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A scoring matrix is used to compute a score for finding identical 3-letter words or similar 3-letter words that takes into account the liklihood of one being related to another. Although these matrices are empirical, they encompass factors like the number of mutations required (which is why there are different matrices for different extents of divergence) ...


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There are certain very well defined groups of genes that you would expect to be co-expressed, e.g. ribosomal proteins, proteosome subunits, splicesome components, VHATPase subunits; and each of these groups are co-expressed in different circumstances. It therefore looks to me that either your different tumour tissues (if that is the situation) are in similar ...


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Check the beautiful publication of Daniel Ramsköld et al. 2009, which holds the numbers for generally anticipated co-expression. The specific level of co-expression, which applies to your scenario, will depend upon your tissue, your thresholds, and your definition of co-expression. It you look for a co-change of some genes across different specimen (rather ...


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Preprocessing will and should always depend upon the biology that you try to answer or discover (e.g.: There might be an experimental rationale to believe that some genes behave differently in individual samples - and that different samples could possibly have different distributions.) log-transforming your data by itself is usually no problem, and hugely ...


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Setting a minimum E-value threshold will result in literally every single entry in the database with E-values above that value, as they will have very large E-values. You will expect a million hits with 1000000 E-value, and as a result you will not get any useful information from the search. Can you explain why you want to set a minimum E-value?


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There is no such option. You can perform the alignment and filter the hits later. However, I wonder why you really need that. Lower E-value indicates lower chance of an alignment randomly picked from a database, to have a given score.


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The easiest answer would be to ask the authors of the patent. Several other possibilities (see comments) were excluded, such as: restriction sites which interfere with cloning signal peptide proteolytic cleavage Although it's just a theory, removing part of the N-terminus might improve protein stability and half-life time because the first 30-40 amino ...


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From personal experience, nearly all count data whether from microarray or reads from RNAseq of some kind, requires a log transformation of the counts. Usually a small fraction is added to all values before doing so to zero protect. Log2(counts + 0.5) or some such. This is independent of the treatments. If you log transform one sample, you will do the same ...


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Exome data can be used to determine both somatic point mutations and copy number variations. The limiting element for the power of detection for both is read count (how many reads per gene). Exome data: Exome data uses a reference (for a trio, that would be parents; for cancer, that would be a paired normal sample from blood or non-invasive tissue) in ...


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If you are asking solely about data structure, the two data formats that you have given are essentially the same. Each row represents a PPI, so in a network a line (edge) will link the proteins (nodes) given in columns one and two. Column three is an edge score, but it can indicate a few things, confidence in the interaction or strength of the interaction. ...


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Please ask questions about Bioconductor on the Bioconductor support site. Bioconductor also distributes 'annotation' packages with curated information. These don't rely on a web service, so are always available, and are fixed at each (6 month) Bioconductor release, but are less comprehensive. Choose your organism BiocInstaller::biocLite(c("org.Hs.eg.db", "...


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Take a look at the biomaRt package. This package allows you to access some databases in R directly. Quote from the user's guide: The package enables retrieval of large amounts of data in a uniform way without the need to know the underlying database schemas or write complex SQL queries. Examples of BioMart databases are Ensembl, Uniprot and ...


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From Entrez Programming Utilities Help [Internet]: Input: Any Entrez text query (&term); Entrez database (&db); &usehistory=y; Existing web environment (&WebEnv) from a prior E-utility call To avoid the error messages, web1, and key1 can be used as terms (these are usually being used to associate with other searches), however this ...


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We will be needing some additional information to answer your question more completely: What sequencing platform are you using? Illumina HiSeq/MySeq; Ion proton What type of sequencing (as noted by @CMosychuk): Exome or Whole Genome? What type of variant caller (as noted by @CMosychuk): Unified Genotyper; Haplotype Caller; TVC The QUAL metric is heavily ...


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According to the HGVS guidelines, a letter prefix should be used to indicate the reference sequence used. Accepted prefixes are: “g.” for a genomic reference sequence “m.” for a mitochondrial reference sequence “c.” for a coding DNA reference sequence “n.” for a non-coding DNA reference sequence “r.” for an RNA reference sequence (transcript) “p.” for a ...


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ID mapping This is called ID mapping. It used to be a headache as programmatic access was the only real way, but it is pretty trivial these days. As mentioned in the comments, by far the most popular and easy method is to use Uniprot's list uploader for mapping. The corresponding publication can be found here. You must convert from Gene name to Uniprot KB ...


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ID mapping This is called ID mapping. It used to be a headache as programmatic sequence comparisons were the only real way, but it is pretty trivial these days. As mentioned in the comments, by far the most popular and easy method is to use Uniprot's list uploader for mapping. The corresponding publication can be found here. Example Programmatic access ...


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If you look at the DNA sequence in the patent, you will see that it does not start with ATG and does not end with a stop codon. The disclosed sequence has some additional bases in it, therefore the discrepancy in protein and DNA length. Those additional bases almost always occur in cDNA, e.g. because of polyadenylation, Kozak sequences, etc.



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