A search for solutions: 2019

Tuesday, September 17, 2019

locate: can not open `/var/lib/mlocate/mlocate.db': Permission denied - resolved

Recently, had this issue with CentOS.

locate: can not open `/var/lib/mlocate/mlocate.db': Permission denied

Had overcome this issue by updating with mlocate

$ sudo yum resintall mlocate

The problem has got solved!!

Friday, August 16, 2019

Installing BEAST2 and Beagle-lib from scratch

git clone --depth=1 https://github.com/beagle-dev/beagle-lib.git
cd beagle-lib
./autogen.sh
./configure --prefix=/home/user/Software/beast/beagle-lib
make install

export LD_LIBRARY_PATH=/home/user/Software/beast/beagle-lib/lib:$LD_LIBRARY_PATH
make check

beast/beagle-lib/examples/tinytest$ ./tinytest
Available resources:
Resource 0:
Name : CPU
Desc :
Flags: PROCESSOR_CPU PRECISION_DOUBLE PRECISION_SINGLE COMPUTATION_SYNCH EIGEN_REAL EIGEN_COMPLEX SCALING_MANUAL SCALING_AUTO SCALING_ALWAYS SCALING_DYNAMIC SCALERS_RAW SCALERS_LOG VECTOR_NONE VECTOR_SSE THREADING_NONE FRAMEWORK_CPU

Using resource 0:
Rsrc Name : CPU
Impl Name : CPU-4State-Single
Impl Desc : none
Flags: PROCESSOR_CPU PRECISION_SINGLE COMPUTATION_SYNCH EIGEN_REAL SCALING_MANUAL SCALERS_RAW VECTOR_NONE THREADING_NONE FRAMEWORK_CPU

logL = -1498.89802 (PAUP logL = -1498.89812)
sumLogL = -1498.89802

$ ./beast -beagle_info

BEAST v2.6.0, 2002-2019

Bayesian Evolutionary Analysis Sampling Trees

Designed and developed by

Remco Bouckaert, Alexei J. Drummond, Andrew Rambaut & Marc A. Suchard

Centre for Computational Evolution

University of Auckland

r.bouckaert@auckland.ac.nz

alexei@cs.auckland.ac.nz

Institute of Evolutionary Biology

University of Edinburgh

a.rambaut@ed.ac.uk

David Geffen School of Medicine

University of California, Los Angeles

msuchard@ucla.edu

Downloads, Help & Resources:

http://beast2.org/

Source code distributed under the GNU Lesser General Public License:

http://github.com/CompEvol/beast2

BEAST developers:

Alex Alekseyenko, Trevor Bedford, Erik Bloomquist, Joseph Heled,

Sebastian Hoehna, Denise Kuehnert, Philippe Lemey, Wai Lok Sibon Li,

Gerton Lunter, Sidney Markowitz, Vladimir Minin, Michael Defoin Platel,

Oliver Pybus, Tim Vaughan, Chieh-Hsi Wu, Walter Xie

Thanks to:

Roald Forsberg, Beth Shapiro and Korbinian Strimmer

--- BEAGLE RESOURCES ---

0 : CPU

Flags: PRECISION_SINGLE PRECISION_DOUBLE COMPUTATION_SYNCH EIGEN_REAL EIGEN_COMPLEX SCALING_MANUAL SCALING_AUTO SCALING_ALWAYS SCALERS_RAW SCALERS_LOG VECTOR_SSE VECTOR_NONE THREADING_NONE PROCESSOR_CPU FRAMEWORK_CPU

we have beagle can run with CPU. But cuda is not activated yet!

I have installed cuda driver based on the my Ubuntu desktop version.

Check the Ubuntu version using the following command:

$ uname -a

16.04.2-Ubuntu

So, accordingly installed the cuda toolkit from the following link:

https://developer.nvidia.com/cuda-downloads

The tutorial is slightly old, I had to go to /usr/local/cuda-10.1/samples

Sometime, while installing, there can be error like this:

$ make
Making all in libhmsbeagle
make[1]: Entering directory '/home/user/Software/beast/beagle-lib/libhmsbeagle'
make all-recursive
make[2]: Entering directory '/home/user/Software/beast/beagle-lib/libhmsbeagle'
Making all in GPU
make[3]: Entering directory '/home/user/Software/beast/beagle-lib/libhmsbeagle/GPU'
Making all in kernels
make[4]: Entering directory '/home/user/Software/beast/beagle-lib/libhmsbeagle/GPU/kernels'
echo "// auto-generated header file with CUDA kernels PTX code" > BeagleCUDA_kernels.h
/usr/bin/nvcc -o BeagleCUDA_kernels.ptx -ptx -DCUDA -DSTATE_COUNT=4 \
./kernels4.cu -O3 -arch compute_30 -Wno-deprecated-gpu-targets -DHAVE_CONFIG_H -I/home/user/Software/beast/beagle-lib -I/home/user/Software/beast/beagle-lib || { \rm BeagleCUDA_kernels.h; exit; }; \
echo "#define KERNELS_STRING_SP_4 \"" | sed 's/$/\\n\\/' >> BeagleCUDA_kernels.h; \
cat BeagleCUDA_kernels.ptx | sed 's/\"/\\"/g' | sed 's/$/\\n\\/' >> BeagleCUDA_kernels.h; \
echo "\"" >> BeagleCUDA_kernels.h
nvcc fatal : Path to libdevice library not specified
for s in 16 32 48 64 80 128 192; do \
echo "Making state count = $s" ; \
/usr/bin/nvcc -o BeagleCUDA_kernels.ptx -ptx -DCUDA -DSTATE_COUNT=$s \
./kernelsX.cu -O3 -arch compute_30 -Wno-deprecated-gpu-targets -DHAVE_CONFIG_H -I/home/user/Software/beast/beagle-lib -I/home/user/Software/beast/beagle-lib || { \rm BeagleCUDA_kernels.h; exit; }; \
echo "#define KERNELS_STRING_SP_$s \"" | sed 's/$/\\n\\/' >> BeagleCUDA_kernels.h; \
cat BeagleCUDA_kernels.ptx | sed 's/\"/\\"/g' | sed 's/$/\\n\\/' >> BeagleCUDA_kernels.h; \
echo "\"" >> BeagleCUDA_kernels.h; \
done
Making state count = 16
nvcc fatal : Path to libdevice library not specified
rm: cannot remove 'BeagleCUDA_kernels.h': No such file or directory
Makefile:518: recipe for target 'BeagleCUDA_kernels.h' failed
make[4]: *** [BeagleCUDA_kernels.h] Error 1
make[4]: Leaving directory '/home/user/Software/beast/beagle-lib/libhmsbeagle/GPU/kernels'
Makefile:700: recipe for target 'all-recursive' failed
make[3]: *** [all-recursive] Error 1
make[3]: Leaving directory '/home/user/Software/beast/beagle-lib/libhmsbeagle/GPU'
Makefile:622: recipe for target 'all-recursive' failed
make[2]: *** [all-recursive] Error 1
make[2]: Leaving directory '/home/user/Software/beast/beagle-lib/libhmsbeagle'
Makefile:465: recipe for target 'all' failed
make[1]: *** [all] Error 2
make[1]: Leaving directory '/home/user/Software/beast/beagle-lib/libhmsbeagle'
Makefile:611: recipe for target 'all-recursive' failed

