github.com - This is a pipeline for finding motifs in fasta files.It can be run from the command line as follows:
usage: orange_pipeline_refine.py [-h] [-w W] [--nmotifs NMOTIFS] [--iter ITER] [-c C][-s S] [-d] [-ff] [-v V]positive_seq negative_seq
positional...
github.com - dnaPipeTE (for de-novo assembly & annotation Pipeline for Transposable Elements), is a pipeline designed to find, annotate and quantify Transposable Elements in small samples of NGS datasets. It is very useful to quantify the proportion of TEs...
github.com - gapFinisher to process SSPACE-LongRead output to fill gaps after the scaffolding. gapFinisher is based on the controlled use of a previously published gap filling tool FGAP and works on all standard Linux/UNIX command...
github.com - Liftoff is a tool that accurately maps annotations in GFF or GTF between assemblies of the same, or closely-related species. Unlike current coordinate lift-over tools which require a pre-generated “chain” file as input, Liftoff is a...
github.com - The pipeline was developed based on a popular workflow framework Nextflow, composed of four core procedures including reads alignment, assembly, identification and quantification. It contains various unique features such as well-designed...
github.com - iMAGine is a metagenomic workflow which includes filtering, assembling, and binning.
This workflow includes the following tools which are needed to be installed in the system.
fastp
spades assembler
QUAST
bwa
samtools
metabat2
CheckM
ftp.genomics.org.cn - An efficient tool called Connecting Overlapped Pair-End (COPE) reads, to connect overlapping pair-end reads using k-mer frequencies. We evaluated our tool on 30× simulated pair-end reads from Arabidopsis thaliana with 1% base error. COPE...
github.com - PERGA - Paired End Reads Guided Assembler
PERGA is a novel sequence reads guided de novo assembly approach which adopts greedy-like prediction strategy for assembling reads to contigs and scaffolds. Instead of using single-end reads to construct...
faculty.cse.tamu.edu - With increased availability of de novo assembly algorithms, it is feasible to study entire transcriptomes of non-model organisms. While algorithms are available that are specifically designed for performing transcriptome assembly from...