github.com - The NanoPack tools are written in Python3 and released under the GNU GPL3.0 License. The source code can be found at https://github.com/wdecoster/nanopack, together with links to separate scripts and their documentation. The scripts are compatible...
github.com - Binaries of ngs-bits are available via Bioconda. Alternatively, ngs-bits can be built from sources:
Binaries for Linux/macOS
From sources for Linux/macOS
From sources for Windows
bioinformatics-core-shared-training.github.io - One of the best tutorial for beginners ...
https://bioinformatics-core-shared-training.github.io/cruk-summer-school-2017/Day1/Session4-seqIntro.html
github.com - Miniasm is a very fast OLC-based de novo assembler for noisy long reads. It takes all-vs-all read self-mappings (typically by minimap) as input and outputs an assembly graph in the GFA format. Different from mainstream...
Miniasm is a very fast OLC-based de novo assembler for noisy long reads. It takes all-vs-all read self-mappings (typically by minimap) as input and outputs an assembly graph in the GFA format. Different from mainstream...
github.com - Flye is a de novo assembler for long and noisy reads, such as those produced by PacBio and Oxford Nanopore Technologies. The algorithm uses an A-Bruijn graph to find the overlaps between reads and does not require them to be error-corrected. After...
1001genomes.org - GenomeMapper is a short read mapping tool designed for accurate read alignments. It quickly aligns millions of reads either with ungapped or gapped alignments. It can be used to align against multiple genomes simulanteously or against a single...
japsa.readthedocs.io - npScarf (jsa.np.npscarf) is a program that connect contigs from a draft genomes to generate sequences that are closer to finish. These pipelines can run on a single laptop for microbial datasets. In real-time mode, it can be integrated with simple...
github.com - Here is the command to run the tool:
python finisherSC.py destinedFolder mummerPath
If you are running on server computer and would like to use multiple threads, then the following commands can generate 20 threads to run FinisherSC.
python...