make: *** [all-recursive] Error 1

Paste the location of cuda bin directory in bashrc (/usr/local/cuda-10.1/bin/)

export PATH="/usr/local/cuda-10.1/bin:$PATH"

$ ./beast -beagle_info

BEAST v2.6.0, 2002-2019
Bayesian Evolutionary Analysis Sampling Trees
Designed and developed by
Remco Bouckaert, Alexei J. Drummond, Andrew Rambaut & Marc A. Suchard

Centre for Computational Evolution
University of Auckland
r.bouckaert@auckland.ac.nz
alexei@cs.auckland.ac.nz

Institute of Evolutionary Biology
University of Edinburgh
a.rambaut@ed.ac.uk

David Geffen School of Medicine
University of California, Los Angeles
msuchard@ucla.edu

Downloads, Help & Resources:
http://beast2.org/

Source code distributed under the GNU Lesser General Public License:
http://github.com/CompEvol/beast2

BEAST developers:
Alex Alekseyenko, Trevor Bedford, Erik Bloomquist, Joseph Heled,
Sebastian Hoehna, Denise Kuehnert, Philippe Lemey, Wai Lok Sibon Li,
Gerton Lunter, Sidney Markowitz, Vladimir Minin, Michael Defoin Platel,
Oliver Pybus, Tim Vaughan, Chieh-Hsi Wu, Walter Xie

Thanks to:
Roald Forsberg, Beth Shapiro and Korbinian Strimmer

--- BEAGLE RESOURCES ---

0 : CPU
Flags: PRECISION_SINGLE PRECISION_DOUBLE COMPUTATION_SYNCH EIGEN_REAL EIGEN_COMPLEX SCALING_MANUAL SCALING_AUTO SCALING_ALWAYS SCALERS_RAW SCALERS_LOG VECTOR_SSE VECTOR_NONE THREADING_NONE PROCESSOR_CPU FRAMEWORK_CPU

1 : Quadro P2000
Global memory (MB): 5058
Clock speed (Ghz): 1.48
Number of cores: 1024

Flags: PRECISION_SINGLE PRECISION_DOUBLE COMPUTATION_SYNCH COMPUTATION_ASYNCH EIGEN_REAL EIGEN_COMPLEX SCALING_MANUAL SCALING_AUTO SCALING_ALWAYS SCALERS_RAW SCALERS_LOG VECTOR_NONE THREADING_NONE PROCESSOR_GPU FRAMEWORK_CUDA

Voila! Beast with Beagle installed!!

Monday, July 8, 2019

GATK - Exception in thread "main" java.lang.IncompatibleClassChangeError

$ gatk VariantsToTable -V SNP.vcf -F CHROM -F POS -F QUAL -F DP4 -F MQ -O test

Using GATK jar /home/sw/gatk-4.1.1.0/gatk-package-4.1.1.0-local.jar
Running:
java -Dsamjdk.use_async_io_read_samtools=false -Dsamjdk.use_async_io_write_samtools=true -Dsamjdk.use_async_io_write_tribble=false -Dsamjdk.compression_level=2 -jar /home/prakki/sw/gatk-4.1.1.0/gatk-package-4.1.1.0-local.jar VariantsToTable -V 14DM017529_1032_HQ_SNP.vcf -F CHROM -F POS -F QUAL -F DP4 -F MQ -O test
Runtime.totalMemory()=2155872256
Exception in thread "main" java.lang.IncompatibleClassChangeError: Inconsistent constant pool data in classfile for class org/broadinstitute/hellbender/transformers/VariantTransformer. Method lambda$identity$76d6cab0$1(Lhtsjdk/variant/variantcontext/VariantContext;)Lhtsjdk/variant/variantcontext/VariantContext; at index 65 is CONSTANT_MethodRef and should be CONSTANT_InterfaceMethodRef
at org.broadinstitute.hellbender.transformers.VariantTransformer.identity(VariantTransformer.java:32)
at org.broadinstitute.hellbender.engine.VariantWalkerBase.makePreVariantFilterTransformer(VariantWalkerBase.java:131)
at org.broadinstitute.hellbender.engine.VariantWalkerBase.getTransformedVariantStream(VariantWalkerBase.java:155)
at org.broadinstitute.hellbender.engine.VariantWalker.traverse(VariantWalker.java:98)
at org.broadinstitute.hellbender.engine.GATKTool.doWork(GATKTool.java:984)
at org.broadinstitute.hellbender.cmdline.CommandLineProgram.runTool(CommandLineProgram.java:138)
at org.broadinstitute.hellbender.cmdline.CommandLineProgram.instanceMainPostParseArgs(CommandLineProgram.java:191)
at org.broadinstitute.hellbender.cmdline.CommandLineProgram.instanceMain(CommandLineProgram.java:210)
at org.broadinstitute.hellbender.Main.runCommandLineProgram(Main.java:162)
at org.broadinstitute.hellbender.Main.mainEntry(Main.java:205)
at org.broadinstitute.hellbender.Main.main(Main.java:291)

Check for alternative versions

$ sudo update-alternatives --config java
[sudo] password for prakki:
There are 2 choices for the alternative java (providing /usr/bin/java).

