I am trying to align PAcBio data (data from third generation sequencer) using bwa mem. I am getting very less number of aligned reads in SAM file having coverage of less than 10X. I tried to use minimap2 as well for alignment but again the quality of sam file isn,t good. I am getting only few unique reads and they are aligning on reference with soft clipping. Moreover, my SAM file contains many cases of multimapping. The read length of spots is >2kb.

What other options are available to get better alignment results? I am working with this data for the very first time.

My project topis is 'Phylogeny, Phylogeography and Population Structure of the large river Pranws Macrobrachium species in the Southern Nigeria river drainge system. I sequenced the 12S,16S and the CO1 genes for this work.

I have opted to make evolutionary bioinformatics as specialist area. I wish that I can find a collaborator or expert under whose tutelage I will be guided. My interest is in the circumtropical species such as Peguins, Prawns, Shripms, doves that are found in almost all continents and climes. In the GenBank, several gene segments and sometimes the whole mitogenome have been sequenced. Comparing these available data is of interest to me. I need limited help as I have funding. 

This is WhatsHap 0.17 running under Python 3.6.6
Traceback (most recent call last):
File "/home/anaconda3/bin/whatshap", line 11, in <module>
load_entry_point('whatshap==0.17', 'console_scripts', 'whatshap')()
File "/home/anaconda3/lib/python3.6/site-packages/whatshap/__main__.py", line 83, in main
module.main(args)
File "/home/anaconda3/lib/python3.6/site-packages/whatshap/phase.py", line 1089, in main
run_whatshap(**vars(args))
File "/home/anaconda3/lib/python3.6/site-packages/whatshap/phase.py", line 580, in run_whatshap
out_file=output, tag=tag)
File "/home/anaconda3/lib/python3.6/site-packages/whatshap/vcf.py", line 478, in __init__
self._reader = vcf.Reader(filename=in_path)
File "/home/anaconda3/lib/python3.6/site-packages/vcf/parser.py", line 300, in __init__
self._parse_metainfo()
File "/home/anaconda3/lib/python3.6/site-packages/vcf/parser.py", line 317, in _parse_metainfo
line = next(self.reader)
File "/home/anaconda3/lib/python3.6/site-packages/vcf/parser.py", line 280, in <genexpr>
self.reader = (line.strip() for line in self._reader if line.strip())
File "/home/anaconda3/lib/python3.6/codecs.py", line 321, in decode
(result, consumed) = self._buffer_decode(data, self.errors, final)
UnicodeDecodeError: 'utf-8' codec can't decode byte 0x8b in position 1: invalid start byte

How to fix this error ? 

## Package Plan ##

environment location: /home/urbe/anaconda3/envs/probeMining

added / updated specs:
- biopython
- numpy
- scikit-learn
- scipy

The following packages will be downloaded:

package | build
---------------------------|-----------------
numpy-1.15.2 |py27_blas_openblashd3ea46f_1 4.2 MB conda-forge
python-2.7.15 | h33da82c_4 13.6 MB conda-forge
reportlab-3.5.9 | py27h77bcf2c_0 2.5 MB conda-forge
scikit-learn-0.20.0 |py27_blas_openblasha84fab4_201 13.5 MB conda-forge
biopython-1.68 | py27_0 2.5 MB bioconda
certifi-2018.10.15 | py27_1000 138 KB conda-forge
msgpack-python-0.5.6 | py27h2d50403_3 101 KB conda-forge
libpng-1.6.35 | ha92aebf_2 305 KB conda-forge
blas-1.1 | openblas 1 KB conda-forge
libtiff-4.0.9 | he6b73bb_2 521 KB conda-forge
openblas-0.2.20 | 8 17.0 MB conda-forge
mmtf-python-1.0.2 | py27_0 34 KB bioconda
scipy-1.1.0 |py27_blas_openblash7943236_201 39.4 MB conda-forge
olefile-0.46 | py_0 31 KB conda-forge
pillow-5.3.0 | py27hc736899_0 603 KB conda-forge
------------------------------------------------------------
Total: 94.3 MB

