github.com - ClinCNV detects CNVs in germline and somatic context in NGS data (targeted and whole-genome). We work in cohorts, so it makes sense to try ClinCNV if you have more than 10 samples (recommended amount - 40 since we estimate variances from...
csb5.github.io - LoFreq* (i.e. LoFreq version 2) is a fast and sensitive variant-caller for inferring SNVs and indels from next-generation sequencing data. It makes full use of base-call qualities and other sources of errors inherent in sequencing (e.g. mapping or...
github.com - Parliament2 identifies structural variants in a given sample relative to a reference genome. These structural variants cover large deletion events that are called as Deletions of a region, Insertions of a sequence into a region, Duplications of a...
benjjneb.github.io - The DADA2 tutorial goes through a typical workflow for paired end Illumina Miseq data: raw amplicon sequencing data is processed into the table of exact amplicon sequence variants (ASVs) present in each sample.
The DADA2...
github.com - Ktrim is written in C++ for GNU Linux/Unix platforms. After uncompressing the source package, you can find an executable file ktrim under bin/ directory compiled using g++ v4.8.5 and linked with libz...
www.weizmann.ac.il - Due to several requests, we are releasing an assingment of orthologs, determined using the same methods used in Hezroni et al. (BLAST, Whole Genome Alignment (WGA), and synteny). One is comparing human GENCODE genes (from GENCODE v30) to lncRNAs...
github.com - gget is a free, open-source command-line tool and Python package that enables efficient querying of genomic databases. gget consists of a collection of separate but interoperable modules, each designed to facilitate one type of...
biokit.readthedocs.io - BioKit is a set of tools dedicated to bioinformatics, data visualisation (biokit.viz), access to online biological data (e.g. UniProt, NCBI thanks to bioservices). It also contains more advanced tools related to data analysis...
For a beginner this can be is the hardest part, it is also the most important to get right.
It is possible to create a vector by typing data directly into R using the combine function ‘c’
x
same as
x
creates the vector x...