Selection Path Priority Status
------------------------------------------------------------
* 0 /usr/lib/jvm/java-11-openjdk-amd64/bin/java 1101 auto mode
1 /usr/lib/jvm/java-11-openjdk-amd64/bin/java 1101 manual mode
2 /usr/lib/jvm/java-8-openjdk-amd64/jre/bin/java 1081 manual mode

Press <enter> to keep the current choice[*], or type selection number: 2

Now, java version should have look something like this:

$ java -version

openjdk version "1.8.0_212"

.....

$ gatk VariantsToTable -V SNP.vcf -F CHROM -F POS -F QUAL -F DP4 -F MQ -O test

Thursday, June 13, 2019

BEAST phylogeny - BEAGLE installation

Running a computational process on GPU is much faster than CPU. Just wanted to test this BEAST phylogeny tool. It was an amazing experience. GPU is way much faster. Just to get a glimpse of the GPU speed on 95 sample data each sequence of 5 MB:

GPU is the winner!! But installation took time.

Here are the steps.

Follow the steps from :

https://github.com/beagle-dev/beagle-lib

If the beast -beagle info gives you only the message as below, then that means your cuda is not properly installed.

--- BEAGLE RESOURCES ---

0 : CPU

I use ubuntu. So, I followed this tut:
https://github.com/beagle-dev/beagle-lib/wiki/LinuxInstallInstructions

For my purpose, I have installed cuda toolkit from here:
https://developer.nvidia.com/cuda-downloads

$ sudo dpkg -i cuda-repo-ubuntu1804-10-1-local-10.1.168-418.67_1.0-1_amd64.deb

(Reading database ... 396141 files and directories currently installed.)

Preparing to unpack cuda-repo-ubuntu1804-10-1-local-10.1.168-418.67_1.0-1_amd64.deb ...

Unpacking cuda-repo-ubuntu1804-10-1-local-10.1.168-418.67 (1.0-1) over (1.0-1) ...

Setting up cuda-repo-ubuntu1804-10-1-local-10.1.168-418.67 (1.0-1) ...

once the cuda is installed, we need to check if it is properly installed. Follow the instructions to check if it is properly installed.

https://xcat-docs.readthedocs.io/en/stable/advanced/gpu/nvidia/verify_cuda_install.html

If deviceQuery, bandwidthTest commands give similar result, then cuda is successfully installed.

Else if you receive an error like when you run ./bin/x86_64/linux/release/deviceQuery

-> no CUDA-capable device is detected

That means either you need to switch the graphics cards or you need to select the appropriate driver. In my case, I had only one graphics card,

When I typed,

$ nvidia-smi -a
NVIDIA: API mismatch: the NVIDIA kernel module has version 295.59,
but this NVIDIA driver component has version 304.54. Please make
sure that the kernel module and all NVIDIA driver components
have the same version.

You can check in the page, what graphics card you have and how to switch over (not my case).
For my case, I needed to select the appropriate driver since there is a mismatch.

so, I ran this command:

$ sudo ubuntu-drivers devices

So, I was recommended to use nvidia-driver-430 for my case, where as I was using driver-418.

So, I selected to driver-430, Apply changes and restart the system

$ ./bin/x86_64/linux/release/deviceQuery
./bin/x86_64/linux/release/deviceQuery Starting...

CUDA Device Query (Runtime API) version (CUDART static linking)

Detected 1 CUDA Capable device(s)

Device 0: "Quadro P2000"
CUDA Driver Version / Runtime Version 10.1 / 10.1
CUDA Capability Major/Minor version number: 6.1
.....

Result = PASS

$ ./bin/x86_64/linux/release/bandwidthTest

[CUDA Bandwidth Test] - Starting...

Running on...

Device 0: Quadro P2000

Quick Mode

.......

Result = PASS

NOTE: The CUDA Samples are not meant for performance measurements. Results may vary when GPU Boost is enabled.

It now works!!!!

Test beast with beagle now, you should see both CPU as well as GPU card in the resources list.

--- BEAGLE RESOURCES ---

0 : CPU
Flags: PRECISION_SINGLE PRECISION_DOUBLE COMPUTATION_SYNCH EIGEN_REAL EIGEN_COMPLEX SCALING_MANUAL SCALING_AUTO SCALING_ALWAYS SCALERS_RAW SCALERS_LOG VECTOR_SSE VECTOR_NONE THREADING_NONE PROCESSOR_CPU FRAMEWORK_CPU

1 : Quadro P2000
Global memory (MB): 5058
Clock speed (Ghz): 1.48
Number of cores: 1024
Flags: PRECISION_SINGLE PRECISION_DOUBLE COMPUTATION_SYNCH COMPUTATION_ASYNCH EIGEN_REAL EIGEN_COMPLEX SCALING_MANUAL SCALING_AUTO SCALING_ALWAYS SCALERS_RAW SCALERS_LOG VECTOR_NONE THREADING_NONE PROCESSOR_GPU FRAMEWORK_CUDA

Thats it!

Thursday, April 25, 2019

Extract a specific gene contig from multiple assemblies

1) Copy and paste a gene (for example NDM-1) from a database in text file - NDM-1.fa

2) Create blast DB for NDM gene using following command

$ makeblastdb -in NDM-1.fa -dbtype nucl -out NDM-1.fa.DB -parse_seqids

3) BLAST the assemblies against the NDM gene

$ for d in $(ls */assembly.fasta); do \
sample=`echo $d | sed 's/\/assembly.fasta//g'`; \
echo "$sample"; sed -i "s/>/>"$sample"_/g" $d; \
sed -i 's/ /_/g' $d; \
~/sw/ncbi-blast-2.7.1+/bin/blastn -db NDM-1.fa.DB -query $d -outfmt '6 qseqid sseqid pident nident length mismatch gapopen qstart qend sstart send evalue bitscore qlen slen' -num_threads 4 -out "$sample"_vs_NDM_blastresults.txt; done

