https://f1000research.com/articles/6-100/

https://github.com/jason-weirather/AlignQC

Address of the bookmark: https://www.healthcare.uiowa.edu/labs/au/AlignQC/

Cleaning your data in this way is often required: Reads from small-RNA sequencing contain the 3’ sequencing adapter because the read is longer than the molecule that is sequenced. Amplicon reads start with a primer sequence. Poly-A tails are useful for pulling out RNA from your sample, but often you don’t want them to be in your reads.

Cutadapt helps with these trimming tasks by finding the adapter or primer sequences in an error-tolerant way. It can also modify and filter reads in various ways. Adapter sequences can contain IUPAC wildcard characters. Also, paired-end reads and even colorspace data is supported. If you want, you can also just demultiplex your input data, without removing adapter sequences at all.

Cutadapt comes with an extensive suite of automated tests and is available under the terms of the MIT license.

If you use cutadapt, please cite DOI:10.14806/ej.17.1.200 .

Address of the bookmark: https://cutadapt.readthedocs.io/en/stable/installation.html#quickstart

https://genome.sph.umich.edu/wiki/Vt

https://github.com/atks/vt

Address of the bookmark: https://genome.sph.umich.edu/wiki/Vt

Address of the bookmark: http://ml.ssu.ac.kr/gSearch/index.html

Title: Comparison of Short Read De Novo Alignment Algorithms 

Author: Nikhil Gopal

Address of the bookmark: http://biochem218.stanford.edu/Projects%202011/Gopal%202011.pdf

Address of the bookmark: https://github.com/iansealy/coursera-assembly

Quickstart

http://nanopolish.readthedocs.io/en/latest/quickstart_consensus.html

Algorithms

http://simpsonlab.github.io/2017/06/30/nanopolish-v0.7.0/

Address of the bookmark: https://github.com/jts/nanopolish

AVAILABILITY AND IMPLEMENTATION:

http://cab.spbu.ru/software/quast-lg

Address of the bookmark: http://cab.spbu.ru/software/quast-lg/

usage:   canu [-correct | -trim | -assemble | -trim-assemble] \
              [-s ] \
               -p  \
               -d  \
               genomeSize=[g|m|k] \
               -maxThreads=2 \
               useGrid=false \
              [other-options] \
               read_file.fastq.gz

A default Canu run produces usually high quality assembly, example of a command that was used for testing can be found below. However, there are still a lot of parameters that are possible to tweak. For example if we desire to assemble haplotypes separately of if we want to smash them together, we can alternate the error correction process.

canu -p test_asmbl \
     -d asm_test3 \
     genomeSize=2m \
     -maxThreads=2 useGrid=false \
     -pacbio-raw \ ~/pacbio/dna/sample_reads.fastq.gz

There is a brilliant section in documentation about parameter tweaking.

The output directory contains will contain many files. The most interesting ones are:

• *.correctedReads.fasta.gz : file containing the input sequences after correction, trim and split based on consensus evidence.
• *.trimmedReads.fastq : file containing the sequences after correction and final trimming
• *.layout : file containing informations about read inclusion in the final assembly
• *.gfa : file containing the assembly graph by Canu
• *.contigs.fasta : file containing everything that could be assembled and is part of the primary assembly

The basic stats of assembly can be read from reports generated by the assembler, or calculated using standard UNIX command line tools.

More at https://canu.readthedocs.io/en/latest/faq.html

https://nxrepair.readthedocs.io/en/latest/tutorial.html

nxrepair aligned_matepairs.bam assemblyfasta.fasta error_locations.csv new_fasta.fasta

Address of the bookmark: https://github.com/rebeccaroisin/nxrepair