github.com - Filtering on quality and/or read length, and optional trimming after passing filters.Reads from stdin, writes to stdout.
Intended to be used:
directly after fastq extraction
prior to mapping
in a stream between extraction and...
Ancestral sequence reconstruction (ASR) – also known as ancestral gene/sequence reconstruction/resurrection – is a technique used in the study of molecular evolution
github.com - Development packages for zlib and libbz2 are needed, as well as a standard compiler environment. On Ubuntu, this can be installed via:
sudo apt-get install build-essential libtool automake zlib1g-dev libbz2-dev pkg-config
On MacOS, the Apple...
github.com - HALC, a high throughput algorithm for long read error correction. HALC aligns the long reads to short read contigs from the same species with a relatively low identity requirement so that a long read region can be aligned to at least one contig...
github.com - LRCstats is an open-source pipeline for benchmarking DNA long read correction algorithms for long reads outputted by third generation sequencing technology such as machines produced by Pacific Biosciences. The reads produced by third generation...
sourceforge.net - Grinder is a versatile program to create random shotgun and amplicon sequence libraries based on DNA, RNA or proteic reference sequences provided in a FASTA file.
Grinder can produce genomic, metagenomic, transcriptomic, metatranscriptomic,...
www.healthcare.uiowa.edu - Added Command line argument support.
Multi-stage execution modes.
Support for parallelization. Now execution proceeds in batches of long reads the size of which can be set by --long_read_batch_size N.
Better compressed intermediate files.
Added...
github.com - Wtdbg2 is a de novo sequence assembler for long noisy reads produced by PacBio or Oxford Nanopore Technologies (ONT). It assembles raw reads without error correction and then builds the consensus from intermediate assembly output. Wtdbg2...
github.com - medaka is a tool to create a consensus sequence from nanopore sequencing data. This task is performed using neural networks applied from a pileup of individual sequencing reads against a draft assembly. It outperforms graph-based methods...