This would rename all the contigs in the assembly.fasta with the directory name which holds assembly.fasta

4) cat *.txt | column -t

THY1079 NDM-1_JQ080305_1-813_813 100 813 813 0 0 48157 48969 813 1 0 1502 91643 813
THY1219 NDM-1_JQ080305_1-813_813 100 813 813 0 0 4586 5398 813 1 0 1502 13505 813
THY1250 NDM-1_JQ080305_1-813_813 99.754 811 813 2 0 14408 15220 1 813 0 1491 88353 813
THY1357 NDM-1_JQ080305_1-813_813 100 813 813 0 0 78370 79182 813 1 0 1502 177751 813
THY1440 NDM-1_JQ080305_1-813_813 99.754 811 813 2 0 14408 15220 1 813 0 1491 96544 813
THY1669 NDM-1_JQ080305_1-813_813 100 813 813 0 0 6747 7559 813 1 0 1502 118064 813
THY1758 NDM-1_JQ080305_1-813_813 99.754 811 813 2 0 5708 6520 1 813 0 1491 62334 813
THY1916 NDM-1_JQ080305_1-813_813 100 813 813 0 0 19307 20119 813 1 0 1502 278408 813
THY1940 NDM-1_JQ080305_1-813_813 100 813 813 0 0 3171762 3172574 1 813 0 1502 4879405 813
THY1968 NDM-1_JQ080305_1-813_813 100 813 813 0 0 3173593 3174405 1 813 0 1502 4880726 813
THY285 NDM-1_JQ080305_1-813_813 99.754 811 813 2 0 25547 26359 1 813 0 1491 46161 813
THY337 NDM-1_JQ080305_1-813_813 100 813 813 0 0 57706 58518 1 813 0 1502 88057 813
THY708 NDM-1_JQ080305_1-813_813 100 813 813 0 0 302 1114 1 813 0 1502 14280 813
THY807 NDM-1_JQ080305_1-813_813 99.754 811 813 2 0 2469 3281 1 813 0 1491 5469 813
THY924 NDM-1_JQ080305_1-813_813 99.754 811 813 2 0 36917 37729 1 813 0 1491 75214 813
THY924 NDM-1_JQ080305_1-813_813 99.754 811 813 2 0 20047 20859 813 1 0 1491 70472 813

5) extract the NDM_gene from the assemblies

fgrep -A1 -f <(cat *.txt | cut -f1) <(cat */assembly.fasta | awk '/^>/ {printf("\n%s\n",$0);next; } { printf("%s",$0);} END {printf("\n");}') >NDM_positive_contigs.fasta

<(cat *.txt | cut -f1) -process substitution operator - gives the list of contig names

cat */assembly.fasta | awk '/^>/ {printf("\n%s\n",$0);next; } { printf("%s",$0);} END {printf("\n");}' - this woud convert all the multiline fasta to single line fasta

-A1 get the single line after the match

Friday, April 5, 2019

Search for a protein in specific genome database

1) Go to NCBI Blast page and select tblastn

2) Select the protein you want to check, for example, I want to check the following protein is present in the database. Select the protein accession and copy it in the query box.

3) Now search for the protein sequence in Database: Whole-genome shotgun contigs (I selected this because Asian Seabass does not have RefSeq Genome) and organism by typing: Asian Seabass

4) Blast! If you find the protein sequences in the genome, it will appears in the results.

Note: It will take time, if you are using proteins to search because BLAST has to translate all the 6 frames and search against the database. For faster check of the presence of the sequences in the database, it is better to do a local NCBI blast.

Wednesday, April 3, 2019

locate: can not open `/var/lib/mlocate/mlocate.db': Permission denied - Solved!

$ locate unicycler
locate: can not open `/var/lib/mlocate/mlocate.db': Permission denied

Changing the permission solved the issue!

$ sudo chmod -R 755 /var/lib/mlocate/mlocate.db

$ locate unicycler
/home/user/Lab_Doc_Share/Assembly/SA3_Noclean_barcode01_unicycler.log

Monday, April 1, 2019

Installing nanopack

$ pip install nanopack

Collecting nanopack

Collecting nanoplotter>=0.16.5 (from nanopack)

Collecting NanoPlot>=0.20.1 (from nanopack)

Collecting NanoLyse>=0.2.1 (from nanopack)

Collecting NanoFilt>=1.5.2 (from nanopack)

Collecting nanomath>=0.13.3 (from nanopack)

Collecting nanoget>=0.15.0 (from nanopack)

Collecting NanoStat>=0.6.1 (from nanopack)

Collecting numpy (from nanoplotter>=0.16.5->nanopack)

Using cached https://files.pythonhosted.org/packages/e0/b5/63b79fe426433fa1cd110eb04a94ec0c6967e56e5f57c98caf455a5fb6e2/numpy-1.16.1-cp27-cp27mu-manylinux1_x86_64.whl

Collecting seaborn (from nanoplotter>=0.16.5->nanopack)

Collecting pauvre (from nanoplotter>=0.16.5->nanopack)

Collecting pandas (from nanoplotter>=0.16.5->nanopack)

Using cached https://files.pythonhosted.org/packages/c5/88/b8659eecde0350d37d5b47c1c2a88f39e6153e5809bcfc48bb7fde6f231b/pandas-0.24.1-cp27-cp27mu-manylinux1_x86_64.whl

Collecting matplotlib>=2.0.0 (from nanoplotter>=0.16.5->nanopack)

Using cached https://files.pythonhosted.org/packages/59/08/04933377dc4500e3698e93f9113dc3624874e0914f4c85767ecb5b389084/matplotlib-2.2.3-cp27-cp27mu-manylinux1_x86_64.whl

Collecting scipy (from nanoplotter>=0.16.5->nanopack)

Using cached https://files.pythonhosted.org/packages/81/39/f1457091d0a45a84a2bd7815e2cf6bd45d4fe240728e9ed567cbb17c8abe/scipy-1.2.1-cp27-cp27mu-manylinux1_x86_64.whl

Collecting biopython (from NanoPlot>=0.20.1->nanopack)

