of the software
installed on the ASCI facility
Note
The Monash Bioinformatics Platform (MBP) maintains a software stack on M3. More information, including how to access this software stack, can be found on the Bioinformatics community page.
Software |
Version(s) |
|---|---|
3daprecon |
0.0.1, 1.0 |
3depict |
0.0.15 |
3dslicer |
4.10.2, 4.6.0, 4.8.1 |
A |
|
abaqus |
6.14 |
abinit |
8.8.3 |
abricate |
0.8.13 |
abyss |
2.0.2 |
adapterremoval |
2.3.1 |
adf |
2019.104 |
adxv |
1.9.12 |
afni |
16.2.16, 17.0.11 |
align2rawsignal |
2.0 |
allpathslg |
52488 |
amber |
18-multi-gpus, 18-parallel, 18-serial, 18-single-gpu |
amira |
6.3.0, 6.4.0, 6.5.0 |
anaconda |
2018.12-Python3.7-gcc6, 2019.03-Python3.7-gcc5, 4.3.1-Python3.5, 4.3.1-Python3.5-gcc5, 5.0.1-Python2.7-gcc5, 5.0.1-Python3.5-gcc5, 5.0.1-Python3.6-gcc5, 5.1.0-Python3.6-gcc5 |
analyze |
12.0 |
analyze-temp |
12.0 |
ansys |
18.1, 19.1, 19.2 |
ants |
1.9.v4, 20190910, 2.2.0, 2.3.1 |
apex |
latest |
apr |
1.6.5 |
apr-util |
1.6.1 |
argos |
3.0.0-beta52 |
ariba |
2.12.1 |
armadillo |
9.200-rc1 |
arpack |
2.1, 3.1.3-2 |
ascp |
3.5.4 |
ashs |
1.0.0 |
atlas |
3.10.2-gcc4, 3.10.2-gcc5 |
atom |
1.39.1 |
atomprobedevcode |
1.0.0(default) |
attr |
2.4.46-12 |
augustus |
3.3.3 |
autodock_vina |
1.1.2 |
automake |
1.16.1, 1.4-p6 |
autometa |
2019-09 |
avizo |
9.0.1, 9.3.0, 9.3.0.1, 9.4.0, 9.5.0, 9.7 |
axel |
2.12 |
B |
|
bamsurgeon |
1.2 |
bamtools |
2.4.1 |
barrnap |
0.9 |
bart |
0.4.04, 0.4.04-cuda9.0 |
bayenv |
2.0 |
bayesass |
1.3, 3.04 |
bayescan |
2.1 |
bbcp |
17.12 |
bcbtoolkit |
4.0.0 |
bcftools |
1.6, 1.7, 1.8 |
bcl2fastq |
2.19.1 |
beagle |
2.1.2, 3.1.2 |
beast1 |
1.10.0, 1.8.4 |
beast2 |
2.4.7, 2.4.8, 2.5.0 |
bedtools |
2.26.0, 2.26.0-gcc5, 2.27.1-gcc5 |
bgen |
1.1.4 |
bids-validator |
1.3.1, 2019.01 |
bidscoin |
2.2 |
bigdatascript |
v0.99999e |
bigwigtowig |
377-0 |
bilm-tf |
1.0 |
biscuit |
0.2.2, 0.3.8.20180515 |
bismark |
v0.19.1 |
bison |
2.7.1 |
blas |
3.8.0-gcc5, 3.8.0-gcc5-pic |
blast |
2.2.30, 2.3.0, 2.7.1(default) |
blast+ |
2.9.0 |
blender |
2.81 |
bolt-lmm |
2.3.2, 2.3.4 |
boost |
1.46.0-gcc5, 1.46.1-gcc5, 1.52.0-gcc5, 1.58.0, 1.58.0-gcc5, 1.62.0, 1.62.0-gcc4, 1.67.0-gcc5 |
bowtie |
1.1.2 |
bowtie2 |
2.2.9, 2.3.5 |
bracken |
2.5 |
brain_age |
v1.0_18Jan2018 |
breseq |
0.29.0, 0.33.2 |
bsoft |
1.9.2, 2.0(default) |
busco |
3.0.2 |
buster |
20170508 |
bwa |
0.7.12, 0.7.17-gcc5 |
bwa-meth |
0.2.2 |
bzip2 |
1.0.6 |
C |
|
caffe |
1.0.0, 1.0.0-protbuf32, caffe-matlab, caffe-tsn, deepvistool, latest(default), rc4 |
caffe2 |
0.8.1 |
caffe_enet |
1.0 |
caffe_unet |
1.0, 18.04, 2.0 |
canu |
1.7.1 |
caret |
5.65 |
caw |
0.2.4(default) |
cblas |
20032302-gcc5 |
ccp-em |
1.3.0 |
ccp4 |
7.0, 7.0.072, ccp4i, ccp4i2, ccp4mg, coot |
cdhit |
4.8.1 |
cellprofiler |
2.2.0, 3.1.5 |
cellprofileranalyst |
2.2.0 |
cellranger |
2.0.1, 3.0.2 |
centrifuge |
1.0.4-beta |
chimera |
1.10.2, 1.11, 1.13 |
chimerax |
0.6, 0.8 |
chrome |
68, 69, 75, 77, 78, default |
chuffed |
0.10.3 |
circos |
0.69-6 |
cistem |
1.0.0-beta |
clairvoyante |
1.02 |
clamms |
1.1 |
clonalframeml |
1.11 |
cloudstor |
2.3.1-1.1, 2.4.1, 2.4.2 |
cmake |
2.8.12.2, 2.8.12.2-gcc5, 3.10.2-gcc4, 3.10.2-gcc4-system, 3.10.2-gcc5, 3.15.1-gcc4-system, 3.15.1-gcc5, 3.15.4-gcc8, 3.5.2, 3.5.2-gcc4, 3.5.2-gcc5 |
