BLAT

        BLAT: The BLAST-Like Alignment Tool is a pairwise sequence alignment tool from which you can align your sequences with one of the 5 the following databases: NPdenovo-protein, NPdenovo-nucleotide, Human-protein, Human-RefSeqGene and GRCH37/hg19. NPdenovo-protein and NPdenovo-nucleotide respectively represent protein and RefSeq gene sequences which are identified as carrying de novo mutations associated with neuropsychiatry in current studies. Human-protein and Human-RefSeqGene respectively represent protein and RefSeq gene sequences of human. GRCH37/hg19 represents human genome downloaded from UCSC.


Overlap genes in disorders

        By overlap genes analysis, you can get overlapping genes shared in ASD, EE, ID, SCZ and Control. You can also filter your results by selecting specific effects, gene regions and association level. There are 5 degrees of association levels defined according to the p value, and they are "strong"( p-value < 0.0001), "suggestive"(0.0001 ≤ p-value < 0.001), "positive"(0.001 ≤ p-value < 0.01), "possible"(0.01 ≤ p-value < 0.05) and "negative"( p-value ≥ 0.05,or no damaging mutation).


Custom extreme mutation

        You can define extreme mutation by yourself. By selecting specific disorders, methods, gene regions, effects, mutation types, damaging prediction softwares, dbSNP filters, 1000g filters, ESP and CG filters et al., you can get any putatively extreme mutations from NPdenovo database.
        In Damage prediction field, wherein listed a series of softwares available for your choices. By setting the minimum number of prediction softwares, you can define the prediction power, of which the default value is 6(only the mutations which at least 6 softwares predicted as damaging will be displayed). In dbSNP filters, 1000g filters, ESP and CG filters, all of the mutations will be filtered by the databases you choosed. In 1000g filters, ESP and CG filters, minor allele frequency (MAF) could be set as a filtering threshold, which the default is 0.01.


Co-expression

        In spatio-temporal co-expression analysis, a network of co-expression will be displayed. You can set a number of parameters to get the network you want. The size of nodes are ranked from large to small, a larger node refers to a stronger mutation. The color of nodes are ranked from dark to light, denoting the correlation with central node from significant to less significant. Several tables of the connections will also be displayed. The co-expression results are sorted by pearson correlation coefficient in descending order.


Submit de novo mutation

        If you find any neuropsychiatric disorder de novo mutations, please feel free to submit your data. Your kindness would be of great help for our future development. Formulate your data set as a tab-separated file, the format of your file should be like this: "chr start end ref method proband_id reference".