Using cached https://files.pythonhosted.org/packages/19/4e/ac487da685e947c56fafd10b2a04c6a09f0051c2e7665a873263f5e303f2/biopython-1.73-cp27-cp27mu-manylinux1_x86_64.whl

Collecting pysam>0.10.0.0 (from NanoPlot>=0.20.1->nanopack)

Using cached https://files.pythonhosted.org/packages/0f/bd/f5ab828a9ff45a6ca14d5ea2a3580f720134052db258cd7ef929a4ed1d7a/pysam-0.15.2-cp27-cp27mu-manylinux1_x86_64.whl

Collecting python-dateutil (from NanoPlot>=0.20.1->nanopack)

Using cached https://files.pythonhosted.org/packages/41/17/c62faccbfbd163c7f57f3844689e3a78bae1f403648a6afb1d0866d87fbb/python_dateutil-2.8.0-py2.py3-none-any.whl

Collecting mappy>=2.2 (from NanoLyse>=0.2.1->nanopack)

Collecting pytz>=2011k (from pandas->nanoplotter>=0.16.5->nanopack)

Using cached https://files.pythonhosted.org/packages/61/28/1d3920e4d1d50b19bc5d24398a7cd85cc7b9a75a490570d5a30c57622d34/pytz-2018.9-py2.py3-none-any.whl

Collecting cycler>=0.10 (from matplotlib>=2.0.0->nanoplotter>=0.16.5->nanopack)

Using cached https://files.pythonhosted.org/packages/f7/d2/e07d3ebb2bd7af696440ce7e754c59dd546ffe1bbe732c8ab68b9c834e61/cycler-0.10.0-py2.py3-none-any.whl

Collecting backports.functools-lru-cache (from matplotlib>=2.0.0->nanoplotter>=0.16.5->nanopack)

Using cached https://files.pythonhosted.org/packages/03/8e/2424c0e65c4a066e28f539364deee49b6451f8fcd4f718fefa50cc3dcf48/backports.functools_lru_cache-1.5-py2.py3-none-any.whl

Collecting subprocess32 (from matplotlib>=2.0.0->nanoplotter>=0.16.5->nanopack)

Collecting kiwisolver>=1.0.1 (from matplotlib>=2.0.0->nanoplotter>=0.16.5->nanopack)

Using cached https://files.pythonhosted.org/packages/3a/62/a8c9bef3059d55ab38e41fe9cba4fad773bfc04e47290bab84db1c18262e/kiwisolver-1.0.1-cp27-cp27mu-manylinux1_x86_64.whl

Collecting six>=1.10 (from matplotlib>=2.0.0->nanoplotter>=0.16.5->nanopack)

Using cached https://files.pythonhosted.org/packages/73/fb/00a976f728d0d1fecfe898238ce23f502a721c0ac0ecfedb80e0d88c64e9/six-1.12.0-py2.py3-none-any.whl

Collecting pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 (from matplotlib>=2.0.0->nanoplotter>=0.16.5->nanopack)

Using cached https://files.pythonhosted.org/packages/de/0a/001be530836743d8be6c2d85069f46fecf84ac6c18c7f5fb8125ee11d854/pyparsing-2.3.1-py2.py3-none-any.whl

Collecting setuptools (from kiwisolver>=1.0.1->matplotlib>=2.0.0->nanoplotter>=0.16.5->nanopack)

Using cached https://files.pythonhosted.org/packages/d1/6a/4b2fcefd2ea0868810e92d519dacac1ddc64a2e53ba9e3422c3b62b378a6/setuptools-40.8.0-py2.py3-none-any.whl

Installing collected packages: numpy, pytz, six, python-dateutil, pandas, scipy, cycler, backports.functools-lru-cache, subprocess32, setuptools, kiwisolver, pyparsing, matplotlib, seaborn, biopython, pauvre, nanoplotter, pysam, nanomath, nanoget, NanoPlot, mappy, NanoLyse, NanoFilt, NanoStat, nanopack

Successfully installed NanoFilt-2.0.0 NanoLyse-0.5.0 NanoPlot-1.8.1 NanoStat-0.8.0 backports.functools-lru-cache-1.5 biopython-1.73 cycler-0.10.0 kiwisolver-1.0.1 mappy-2.15 matplotlib-2.2.3 nanoget-1.2.0 nanomath-0.15.1 nanopack-0.1.4 nanoplotter-0.28.0 numpy-1.16.1 pandas-0.24.1 pauvre-0.1.86 pyparsing-2.3.1 pysam-0.15.2 python-dateutil-2.8.0 pytz-2018.9 scipy-1.2.1 seaborn-0.9.0 setuptools-40.8.0 six-1.12.0 subprocess32-3.5.3

$ NanoPlot

NanoPlot: command not found

$ pip install nanopack

Collecting nanopack

Downloading https://files.pythonhosted.org/packages/3b/cc/52bdfaa3fb739d6fc26ac9ec55cd63d7db06d73bf0d7d096b37b7b2839bf/nanopack-0.1.4.tar.gz

Collecting NanoPlot>=0.20.1 (from nanopack)

Downloading https://files.pythonhosted.org/packages/d6/9e/992d05d1e8a72a3de6dd945a6c2fab64ddae0b95657b3263809a4c125ecb/NanoPlot-1.8.1.tar.gz

Collecting NanoStat>=0.6.1 (from nanopack)

Downloading https://files.pythonhosted.org/packages/5f/58/6555371d9c6fe42c67e64bcf1a4e2a25d237f086292f696a814c12149a68/NanoStat-0.8.0.tar.gz

Collecting NanoFilt>=1.5.2 (from nanopack)

Downloading https://files.pythonhosted.org/packages/b9/96/6e9025334a704d64140e8d7fc664c0a11e3e98ba16d109ea12dc6ca2d067/NanoFilt-2.0.0.tar.gz

Collecting NanoLyse>=0.2.1 (from nanopack)

Downloading https://files.pythonhosted.org/packages/37/ec/3ce7573f77a341040f77de0988594d2229522b8a52384f7a29aecf7082b2/NanoLyse-0.5.0.tar.gz

Collecting nanoget>=0.15.0 (from nanopack)