cmkl |
9.1.023 |
cnvkit |
0.9.5 |
colmap |
3.6 |
comsol |
5.2a, 5.4 |
connectome |
1.2.3 |
convert3d |
1.0.0 |
coot |
0.8.9.1 |
coventormp |
1.002 |
cp2k |
5.1.0, 6.1.0 |
cplex |
12.6, 12.6.3, 12.7.1, 12.8.0 |
cpmd |
3.17.1, 4.3 |
crisprcasfinder |
1.05 |
crispresso |
1.0.13-gcc5 |
crossmap |
0.3.5, 0.3.6 |
cryo-em-processing-tool |
0.1 |
cryoef |
1.1.0 |
cryolo |
1.0.0, 1.1.3, 1.3.1, 1.4.0, 1.4.1, 1.5.3 |
cryosparc |
beta, cryosparc-cluster, v2 |
crystallography |
0.0.3(default) |
cst |
2017 |
ctffind |
4.0.17, 4.1.10, 4.1.13, 4.1.3, 4.1.4, 4.1.8 |
ctftilt |
latest |
cuda |
10.0, 10.1, 4.1, 4.1.bajk, 6.0, 7.0, 7.5, 8.0, 8.0.61, 8.0-DL, 9.0, 9.1 |
cudadeconv |
1.0 |
cudalibs8to9 |
0.1 |
cudnn |
5.1, 5.1-DL, 7.1.2-cuda8, 7.1.3-cuda9, 7.3.0-cuda9, 7.6.5-cuda10.1 |
cufflinks |
2.2.1 |
cunit |
2.1.3 |
cutadapt |
0.16, 2.5, 2.7 |
cytoscape |
3.4.0 |
D |
|
daris-utils |
1.0 |
darknet |
alexey, darknet_yolo_v3, latest |
dcm2niix |
latest |
dcmtk |
3.6.3 |
deep-complex-networks |
2017 |
deepmedic |
0.6.1, 0.7.0 |
deeptools |
3.1.2, 3.1.3 |
deepvariant |
0.8-cpu, 0.8-gpu |
dense3dcrf |
20160527 |
detectron |
20180322 |
dftbplus |
18.2 |
dials |
1.12.1, 1.5.1 |
diamond |
0.9.22 |
dicomnifti |
2.32.1 |
diyabc |
2.1.0 |
dmtcp |
2.5.2 |
dominate |
2.3.5 |
dos2unix |
7.4.0 |
dragondisk |
1.0.5 |
drishti |
2.6.3, 2.6.4, ansto |
drmaa |
1.0.7, 1.1.0 |
dti-tk |
2.3.1 |
dtk |
0.6.4.1 |
dynamo |
1.1.178(default), 1.1.451 |
dynet |
2.1-cpu, 2.1-gpu |
E |
|
ea-utils |
1.1.2, 1.1.2-gcc5 |
eclipse |
4.7.3a, 4.8 |
effoff |
0.2.1(default) |
eigen |
2.0.17, 3.2.9, 3.3.0, 3.3.7 |
eigensoft |
7.2.1 |
eiger2cbf |
1.0 |
elf |
1.0 |
eman |
2.12, 2.2, 2.22, 2.3, 2.3.1 |
emap-galaxy-shortcut |
1.0.0(default) |
emap-mytardis-shortcut |
1.0.0(default) |
emap-wiki-shortcut |
0.0.1(default) |
emapaccess |
1.0(default) |
emboss |
6.6.0 |
emclarity |
1.0.0 |
emspring |
spring_v0-84-1470, spring_v0-84-1470_mlx |
epacts |
3.3.2 |
exciting |
nitrogen |
exonerate |
2.4.0 |
exploredti |
4.8.6 |
F |
|
fastani |
1.1 |
fastml |
3.1, 3.11 |
fastp |
0.20.0 |
fastqc |
0.11.7 |
fastQValidator |
0.1.1a |
fastspar |
0.0.7 |
fasttree |
2.1.10 |
fastx-toolkit |
0.0.13 |
fcsalyzer |
0.9.12 |
fdtd |
2020a-r1, 8.21.1933 |
feedback |
1.0.1(default) |
ffmpeg |
3.4.2 |
fftw |
3.3.4-gcc, 3.3.5-gcc, 3.3.5-gcc5 |
fgbio |
0.9.0 |
figtree |
1.4.3 |
fiji |
20160808, 20170223, 20170530, current, current.bak, MMI-MHTP |
fix |
1.064, 1.068 |
flash |
1.2.11-gcc5 |
flashpca |
2.0 |
flexbar |
3.4.0 |
flye |
2.3.5 |
fmriprep |
1.0.15, 1.1.1, 1.2.5, 1.3.0_post2, 1.4.0, 1.4.1 |
foma |
0.9.18 |
fooof |
0.1.3 |
fouriertransform |
0.2.3(default) |
freebayes |
0.9.9 |
freesurfer |
20160922, 5.3, 6.0, 6.0-patch, devel-20171013, devel-20180612, devel-20190128 |
frustum |
xflx1992 |
fsl |
5.0.11, 5.0.9, 6.0.0, 6.0.1, 6.0.3 |
fsleyes |
0.22.4, 0.23.0, 0.24.3, 0.32.0 |
ftgl |
2.1 |
fxtract |
2.3 |
G |
|
gamess |
16srs1, 16srs1-v2, 2018r3 |
gap |
4.8.10 |
gatan |
free, uwa |
gatk |
3.4, 3.7, 4.0.1.1, 4.0.11.0, 4.1.2.0 |
gatktool |
0.0.1 |
gauss |
11.0, 9.0 |
gaussian |
g16a03 |
gautomatch |
0.53, 0.56 |
gcat |
e48bf8b |
gcc |
4.9.3, 5.4.0, 6.1.0, 8.1.0 |
gcta |
1.92.2beta |
gctf |
