github.com - HapCUT2 is a maximum-likelihood-based tool for assembling haplotypes from DNA sequence reads, designed to "just work" with excellent speed and accuracy. We found that previously described haplotype assembly methods are specialized for specific read...
github.com - maftools - An R package to summarize, analyze and visualize MAF files. Introduction.
With advances in Cancer Genomics, Mutation Annotation Format (MAF) is being widley accepted and used to store variants detected. The Cancer Genome Atlas Project...
hibberdlab.com - Transrate is software for de-novo transcriptome assembly quality analysis. It examines your assembly in detail and compares it to experimental evidence such as the sequencing reads, reporting quality scores for contigs and assemblies. This...
Research Associate (RA) Two (2)
Ph.D. in Bioinformatics/ Agricultural Statistics/ Statistics/ Computer Science/ Computer Application or equivalent or Master’s in Bioinformatics/ Agricultural Statistics/ Statistics/ Computer Science/ Computer...
github.com - The major problem of scaffolding polyploid genome is that Hi-C signals are frequently detected between allelic haplotypes and any existing stat of art Hi-C scaffolding program links the allelic haplotypes together. To solve the problem, we developed...
github.com - TMAP - torrent mapping alignment program General Notes
TMAP is a fast and accurate alignment software for short and long nucleotide sequences produced by next-generation sequencing technologies.
The latest TMAP is unsupported. To use a...
github.com - SvABA is a method for detecting structural variants in sequencing data using genome-wide local assembly. Under the hood, SvABA uses a custom implementation of SGA (String Graph Assembler) by Jared Simpson, and BWA-MEM by Heng Li....
github.com - NextDenovo is a string graph-based de novo assembler for TGS long reads. It uses a "correct-then-assemble" strategy similar to canu, but requires significantly less computing resources and storages. After assembly, the per-base error rate...
github.com - Barrnap predicts the location of ribosomal RNA genes in genomes. It supports bacteria (5S,23S,16S), archaea (5S,5.8S,23S,16S), mitochondria (12S,16S) and eukaryotes (5S,5.8S,28S,18S).
It takes FASTA DNA sequence as input, and write GFF3 as output....