Downloading https://files.pythonhosted.org/packages/b0/a4/d925390225969242be5e1ff8e019372a3831b3cd71870164c4c95b243449/nanoget-1.2.0.tar.gz

Collecting nanomath>=0.13.3 (from nanopack)

Downloading https://files.pythonhosted.org/packages/6d/cd/b6ea00834b31c20de01fdaaea334e87bbba04ec47222f6f17d06a47b06d2/nanomath-0.15.1.tar.gz

Collecting nanoplotter>=0.16.5 (from nanopack)

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Collecting biopython (from NanoPlot>=0.20.1->nanopack)

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Collecting pysam>0.10.0.0 (from NanoPlot>=0.20.1->nanopack)

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Collecting pandas (from NanoPlot>=0.20.1->nanopack)

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Collecting numpy (from NanoPlot>=0.20.1->nanopack)

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Collecting scipy (from NanoPlot>=0.20.1->nanopack)

Downloading https://files.pythonhosted.org/packages/81/39/f1457091d0a45a84a2bd7815e2cf6bd45d4fe240728e9ed567cbb17c8abe/scipy-1.2.1-cp27-cp27mu-manylinux1_x86_64.whl (24.8MB)

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Collecting python-dateutil (from NanoPlot>=0.20.1->nanopack)

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Collecting seaborn (from NanoPlot>=0.20.1->nanopack)

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Collecting mappy>=2.2 (from NanoLyse>=0.2.1->nanopack)

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Collecting matplotlib>=2.0.0 (from nanoplotter>=0.16.5->nanopack)

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Collecting pauvre (from nanoplotter>=0.16.5->nanopack)

Downloading https://files.pythonhosted.org/packages/f0/70/b1a2c106128156d2f234964caee3f900733f81b67df51ffa62591e5bba46/pauvre-0.1.86.tar.gz (40kB)

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Collecting pytz>=2011k (from pandas->NanoPlot>=0.20.1->nanopack)

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Collecting six>=1.5 (from python-dateutil->NanoPlot>=0.20.1->nanopack)

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Collecting cycler>=0.10 (from matplotlib>=2.0.0->nanoplotter>=0.16.5->nanopack)

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Collecting subprocess32 (from matplotlib>=2.0.0->nanoplotter>=0.16.5->nanopack)

Downloading https://files.pythonhosted.org/packages/be/2b/beeba583e9877e64db10b52a96915afc0feabf7144dcbf2a0d0ea68bf73d/subprocess32-3.5.3.tar.gz (96kB)

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Collecting kiwisolver>=1.0.1 (from matplotlib>=2.0.0->nanoplotter>=0.16.5->nanopack)

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Collecting pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 (from matplotlib>=2.0.0->nanoplotter>=0.16.5->nanopack)

Downloading https://files.pythonhosted.org/packages/de/0a/001be530836743d8be6c2d85069f46fecf84ac6c18c7f5fb8125ee11d854/pyparsing-2.3.1-py2.py3-none-any.whl (61kB)

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Collecting setuptools (from kiwisolver>=1.0.1->matplotlib>=2.0.0->nanoplotter>=0.16.5->nanopack)

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Installing collected packages: numpy, biopython, pysam, pytz, six, python-dateutil, pandas, scipy, cycler, backports.functools-lru-cache, subprocess32, setuptools, kiwisolver, pyparsing, matplotlib, seaborn, pauvre, nanoplotter, nanomath, nanoget, NanoPlot, NanoStat, NanoFilt, mappy, NanoLyse, nanopack

Running setup.py install for subprocess32 ... done

Running setup.py install for seaborn ... done

Running setup.py install for pauvre ... done

Running setup.py install for nanoplotter ... done

Running setup.py install for nanomath ... done

Running setup.py install for nanoget ... done

Running setup.py install for NanoPlot ... done

Running setup.py install for NanoStat ... done

Running setup.py install for NanoFilt ... done

Running setup.py install for mappy ... done

Running setup.py install for NanoLyse ... done

Running setup.py install for nanopack ... done

Successfully installed NanoFilt-2.0.0 NanoLyse-0.5.0 NanoPlot-1.8.1 NanoStat-0.8.0 backports.functools-lru-cache-1.5 biopython-1.73 cycler-0.10.0 kiwisolver-1.0.1 mappy-2.15 matplotlib-2.2.3 nanoget-1.2.0 nanomath-0.15.1 nanopack-0.1.4 nanoplotter-0.28.0 numpy-1.16.1 pandas-0.24.1 pauvre-0.1.86 pyparsing-2.3.1 pysam-0.15.2 python-dateutil-2.8.0 pytz-2018.9 scipy-1.2.1 seaborn-0.9.0 setuptools-40.8.0 six-1.12.0 subprocess32-3.5.3

$ pip list | grep NanoPlot

NanoPlot (1.8.1)

$ sudo pip install nanopack

[sudo] password for user:

The directory '/home/user/.cache/pip/http' or its parent directory is not owned by the current user and the cache has been disabled. Please check the permissions and owner of that directory. If executing pip with sudo, you may want sudo's -H flag.

The directory '/home/user/.cache/pip' or its parent directory is not owned by the current user and caching wheels has been disabled. check the permissions and owner of that directory. If executing pip with sudo, you may want sudo's -H flag.

Requirement already satisfied: nanopack in /home/user/.local/lib/python2.7/site-packages

Requirement already satisfied: NanoPlot>=0.20.1 in /home/user/.local/lib/python2.7/site-packages (from nanopack)

Requirement already satisfied: NanoStat>=0.6.1 in /home/user/.local/lib/python2.7/site-packages (from nanopack)

Requirement already satisfied: NanoFilt>=1.5.2 in /home/user/.local/lib/python2.7/site-packages (from nanopack)

Requirement already satisfied: NanoLyse>=0.2.1 in /home/user/.local/lib/python2.7/site-packages (from nanopack)

Added the path in bashrc

Still no luck!