0.50, 0.66, 1.06, 1.06_cuda8, 1.06_cuda8-uow, 1.08_cuda8, 1.18, 1.18_b2, 1.18_b2_cuda9, 1.18_cuda8, 1.18_cuda8-uow, 1.18_cuda91 |
gd-devel |
2.0.35 |
gdal |
2.2.4, 2.3.1, 3.0.2 |
gdb |
8.2.1 |
gdcm |
2.6.6-gcc4, 2.6.6-gcc5 |
geant4 |
10.02.p03, 10.03.p01 |
gem |
3.3 |
gemini |
0.30.1 |
gengetopt |
2.10 |
genotypeharmonizer |
1.4.20 |
genrich |
v0.6 |
geos |
3.6, 3.7.2 |
gephi |
0.9.2 |
gflags |
master, master-gcc4 |
ghostscript |
9.26 |
gimp |
2.8, 2.8.22 |
gingerale |
2.3.6 |
git |
2.17.0, 2.19.0, 2.8.1 |
git-annex |
6.20180227 |
glew |
2.0-gcc4, 2.0-gcc5 |
glm |
0.9.9.5 |
glog |
master, master-gcc4 |
glpk |
4.60 |
gmp |
6.1.2 |
gmsh |
3.0.3 |
gnuparallel |
20160822, 20190122 |
gnuplot |
5.2.1 |
go |
1.11.1 |
goctf |
1.1.0 |
gpu_burn |
0.9, 1.0 |
gpucomputingsdk |
4.0.17 |
graphviz |
2.30.1, 2.40.1 |
gromacs |
2016.3-openmpi-cuda8.0, 2016.4-openmpi-cuda8.0, 2016.5-openmpi-cuda8.0-plumed, 2018.4-openmpi-cuda8.0, 2018.7-openmpi-cpu-only, 2018.7-openmpi-cuda-plumed, 2018-openmpi-cuda8.0, 2018-openmpi-cuda8.0-NVML(default), 2019.4-openmpi-cuda10.0, 5.1.4 |
gsl |
1.15.13-system, 2.2-gcc4(default), 2.2-gcc5, 2.2-system, 2.5-gcc4 |
gst-devel |
1.4.5 |
gst-libav |
1.10.4, 1.4.5 |
gtdb-tk |
0.3.2 |
gubbins |
2.3.2 |
guppy |
3.1.5-1, 3.2.4, container |
gurobi |
7.5.1, 8.0.0, 9.0.0 |
gvcftools |
0.17.0 |
H |
|
h5toxds |
1.1.0 |
haplomerger2 |
20180603 |
haystack_bio |
0.5.5 |
hdf5 |
1.10.0-patch1, 1.10.5 |
hdfview |
3.0 |
heudiconv |
0.5.4 |
hisat2 |
2.1.0 |
hmmer |
2.4i, 3.2.1 |
horovod |
0.16.4 |
hotspot |
4.0.0 |
hpcx |
2.5.0 |
htop |
2.0.1 |
htseq |
0.10.0 |
htslib |
1.7, 1.9, 1.9-gcc5 |
huygens |
16.10.1-p1 |
hyperspy |
1.4 |
hyphy |
2.5.0 |
hypre |
2.11.2, 2.15.0 |
I |
|
icm |
3.7-3b, 3.8.7 |
idl |
8.6 |
idr |
2.0.3 |
igv |
2.3.81, 2.4.19 |
ihrsr++ |
v1.5 |
ilastik |
1.2.0, 1.3.3 |
illumina-utils |
2.6, 2.6-python3.7 |
imagej |
20160205 |
imagemagick |
7.0.5-7, 7.0.8-23, 7.0.8.23-native |
imagescope |
11.2.0.780 |
imblproc |
20190405 |
imod |
4.8.54, 4.9.12, 4.9.9 |
imod-raza |
4.7.12 |
imosflm |
7.2.1, 7.2.2 |
impute2 |
2.3.1 |
intel |
2015.0.090, 2016, 2017u4, 2018test, 2018u3 |
iqtree |
1.5.3, 1.6.10, 1.6.2, 2.0-rc1 |
ismapper |
2.0 |
itk |
4.10.0-gcc4, 4.10.0-gcc5, 4.10.0-gcc5-p1, 4.13.0-gcc4, 4.13.1-gcc4, 4.8.2-gcc4, 4.8.2-gcc5, ansto |
itksnap |
3.3.x(default), 3.8.0, 3.8.0-beta |
J |
|
jags |
3.3.0, 3.4.0, 4.3.0 |
java |
1.7.0_67, 1.8.0_77(default) |
jdk |
10-20180320, 14 |
jellyfish |
1.1.12, 2.3.0(default), 2.3.0-gcc5 |
jspr |
2017-7-20 |
juicer |
1.6.2 |
julia |
0.6.4 |
K |
|
kallisto |
0.43.0 |
kaptive |
0.5.1 |
kilosort |
1.0 |
king |
2.1.6 |
kleborate |
0.2.0, 0.3.0 |
kraken |
1.1.1 |
kraken2 |
2.0.7-beta |
krakenuniq |
0.5.8 |
kronatools |
2.7.1 |
L |
|
lammps |
20180510(default), 20181212 |
lapack |
3.6.1-gcc4, 3.6.1-gcc4-opt, 3.6.1-gcc5, 3.8.0-gcc5, 3.8.0-gcc5-pic |
ldmap |
28apr15 |
ldpred |
1.0.6 |
leveldb |
master, master-gcc4 |
levelset |
0.0.2(default) |
libertem |
20190521 |
libffi |
3.2.1 |
libffi-devel |
3.0.13 |
libfuse |
3.6.1 |
libgd |
2.2.4 |
libgeotiff |
1.4.2 |
libharu |
2.2.1 |
libint |
1.1.4 |
libjpeg-turbo |
1.4.2, 1.5.1, 1.5.1-shared |
libsmm |
20150702 |
libtiff |
3.9.7, 4.0.10 |
libunwind |
1.3.1 |
libuuid |
2.23.2-43 |
