Search Results for "maf"

DNA and RNA nucleotide sequences are an ubiquitous element of all biological cells and are serving on one hand as a comprehensive library of capabilities for the cells and on the other as an impressive regulatory system to control cellular function. The presented multi-alignment framework (MAF) should give researchers a simple sequence alignment platform as a functional template, flexible enough to adjust all steps but also comprehensive enough to join many different tools and custom parameter combinations if in-depth analysis is necessary or advised in e.g. low read rate situations. The platform enables researcher to apply multiple sequence aligners and further pre- and postprocessing tools in flexible combinations to analyze the subtle to remarkable differences between different sequence alignment and processing algorithms applied to the same data basis. ...

...It can also be used as a filter to extract and convert searches or alignments to common formats. Inputs: - Sequence database search: BLAST, FASTA suites. - Multiple sequence alignment: CLUSTAL, HSSP, MSF, FASTA, PIR, MAF. Outputs: - HTML, FASTA, CLUSTAL, MSF, PIR, RDB (tab-separated). Found a bug? Please open an issue on the MView issue tracker at https://github.com/desmid/mview/issues or send an email to biomview@gmail.com.

...Formats which can be generated by fcGENE: plink-pedigree, plink-raw, plink-dosage, mach-inputs, minimac-inputs, impute-inputs, beagle-inputs and bimbam-inputs, HAPLOVIEW-inputs, EIGENSOFT-inputs. Further application: -obtaining templates of necessary imputation commands and commands of other imputation tool - Quality control according as MAF,HWE & CALLRATE. key words: genotype transformation, convert genotype format, imputation output, PLINK, IMPUTE, MACH, minimac, HAPLOVIEW, BEAGLE, BIMBAM,EIGENSOFT.

...General pipeline: 1-iterative De Novo assembly, with different k-mer values, trying to assemble a build that matches a target mitochondrial genome given. 2-searches for all mitochondrial gene features and circularization. 3-stores the best result found. 4-uses the best assembly as backbone for a reference based assembly, using MIRA and MITObim, trying to extend the mitogenome and close gaps. 5-annotates the best assembly, identifying the start and end position of each and every feature. 6-creates a folder with all the results (PNG, GENBANK, FASTA, SEQUIN, CAF, MAF and a stats logfile).