Tried this:

$ pip3 install nanopack

Collecting nanopack

Downloading https://files.pythonhosted.org/packages/54/24/f5b5a96a6a32d1127eb547745ab9572286035058f60a2988bdd2b1673bd7/nanopack-1.0.0.tar.gz

Collecting NanoComp>=0.4.0 (from nanopack)

Downloading https://files.pythonhosted.org/packages/75/4f/9e8f5c304d1644ab0892e35de294188d99aa8eb3df351d19c199b51f3ae6/NanoComp-1.4.0.tar.gz

Collecting NanoFilt>=1.5.2 (from nanopack)

Downloading https://files.pythonhosted.org/packages/dc/4a/dacdbbd28973d2d56ad0c0f3bf578f2bdfb68c9d27d7828034ea05cc90bc/NanoFilt-2.2.0.tar.gz

Collecting NanoGUI (from nanopack)

Downloading https://files.pythonhosted.org/packages/bd/a1/6cf74f2086e4e7215c740c28671337f01d126e9d2f4ec6ebacc47fd792de/NanoGUI-0.1.0.tar.gz

Collecting NanoLyse>=0.2.1 (from nanopack)

Downloading https://files.pythonhosted.org/packages/e9/52/812e19f50576871e82c0f5e8f188f4a7de99199fe1ceb50c33ac353de408/NanoLyse-1.1.0.tar.gz

Collecting NanoPlot>=0.20.1 (from nanopack)

Downloading https://files.pythonhosted.org/packages/f2/79/849cda1c7a6a124ccbf9e81d4c2e61ec6d780a841f4b6bb04aa942b47fcc/NanoPlot-1.21.0.tar.gz

Collecting NanoStat>=0.6.1 (from nanopack)

Downloading https://files.pythonhosted.org/packages/9c/8e/3fd581ebe737d1bf6716e5e8731f6677a84ab71bb0291b0cf8f1a9c6b656/NanoStat-1.1.2.tar.gz

Collecting nanoget>=0.15.0 (from nanopack)

Downloading https://files.pythonhosted.org/packages/2e/97/f439c3cdb85d99288091b1224460d6b6245ceaa962286744e89006b95aa8/nanoget-1.7.7.tar.gz

Collecting nanomath>=0.13.3 (from nanopack)

Downloading https://files.pythonhosted.org/packages/19/0b/2cdf6f70b6b7e581b7149b60f9117841326186d44aa62f60ed18280f7515/nanomath-0.22.0.tar.gz

Collecting nanoplotter>=0.16.5 (from nanopack)

Downloading https://files.pythonhosted.org/packages/0c/85/86e0323e7448c3c96b7cb17cd41c1e99c80336380cdb77b48debbb82772b/nanoplotter-1.3.1.tar.gz

Collecting numpy (from NanoComp>=0.4.0->nanopack)

Downloading https://files.pythonhosted.org/packages/f5/bf/4981bcbee43934f0adb8f764a1e70ab0ee5a448f6505bd04a87a2fda2a8b/numpy-1.16.1-cp36-cp36m-manylinux1_x86_64.whl (17.3MB)

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Collecting pandas (from NanoComp>=0.4.0->nanopack)

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Collecting psutil (from NanoComp>=0.4.0->nanopack)

Downloading https://files.pythonhosted.org/packages/c7/01/7c30b247cdc5ba29623faa5c8cf1f1bbf7e041783c340414b0ed7e067c64/psutil-5.5.1.tar.gz (426kB)

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Collecting biopython (from NanoFilt>=1.5.2->nanopack)

Downloading https://files.pythonhosted.org/packages/28/15/8ac646ff24cfa2588b4d5e5ea51e8d13f3d35806bd9498fbf40ef79026fd/biopython-1.73-cp36-cp36m-manylinux1_x86_64.whl (2.2MB)

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Collecting mappy>=2.2 (from NanoLyse>=0.2.1->nanopack)

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Collecting pysam>0.10.0.0 (from NanoPlot>=0.20.1->nanopack)

Downloading https://files.pythonhosted.org/packages/f1/fc/d2be1a093bd8494ab63e3168aca36c2494753bbff190f3201ce2e7da9cda/pysam-0.15.2-cp36-cp36m-manylinux1_x86_64.whl (9.6MB)

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Collecting python-dateutil (from NanoPlot>=0.20.1->nanopack)

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Collecting scipy (from NanoPlot>=0.20.1->nanopack)

Downloading https://files.pythonhosted.org/packages/7f/5f/c48860704092933bf1c4c1574a8de1ffd16bf4fde8bab190d747598844b2/scipy-1.2.1-cp36-cp36m-manylinux1_x86_64.whl (24.8MB)

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Collecting seaborn (from NanoPlot>=0.20.1->nanopack)

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Collecting matplotlib>=2.1.0 (from nanoplotter>=0.16.5->nanopack)

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Collecting pauvre==0.1.86 (from nanoplotter>=0.16.5->nanopack)

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Collecting plotly>=3.4.2 (from nanoplotter>=0.16.5->nanopack)

Downloading https://files.pythonhosted.org/packages/fd/db/003b5cfbc710f4d4982440451185b952269e4080a57ae7e760a2ceb8ce0c/plotly-3.6.1-py2.py3-none-any.whl (38.6MB)

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Collecting statsmodels>=0.8.0 (from nanoplotter>=0.16.5->nanopack)

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Collecting pytz>=2011k (from pandas->NanoComp>=0.4.0->nanopack)

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Collecting six>=1.5 (from python-dateutil->NanoPlot>=0.20.1->nanopack)

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Collecting pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 (from matplotlib>=2.1.0->nanoplotter>=0.16.5->nanopack)

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Collecting kiwisolver>=1.0.1 (from matplotlib>=2.1.0->nanoplotter>=0.16.5->nanopack)

Downloading https://files.pythonhosted.org/packages/69/a7/88719d132b18300b4369fbffa741841cfd36d1e637e1990f27929945b538/kiwisolver-1.0.1-cp36-cp36m-manylinux1_x86_64.whl (949kB)

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Collecting cycler>=0.10 (from matplotlib>=2.1.0->nanoplotter>=0.16.5->nanopack)

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Collecting decorator>=4.0.6 (from plotly>=3.4.2->nanoplotter>=0.16.5->nanopack)