libxc |
4.1.0 |
libxsmm |
1.9 |
libzip |
0.10.1-8 |
lighter |
1.1.2 |
lkh |
2.0.9 |
lmdb |
latest |
locuszoom |
1.4 |
lofreq |
2.1.3.1 |
lsd |
0.3beta |
M |
|
macs2 |
2.1.1.20160309 |
mafft |
7.310 |
magic-impute |
1.5.5 |
magma |
1.6.1, 2.0.2 |
mainmast |
1.0 |
mango |
4.0.1 |
manta |
1.5.0-gcc5 |
mantid |
3.13.0, 3.8.0, 3.9.0 |
mapdamage |
2.0.9(default), 2.0.9-u1 |
mash |
2.1(default), 2.1.1 |
materialsstudio |
18.1.0 |
mathematica |
11.0.1, 12.0.0 |
mathgl |
1.11.2, 2.0.3(default), 2.3.3 |
matlab |
r2012b, r2014a, r2014b, r2015b, r2016a, r2017a, r2017b, r2017b-caffe, r2018a, r2019a |
mauve |
20150213 |
maven |
3.3.9 |
maxquant |
1.6.5.0 |
mc |
4.8.21 |
mcl |
11-294 |
mcr2010b |
1.0 |
megahit |
1.1.3, 1.2.4-beta, 1.2.9 |
meld |
0.4.14 |
meme |
5.0.1 |
merantk |
1.2.1 |
mercurial |
4.7.1 |
mesa |
13.0.5, default |
meshlab |
2016.12-gcc5, 2019.03 |
meson |
0.51.0 |
metal |
2011 |
metaplotr |
2018_09 |
metawrap |
1.1.3 |
mevislab |
2.8.1-gcc-64bit |
miakat |
4.2.6 |
minc-lib |
2.2-git-gcc4 |
minc-tools |
2.2 |
miniconda3 |
4.1.11-python3.5 |
minimap2 |
2.17-r954-dirty |
minizinc |
2, 2.3.1 |
mixcr |
3.0.7 |
mkl |
2018u3 |
mlst |
2.15 |
mne |
TF-201804 |
molden |
5.7 |
mono |
5.20.1.19 |
moose |
1.0 |
morphind |
1.4 |
motioncor2 |
20180924, 20181020, 20181020-cuda91, 2.1, 2.1.10-cuda8, 2.1.10-cuda9.1, 2.1.3.0-cuda101, 2.1.3.0-cuda80 |
motioncorr |
2.1 |
motioncorr2 |
20160822 |
mpfr |
3.1.5 |
mpifileutils |
20170922 |
mpip |
3.4.1 |
mrbayes |
3.2.6, 3.2.6-mpi |
mrf |
0.2.2(default) |
mriconvert |
2.1.0 |
mricrogl |
1.0.20170207, 20180623 |
mricron |
06.2013, 30apr2016 |
mriqc |
0.14.2, 0.9.7 |
mrtrix |
0.3.15-gcc4, 0.3.15-gcc5, 0.3.16, 20170712, 3.0_rc3, 3.0_rc3_latest |
mrtrix3tissue |
5.2.8 |
msm_hocr |
3.0 |
mummer |
3.23-gcc5, 4.0.0.beta2-gcc5 |
muscle |
3.8.31 |
mustem |
5.3 |
mxtools |
0.1 |
mytardis |
0.1(default) |
N |
|
namd |
2.12-ibverbs-smp-cuda, 2.12-multicore, 2.13-multicore-CUDA |
nanofilt |
201807 |
nanopolish |
0.10.1, 0.11.1 |
nccl |
2.4.7-cuda10.0, 2.4.7-cuda9.1, master, master-gcc4 |
netcdf |
4.4.1.1(default), 4.4.1.1-openmpi-1.10.7-mlx, 4.7.0, 4.7.1-intel |
neuro-workshop |
20191115 |
neuro_workflow |
2017v2 |
new-fugue |
2010-06-02 |
newick-utils |
1.6 |
nextgenmap |
0.5.5 |
ngsqctoolkit |
2.3.3 |
nibabel |
2.3.3 |
niftilib |
2.0.0 |
nighres |
1.1.0b1 |
niistat |
9.oct.2016 |
ninja |
1.9.0 |
nis-elements-viewer |
4.20 |
nlopt |
2.6.1 |
nn |
0.2.4(default) |
novactf |
03.2018 |
nullarbor |
2.0.20181010 |
O |
|
objexport |
0.0.4(default) |
octave |
4.2.2 |
octopus |
8.4, 8.4-parallel |
openbabel |
2.4.1 |
openblas |
0.2.20 |
opencv |
3.4.1, 3.4.1-gcc4, 4.1.0 |
openfoam |
4.1, 5-paraview54, 5.x |
openjpeg |
2.3.0 |
openmpi |
1.10.3-gcc4-mlx, 1.10.3-gcc4-mlx-cuda75, 1.10.3-gcc4-mlx-verbs, 1.10.3-gcc4-mlx-verbs-cuda75, 1.10.3-gcc5, 1.10.3-gcc5-mlx, 1.10.7-1.mlx, 1.10.7-intel, 1.10.7-mlx(default), 1.10.7-mlx-intel, 3.1.4-mlx |
opennmt-py |
0.7.0 |
openrefine |
3.1 |
orange3 |
ansto |
orca |
4.0.1(default), 4.2.1 |
orfm |
v0.7.1 |
P |
|
packer |
1.3.5 |
paleomix |
1.2.13.4-python2 |
paml |
4.9 |
pandoc |
2.7.3 |
paraview |
4.0.1, 5.6.0, ansto |
partitionfinder2 |
2.1.1 |
pastml |
1.0 |
pbzip2 |
1.1.13 |
peakseq |
1.3.1 |
perl |