The following NEW packages will be INSTALLED:

biopython: 1.68-py27_0 bioconda
blas: 1.1-openblas conda-forge
ca-certificates: 2018.10.15-ha4d7672_0 conda-forge
certifi: 2018.10.15-py27_1000 conda-forge
freetype: 2.9.1-h6debe1e_4 conda-forge
jpeg: 9c-h470a237_1 conda-forge
libffi: 3.2.1-hfc679d8_5 conda-forge
libgcc-ng: 7.2.0-hdf63c60_3 conda-forge
libgfortran: 3.0.0-1 conda-forge
libpng: 1.6.35-ha92aebf_2 conda-forge
libstdcxx-ng: 7.2.0-hdf63c60_3 conda-forge
libtiff: 4.0.9-he6b73bb_2 conda-forge
mmtf-python: 1.0.2-py27_0 bioconda
msgpack-python: 0.5.6-py27h2d50403_3 conda-forge
ncurses: 6.1-hfc679d8_1 conda-forge
numpy: 1.15.2-py27_blas_openblashd3ea46f_1 conda-forge [blas_openblas]
olefile: 0.46-py_0 conda-forge
openblas: 0.2.20-8 conda-forge
openssl: 1.0.2p-h470a237_1 conda-forge
pillow: 5.3.0-py27hc736899_0 conda-forge
pip: 18.1-py27_1000 conda-forge
python: 2.7.15-h33da82c_4 conda-forge
readline: 7.0-haf1bffa_1 conda-forge
reportlab: 3.5.9-py27h77bcf2c_0 conda-forge
scikit-learn: 0.20.0-py27_blas_openblasha84fab4_201 conda-forge [blas_openblas]
scipy: 1.1.0-py27_blas_openblash7943236_201 conda-forge [blas_openblas]
setuptools: 40.4.3-py27_0 conda-forge
sqlite: 3.25.2-hb1c47c0_0 conda-forge
tk: 8.6.8-ha92aebf_0 conda-forge
wheel: 0.32.1-py27_0 conda-forge
xz: 5.2.4-h470a237_1 conda-forge
zlib: 1.2.11-h470a237_3 conda-forge

Proceed ([y]/n)? y

Downloading and Extracting Packages
numpy-1.15.2 | 4.2 MB | ##################################### | 100%
python-2.7.15 | 13.6 MB | ##################################### | 100%
reportlab-3.5.9 | 2.5 MB | ##################################### | 100%
scikit-learn-0.20.0 | 13.5 MB | ##################################### | 100%
biopython-1.68 | 2.5 MB | ##################################### | 100%
certifi-2018.10.15 | 138 KB | ##################################### | 100%
msgpack-python-0.5.6 | 101 KB | ##################################### | 100%
libpng-1.6.35 | 305 KB | ##################################### | 100%
blas-1.1 | 1 KB | ##################################### | 100%
libtiff-4.0.9 | 521 KB | ##################################### | 100%
openblas-0.2.20 | 17.0 MB | ##################################### | 100%
mmtf-python-1.0.2 | 34 KB | ##################################### | 100%
scipy-1.1.0 | 39.4 MB | ##################################### | 100%
olefile-0.46 | 31 KB | ##################################### | 100%
pillow-5.3.0 | 603 KB | ##################################### | 100%
Preparing transaction: done
Verifying transaction: done
Executing transaction: done
#
# To activate this environment, use
#
# $ conda activate probeMining
#
# To deactivate an active environment, use
#
# $ conda deactivate

➜ OligoMiner git:(master) conda activate probeMining

CommandNotFoundError: Your shell has not been properly configured to use 'conda activate'.
If your shell is Bash or a Bourne variant, enable conda for the current user with

$ echo ". /home/urbe/anaconda3/etc/profile.d/conda.sh" >> ~/.bashrc

or, for all users, enable conda with

$ sudo ln -s /home/urbe/anaconda3/etc/profile.d/conda.sh /etc/profile.d/conda.sh

The options above will permanently enable the 'conda' command, but they do NOT
put conda's base (root) environment on PATH. To do so, run

$ conda activate

in your terminal, or to put the base environment on PATH permanently, run

$ echo "conda activate" >> ~/.bashrc

Previous to conda 4.4, the recommended way to activate conda was to modify PATH in
your ~/.bashrc file. You should manually remove the line that looks like

export PATH="/home/urbe/anaconda3/bin:$PATH"

^^^ The above line should NO LONGER be in your ~/.bashrc file! ^^^

4C:chromosome conformation capture-on-chip

5C : chromosome conformation capture carbon copy

[WARNING] For a multi-part index, no @SQ lines will be outputted.

How to resolve it.