![]() ![]() ![]() We want to calculate the p-value for calling a G SNP in this column. All 3 reads have quality 20 ( = 99% confidence) at this position. 1 read contains an A in the column and the other 2 reads contain a G. The approximate p-value method calculates the p-value by first averaging the qualities of each base equal to the proposed SNP and averaging the qualities of each base not equal to the proposed SNP.Įxample: Assume you have a column where the reference sequence is an A and there are 3 reads covering that position.In other words the p-values calculated are independent of the reference sequence data. When finding variations relative to a reference sequence, the p-value calculated is for the variant, not the change.Gaps are assumed to have a quality equal to the minimum quality on either side of them (after adjusting for homopolymers).This is done because variations may be called at either end of the homopolymer and because reads may be from different strands. For example if a series of 6 G's have quality values 37, 31, 23, 15, 7, 2 then these are treated as though they are 2, 7, 15, 15, 7, 2. Homopolymer region qualities are reduced to be symmetrical across the homopolymer.Ambiguity characters are ignored (other characters in the column are still used).The contig is assumed to have been fine tuned around indels.Click the down arrow next to the exponent of the Maximum Variant P-Value setting to increase the number of variants found. The lower the p-value, the more likely the variation at the given position represents an real variant. The p-value represents the probability of a sequencing error resulting in observing bases with at least the given sum of qualities. It can also calculate p-values for variations and filter only for variations with a specified maximum P-Value.įor full details of how the various settings work in the Variation/SNP finder, hover the mouse over them to read the tooltips or click one of the '?' buttons. This feature can also be configured to only find disagreements in coding regions (if the reference sequence has CDS annotations present) and can analyze the effects of variations on the protein translation to allow you to quickly identify silent or non-silent mutations. The Find Variations/SNPs feature from the Annotate & Predict menu will annotate regions of disagreement and can be configured to only find disagreements above a minimum threshold to screen out disagreements due to read errors. Manually investigating every little disagreement can be time consuming on larger contigs. Each disagreement can then be examined or resolved. With this on you can quickly jump to each disagreement by pressing Ctrl+D (command+D on Mac OS X) or by clicking the arrows in the sequence viewer option panel to the right. When this is on, matching bases are grayed out and bases not matching are left colored. Select the options Disagreements to Consensus or Reference depending on your needs. To easily identify bases which do not match the consensus or reference sequence, turn on Highlighting in the consensus section of the sequence viewer options. ![]() Analysis of Assemblies and Alignments Finding polymorphisms ![]()
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