5.24.0, 5.28.0(default), 5.30.1 |
petsc |
3.10.1-gcc5, 3.12.1 |
pgap |
3958 |
pgi |
19.4, 2019 |
phate |
0.4.4 |
phenix |
1.11.1, 1.15.1, 1.15.2 |
phreeqc |
3.5.0 |
phyml |
3.1 |
picard |
2.19.0, 2.9.2 |
picrust2 |
2.1.4_b(default), 2.2.0_b |
pigz |
2.3.3, 2.3.4 |
pilon |
1.22 |
pindel |
0.6.3-gcc5 |
plink |
1.7, 1.9, 1.90b6.10, 2.0-alpha |
plinkseq |
0.10 |
plumed |
2.5.0 |
pmix |
4.0.0, v2.2 |
pointless |
1.10.28 |
posgen |
0.0.1(default) |
posminus |
0.2.3(default) |
pplacer |
v1.1.alpha19 |
prank |
170427 |
prismatic |
1.1 |
prismatic-cpu |
1.1 |
prodigal |
2.6.3 |
proj |
4.9.3, 5.1.0, 6.2.1 |
prokka |
1.13.3(default), 1.14.5 |
protobuf |
master, master-gcc4 |
protomo |
2.4.2 |
psi4 |
v1.1 |
pulchra |
3.06 |
purge_haplotigs |
1.1.0 |
pv |
1.6.6 |
py4dstem |
0.3 |
pybids |
0.9.1 |
pycharm |
2018.3.3 |
pydeface |
1.1.0 |
pyem |
v0.1, v0.1-201806, v0.3 |
pymol |
1.8.2.1, 1.8.6, 2.4.0a0 |
pyprismatic |
1.1.16 |
pypy |
7.0.0-3.6 |
pysam |
0.15.2-python2 |
python |
2.7.11-gcc, 2.7.12-gcc4(default), 2.7.12-gcc5, 2.7.15-gcc5, 2.7.17-gcc8, 3.5.2-gcc, 3.5.2-gcc4, 3.5.2-gcc5, 3.6.2, 3.6.2-static, 3.6.6-gcc5, 3.7.2-gcc6, 3.7.3-system |
pytom |
0.971 |
pytorch |
1.0-cuda10, 1.1-cuda10(default), 1.3-cuda10 |
pyxnat |
1.1.0.2, 20170308 |
Q |
|
qatools |
1.2 |
qctools |
v2.0-beta |
qgis |
3.9.0 |
qhull |
2003.1, 2015.2 |
qiaseq-dna |
1.0(default), 14.1 |
qiime1 |
1.9.1 |
qiime2 |
2017.9, 2018.11, 2018.2, 2018.4, 2019.1, 2019.4, 2019.7-q2_scnic, 2019.7-q2_scnic_2 |
qt |
5.7.1-gcc5 |
qt5-qtwebkit |
5.9.1 |
quicktree |
2.0, 2.5 |
quit |
1.1, 2.0.2 |
qupath |
0.2.0-m4 |
R |
3.3.1, 3.4.3, 3.5.0, 3.5.1, 3.5.2-openblas, 3.5.3-mkl, 3.6.0-mkl |
R |
|
r-launcher |
0.0.1(default) |
racon |
1.3.1 |
raremetal |
4.15.1 |
raxml |
8.2.12, 8.2.9 |
razers3 |
3.5.8 |
rclone |
1.49.3 |
rdf-kd |
0.0.1(default) |
rdkit |
2019.03.3.0 |
relion |
1.4, 2.02, 2.0.6, 2.0beta, 2.1(default), 2.1.b1, 2.1.b2, 2.1-openmpi-1.10.7-mlx, 3.0-20181109-cuda80, 3.0-20181109-cuda91, 3.0-20190115, 3.0.5, 3.0.5-uow, 3.0.6, 3.0.6-uow, 3.0.7, 3.0.7-uow, 3.0.7-uow-cuda10.1, 3.0.7-uow-mc2.1.3.0, 3.0-beta, 3.0-stable, 3.0-stable-cuda91, 3.0-stable-uow, 3.0-uow-20180904, 3.0-uow-20180917, 3.0-uow-20181109-cuda80, 3.0-uow-20181109-cuda91, 3.0-uow-20190115, 3.1_beta, 3.1_beta-20191105, 3.1_beta-20191113, 3.1_beta-latest |
resmap |
1.1.4, 1.1.5, 1.9.5 |
rest |
1.8, 1.8-matlab2017a.r6685 |
rings |
1.3.3 |
rnammer |
1.2 |
roary |
3.11.2(default), 3.12.0 |
robex |
1.2 |
root |
5.34.32 |
rosetta |
2018.09 |
rsem |
1.3.0 |
rseqc |
3.0.0 |
rstudio |
1.0.143, 1.0.44, 1.1.414, 1.1.463, 1.1.463-r3.5.3-mkl, 1.1.463-r3.6.0-mkl |
rstudioserver_epigenetics |
1.0, 1.0-20171101 |
rsync |
3.1.3 |
rtk |
ansto |
S |
|
saintexpress |
3.6.3 |
salmon |
0.14.1 |
salome |
9.2.0 |
samclip |
0.2 |
samtools |
0.1.18, 1.3.1, 1.6, 1.7, 1.7-gcc5, 1.9, 1.9-gcc5 |
sas |
9.4 |
sbt |
0.13.15, 1.2.1 |
scalapack |
2.0.2 |
scipion |
2.0, devel, devel-20170327, v1.0.1_2016-06-30, v1.1, v1.1.1, v1.2, v1.2.1, v1.2.1_2018-10-01 |
scrappie |
1.4.1 |
sdm_1d_calculate |
2.0.2(default) |
sdm_1d_plot |
0.0.4(default) |
sdm_2d_calculate |
2.0.2(default) |
sdm_2d_plot |
0.0.4(default) |
segadapter |
1.9 |
seqgen |
1.3.4 |
seqtk |
1.3 |
shapeit |
v2_r837, v2_r904 |