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Building wheels for collected packages: nanopack, NanoComp, NanoFilt, NanoGUI, NanoLyse, NanoPlot, NanoStat, nanoget, nanomath, nanoplotter, psutil, mappy, pauvre, retrying, pyrsistent

Running setup.py bdist_wheel for nanopack ... done

Stored in directory: /home/user/.cache/pip/wheels/03/38/47/12ff3f64dcef32f2a9fcd92e57c3fdf8fb8953db45e083a806

Running setup.py bdist_wheel for NanoComp ... done

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Running setup.py bdist_wheel for NanoFilt ... done

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Running setup.py bdist_wheel for NanoGUI ... done

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Running setup.py bdist_wheel for NanoLyse ... done

Stored in directory: /home/user/.cache/pip/wheels/68/6d/64/27b22d72fac5d81ed03f70d98c141ce056fdada3d1860132cb

Running setup.py bdist_wheel for NanoPlot ... done

Stored in directory: /home/user/.cache/pip/wheels/1b/5b/3e/6c83f4fed51f3960855fad667a1010be1086edcc023207a679

Running setup.py bdist_wheel for NanoStat ... done

Stored in directory: /home/user/.cache/pip/wheels/ad/ab/b1/55c9bf3e44f4229d21815a72c729bfa0ddfb502a32a060a9f7

Running setup.py bdist_wheel for nanoget ... done

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Running setup.py bdist_wheel for nanomath ... done

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Running setup.py bdist_wheel for nanoplotter ... done

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Running setup.py bdist_wheel for psutil ... done

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Running setup.py bdist_wheel for mappy ... done

Stored in directory: /home/user/.cache/pip/wheels/16/61/f2/3ab933f528809270525fdf5b4f85d633b9212082a1d120fbd2

Running setup.py bdist_wheel for pauvre ... done

Stored in directory: /home/user/.cache/pip/wheels/6e/2b/00/0e4d27ead78a742a19bc4705a54bdcaae9cc456974b234bfad

Running setup.py bdist_wheel for retrying ... done

Stored in directory: /home/user/.cache/pip/wheels/d7/a9/33/acc7b709e2a35caa7d4cae442f6fe6fbf2c43f80823d46460c

Running setup.py bdist_wheel for pyrsistent ... done

Stored in directory: /home/user/.cache/pip/wheels/83/59/9a/a037b9b3c3e93d9275ea0aff9d6064400f372879dfdab01afe

Successfully built nanopack NanoComp NanoFilt NanoGUI NanoLyse NanoPlot NanoStat nanoget nanomath nanoplotter psutil mappy pauvre retrying pyrsistent

Installing collected packages: numpy, biopython, pytz, six, python-dateutil, pandas, nanomath, pysam, nanoget, pyparsing, setuptools, kiwisolver, cycler, matplotlib, scipy, pauvre, decorator, retrying, chardet, idna, certifi, urllib3, requests, ipython-genutils, pyrsistent, attrs, jsonschema, traitlets, jupyter-core, nbformat, plotly, seaborn, patsy, statsmodels, nanoplotter, NanoPlot, psutil, NanoComp, NanoFilt, NanoGUI, mappy, NanoLyse, NanoStat, nanopack

Successfully installed NanoComp-1.4.0 NanoFilt-2.2.0 NanoGUI-0.1.0 NanoLyse-1.1.0 NanoPlot-1.21.0 NanoStat-1.1.2 attrs-18.2.0 biopython-1.73 certifi-2018.11.29 chardet-3.0.4 cycler-0.10.0 decorator-4.3.2 idna-2.8 ipython-genutils-0.2.0 jsonschema-3.0.0 jupyter-core-4.4.0 kiwisolver-1.0.1 mappy-2.15 matplotlib-3.0.2 nanoget-1.7.7 nanomath-0.22.0 nanopack-1.0.0 nanoplotter-1.3.1 nbformat-4.4.0 numpy-1.16.1 pandas-0.24.1 patsy-0.5.1 pauvre-0.1.86 plotly-3.6.1 psutil-5.5.1 pyparsing-2.3.1 pyrsistent-0.14.11 pysam-0.15.2 python-dateutil-2.8.0 pytz-2018.9 requests-2.21.0 retrying-1.3.3 scipy-1.2.1 seaborn-0.9.0 setuptools-40.8.0 six-1.12.0 statsmodels-0.9.0 traitlets-4.3.2 urllib3-1.24.1

This worked!!

$ NanoComp -h

usage: NanoComp [-h] [-v] [-t THREADS] [-o OUTDIR] [-p PREFIX] [--verbose]

                [--raw] [--readtype {1D,2D,1D2}] [--maxlength N]

                [--minlength N] [--barcoded] [--split_runs TSV_FILE]

                [-f {eps,jpeg,jpg,pdf,pgf,png,ps,raw,rgba,svg,svgz,tif,tiff}]

                [-n names [names ...]] [-c colors [colors ...]]

                [--plot {violin,box,false}] [--title TITLE] [--dpi DPI]

                (--fasta file [file ...] | --fastq files [files ...] | --summary files [files ...] | --bam files [files ...])

Compares long read sequencing datasets.

fastqc -java.lang.OutOfMemoryError: Java heap space - Solved!

$fastqc filename.fastq
Started analysis of filename.fastq
Exception in thread "Thread-1" java.lang.OutOfMemoryError: Java heap space
    at uk.ac.babraham.FastQC.Modules.GCModel.GCModel.<init>(GCModel.java:69)
    at uk.ac.babraham.FastQC.Modules.PerSequenceGCContent.processSequence(PerSequenceGCContent.java:198)
    at uk.ac.babraham.FastQC.Analysis.AnalysisRunner.run(AnalysisRunner.java:88)
    at java.base/java.lang.Thread.run(Thread.java:844)

$ grep -n 'Xm' /home/prakki/sw/FastQC/fastqc
167:    unshift @java_args,"-Xmx${memory}m";
170:    unshift @java_args,'-Xmx250m';

$ vi /home/prakki/sw/FastQC/fastqc

Changed the 250m to 10g (depends on the RAM of your computer) in the line 170

$ fastqc filename.fastq
Started analysis of filename.fastq
Approx 5% complete for filename.fastq
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Analysis complete for filename.fastq