shovill |
1.0.4 |
simnibs |
2.0.1g |
simple |
2.1, 2.5 |
simul-atrophy |
12-09-2017 |
singlem |
0.12.1 |
singularity |
2.3.1, 2.4.2, 2.4.5, 2.5.2, 3.0, 3.0.1, 3.0.2, 3.1.0, 3.2.0, 3.2.1(default), 3.4.0, d3d0f3fdc4390c7e14a6065543fc85dd69ba42b7 |
situs |
3.1 |
ska |
1.0-e1968f0 |
skesa |
2.2.1, 2.3 |
skewer |
20170212 |
slamdunk |
latest |
slim |
3.2 |
slurm |
17.11.4 |
smafa |
0.5.0 |
smcounter |
10apr2017 |
smux |
0.0.1 |
snappy |
master, master-gcc4 |
snippy |
4.3.8 |
snp-dists |
0.6.3 |
snpeff |
4.3t |
snpm |
13 |
soapdenovo2 |
2.04-r241 |
sourcetracker |
2.0.1 |
spades |
3.12.0, 3.13.1 |
sparseassembler |
1.0 |
sparsehash |
2.0.3 |
spectra |
0.8.1 |
spider |
21.11 |
spm12 |
matlab2015b.r6685, matlab2018a.r6685, matlab2018a.r7487 |
spm8 |
matlab2015b.r6685, matlab2017a.r6685 |
sqlite3 |
3.30.1 |
squashfs-tools |
4.3-0.21 |
squashfuse |
0.1.103 |
sra-tools |
2.7.0, 2.9.2, 2.9.4, 2.9.6 |
srst2 |
0.2.0, 0.2.0-2019 |
stacks |
2.4 |
star |
2.5.2b |
stata |
14(default), 14.2, 16 |
stisuite |
3.0 |
strelka |
2.8.4 |
stringtie |
1.3.5, 1.3.6 |
structure |
2.3.4 |
subread |
1.5.1 |
subversion |
1.9.5 |
suitesparse |
5.4.0 |
superlu |
3.1 |
surfice |
7_feb_2017 |
svd |
1.4 |
swig |
3.0.12, 4.0.1 |
synopsys |
3.1(default) |
T |
|
tannertools |
2016.1, 2016.2 |
tapsim |
v1.0b_r766 |
tbb |
20180312oss |
tempest |
1.5 |
tensorflow |
1.0.0-python2.7.12-gcc5, 1.10.0-pytorch, 1.10.0-pytorch-all, 1.10.0-pytorch-keras, 1.12.0-python2.7.12-gcc5, 1.12.0-python3.6-gcc5, 1.13.1-gdal, 1.14.0-keras, 1.14.0-keras-pydicom, 1.3.0-python2.7.12-gcc5, 1.4.0-python2.7.12-gcc5, 1.4.0-python3.6-gcc5, 2.0.0-beta1, 2.0.0-gpu |
terastitcher |
20171106 |
texlive |
2017 |
tiff |
4.0.8 |
tigervnc |
1.8.0 |
tmap |
3.0.1 |
toothmaker |
0.64 |
topaz |
1.0, latest |
tophat |
2.1.1 |
tracer |
1.6 |
trackvis |
0.6.1 |
tractseg |
2.0 |
transdecoder |
5.5.0 |
trim_galore |
0.4.5, 0.5.0 |
trimmomatic |
0.38 |
trinity |
2.8.5(default), 2.8.5-gcc5 |
turbovnc |
2.0.2(default), 2.1.0 |
tvips-tools |
0.0.3 |
U |
|
ucsc-genome-tools |
201806 |
ucx |
1.6.1 |
udunits2 |
2.2.20-2 |
ufo-kit |
ansto |
umap |
0.3.8 |
umi-tools |
0.5.5-python2, 0.5.5-python3 |
unblur |
1.0.2 |
underworld |
2.3.0, 2.8.0b |
unicycler |
0.4.7 |
unimelb-mf-clients |
0.2.7, 0.3.2 |
unrar |
5.0 |
V |
|
valgrind |
3.13 |
varscan |
2.3.9 |
vasp |
5.4.4 |
vcftools |
0.1.15 |
vdjtools |
1.2.1 |
vegas2 |
v02 |
velvet |
1.2.10, 1.2.10-modified |
vep |
90(default), 94 |
vigra |
1.9.0 |
vim |
8.0.0596 |
viptreegen |
1.1.2 |
virtualgl |
2.5.0(default), 2.5.2, 2.6.2 |
visit |
2.12.3 |
vmd |
1.9.3, 1.9.4 |
volview |
3.4 |
voro++ |
0.4.6 |
vscode |
1.39.2 |
vsearch |
2.13.6 |
vt |
0.57 |
vtk |
5.10.1, 5.10.1-gcc4, 7.0.0, 7.0.0-gcc5 |
W |
|
wasp |
0.3.0 |
weblogo |
3.7 |
wfu_pickatlas |
3.0.5b |
wgsim |
0.3.1-r13 |
workspace |
4.0.2 |
wxgtk |
3.0.2 |
wxwidgets |
3.0.3 |
X |
|
xds |
20170302, monash(default), mxbeamteam |
xjview |
9.0, 9.6, 9.7 |
xnat-desktop |
0.96, 1.0.40 |
xnat-upload-assistant |
1.1.3 |
xnat-utils |
0.2.1, 0.2.5, 0.2.6, 0.4.5, 0.4.6, 0.4.9, 0.5.3 |
xnatpy |
0.3.18 |
xvfb |
1.19.3 |
Y |
|
yade |
1.20.0-cpu, 1.20.0-gpu, 2019-06-20, 2019-06-20-cpu, yade-daily-may-2019 |
yasm |
1.2.0-4 |
Z |
|
zetastitcher |
0.3.3 |
zlib |
1.2.11 |
zoem |
11-166 |
zoltan |
3.83 |
zstd |
1.4.0 |
Requesting an install¶
If you require additional software please email help@massive.org.au with the following details:
software
version
URL for download
urgency
if there are any licensing restrictions we need to impose
Docker based work flows¶
Many fields are beginning to distribute fully self contained pieces of software in a container format known as docker. Unfortunately docker is unsuited as a container format for shared user systems, however it is relatively easy to convert most docker containers for scientific work flows to the Singularity format. If you wish to run software based on a Docker container, please email help@massive.org.au and let us know where we can obtain the container and we will be happy to convert it for you.
Running QIIME on M3¶
QIIME (Quantitative Insights Into Microbial Ecology) 2 is installed on M3. To use this software:
# Loading module
module load qiime2/2017.9
# Unloading module
module unload qiime2/2017.9
If you encounter issues with this install, please contact help@massive.org.au
Running Python on M3¶
M3 has different versions of Python installed. To list them use the command:
# Listing python modules
module avail python
--------------------------------------------------- /usr/local/Modules/modulefiles ---------------------------------------------------
python/2.7.11-gcc python/2.7.15-gcc5 python/3.5.2-gcc5 python/3.6.6-gcc5
python/2.7.12-gcc4(default) python/3.5.2-gcc python/3.6.2 python/3.7.2-gcc6
python/2.7.12-gcc5 python/3.5.2-gcc4 python/3.6.2-static python/3.7.3-system
The listed Python versions have a standard set of python modules installed using Pip. As a user, unfortunately, you are unable to update or install your own python modules into the supplied Python software on Massive.
There is an alternative, to create a Python virtual environment (venv). A Python virtual environment effectively creates your own copy of Python, allowing you to install any Python modules you require. The instructions below focus on creating a Python virtual environment using 3.6.2.
‘destinationPath’ is the location you use to install Python on Massive.
#Setup python virtualenv - need to use this path to avoid 'module load'
/usr/local/python/3.6.2-static/bin/python3 -m venv destinationPath
#Activate the virtual environment - do this for each shell session
source destinationPath/bin/activate
#Upgrade pip
pip install --upgrade pip
Note
For each new shell session created, ‘source destinationPath/bin/activate’ is required to use your Python virtual environment.
To better understand Python virtual environments please refer to https://docs.python.org/3/tutorial/venv.html
Using PyCharm with your Virtual environment¶
After successfully creating your own virtual environment, you can use it in your PyCharm projects.
The first step is to start PyCharm. Start a Massive desktop session and select PyCharm from the menu. Please refer to Connecting to M3 via the MASSIVE desktop
Once PyCharm is up and running, select File, New Project.
2. You will be presented with the Create Project window. Click on the arrow next to ‘Project Interpreter’
Select ‘Existing interpreter’ and click the ‘browse’ icon.
4. Browse to the location where you created your virtual environment, enter the ‘bin’ folder, then select the ‘python’ executable. Click OK.
Click OK.
6. Back on the Create Project window, enter the new project name. Click OK. You now have a PyCharm project setup using your new virtual environment.
Running Anaconda on M3¶
M3 has different versions of Anaconda installed. To list them use the
command module avail anaconda:
module avail anaconda
----------------------------------------------- /usr/local/Modules/modulefiles ------------------------------------------------
anaconda/2018.12-Python3.7-gcc6 anaconda/4.3.1-Python3.5-gcc5 anaconda/5.0.1-Python3.6-gcc5
anaconda/2019.03-Python3.7-gcc5 anaconda/5.0.1-Python2.7-gcc5 anaconda/5.1.0-Python3.6-gcc5
anaconda/4.3.1-Python3.5 anaconda/5.0.1-Python3.5-gcc5
The listed Anaconda versions have a standard set of modules installed. As a user, unfortunately, you are unable to update or install your own modules into the supplied Anaconda software on Massive.
There is an alternative, to create a Conda environment. A Conda
environment effectively creates your own copy of Conda, allowing you to
install any Conda/Python modules you require. The instructions below focus on
creating an Ananconda environment using the module anaconda/2019.03-Python3.7-gcc5.
myEnv represents the environment name to use.
#Load the anaconda module
module load anaconda/2019.03-Python3.7-gcc5
#Change this to your project ID
export PROJECT=myID
export CONDA_ENVS=/projects/$PROJECT/$USER/conda_envs
#Create the conda environment - cloning the already installed packages
#change myEnv to your environment name
conda create --yes -p $CONDA_ENVS/myEnv --clone base
#OR create the conda environment with no packages installed
#change myEnv to your environment name
conda create --yes -p $CONDA_ENVS/myEnv
Conda will then create the environment and the end of the message may look like this:
Executing transaction: done
#
# To activate this environment, use:
# > conda activate myEnv
#
# To deactivate an active environment, use:
# > conda deactivate
#
On Massive, if you run conda activate for the first time, the following will be displayed:
CommandNotFoundError: Your shell has not been properly configured to use 'conda activate'.
To initialize your shell, run
$ conda init <SHELL_NAME>
Currently supported shells are:
- bash
- fish
- tcsh
- xonsh
- zsh
- powershell
See 'conda init --help' for more information and options.
IMPORTANT: You may need to close and restart your shell after running 'conda init'.
Note
On Massive DO NOT run conda init. Running this command will update your .bashrc file. The update prevents your Desktop session from starting.
Activating your Conda environment on Massive¶
Assuming you are in a new shell with no modules loaded.
#Load the anaconda module
module load anaconda/2019.03-Python3.7-gcc5
#Change this to your project ID
export PROJECT=myID
export CONDA_ENVS=/projects/$PROJECT/$USER/conda_envs
# To use the environment
source activate $CONDA_ENVS/myEnv
# Leave the enviroment
source deactivate
Installing and updating Python packages in your Conda environment¶
Check that your conda environment has been properly activated.
conda env list
# conda environments:
#
* /projects/PROJECT_ID/USER_ID/myEnv
base /usr/local/anaconda/2019.03-Python3.7-gcc5
illumina-utils-2.6 /usr/local/anaconda/2019.03-Python3.7-gcc5/envs/illumina-utils-2.6
pytorch-1.0-cuda10 /usr/local/anaconda/2019.03-Python3.7-gcc5/envs/pytorch-1.0-cuda10
pytorch-1.0-cuda9 /usr/local/anaconda/2019.03-Python3.7-gcc5/envs/pytorch-1.0-cuda9
The ‘*’ indicates the active environment. Ensure the correct one is indicated. If not, refer above to correctly activate your environment.
Use the following sample commands to install or update packages.
conda install packageName
conda install pagageName=versionNumber
conda update packageName
conda update packageName=versionNumber
I ran conda init and my Desktop session no longer starts¶
To fix follow these instructions.
ssh into Massive.
Edit your
.bashrcfile using your favourite editor.
3. Comment out the ‘conda’ lines using a # at the start of the lines. Below is a
sample .bashrc with the comments
# .bashrc
# Source global definitions
if [ -f /etc/bashrc ]; then
. /etc/bashrc
fi
# User specific aliases and functions
# Give bash history a decent size
export HISTFILESIZE=10000
# Helpful alias for users to quickly see their queue status
alias squ='squeue -u $USER'
# >>> conda initialize >>>
# !! Contents within this block are managed by 'conda init' !!
#__conda_setup="$('/usr/local/anaconda/2019.03-Python3.7-gcc5/bin/conda' 'shell.bash' 'hook' 2> /dev/null)"
#if [ $? -eq 0 ]; then
# eval "$__conda_setup"
#else
# if [ -f "/usr/local/anaconda/2019.03-Python3.7-gcc5/etc/profile.d/conda.sh" ]; then
# . "/usr/local/anaconda/2019.03-Python3.7-gcc5/etc/profile.d/conda.sh"
# else
# export PATH="/usr/local/anaconda/2019.03-Python3.7-gcc5/bin:$PATH"
# fi
#fi
#unset __conda_setup
# <<< conda initialize <<<
Save the file and exit your ssh session.
Restart your Desktop session.
Note
If you are not comfortable updating your .bashrc file, please
see Help and Support to obtain assistance.