Mercurial > repos > xuebing > sharplabtool
view tools/human_genome_variation/snpFreq.xml @ 0:9071e359b9a3
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author | xuebing |
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date | Fri, 09 Mar 2012 19:37:19 -0500 |
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<tool id="hgv_snpFreq" name="snpFreq" version="1.0.0"> <description>significant SNPs in case-control data</description> <command interpreter="perl"> snpFreq2.pl $input $group1_1 $group1_2 $group1_3 $group2_1 $group2_2 $group2_3 0.05 $output </command> <inputs> <param format="tabular" name="input" type="data" label="Dataset" /> <param name="group1_1" label="Column with genotype 1 count for group 1" type="data_column" data_ref="input" /> <param name="group1_2" label="Column with genotype 2 count for group 1" type="data_column" data_ref="input" /> <param name="group1_3" label="Column with genotype 3 count for group 1" type="data_column" data_ref="input" /> <param name="group2_1" label="Column with genotype 1 count for group 2" type="data_column" data_ref="input" /> <param name="group2_2" label="Column with genotype 2 count for group 2" type="data_column" data_ref="input" /> <param name="group2_3" label="Column with genotype 3 count for group 2" type="data_column" data_ref="input" /> </inputs> <outputs> <data format="tabular" name="output" /> </outputs> <requirements> <requirement type="binary">R</requirement> </requirements> <tests> <test> <param name="input" ftype="tabular" value="snpFreqInput.txt" dbkey="hg18" /> <param name="group1_1" value="4" /> <param name="group1_2" value="5" /> <param name="group1_3" value="6" /> <param name="group2_1" value="7" /> <param name="group2_2" value="8" /> <param name="group2_3" value="9" /> <output name="output" file="snpFreqTestOut.txt" /> </test> </tests> <help> **Dataset formats** The input is tabular_, with six columns of allele counts. The output is also tabular, and includes all of the input data plus the additional columns described below. (`Dataset missing?`_) .. _tabular: ./static/formatHelp.html#tab .. _Dataset missing?: ./static/formatHelp.html ----- **What it does** This tool performs a basic analysis of bi-allelic SNPs in case-control data, using the R statistical environment and Fisher's exact test to identify SNPs with a significant difference in the allele frequencies between the two groups. R's "qvalue" package is used to correct for multiple testing. The input file includes counts for each allele combination (AA aa Aa) for each group at each SNP position. The assignment of codes (1 2 3) to these genotypes is arbitrary, as long as it is consistent for both groups. Any other input columns are ignored in the computation, but are copied to the output. The output appends eight additional columns, namely the minimum expected counts of the three genotypes for each group, the p-value, and the q-value. ----- **Example** - input file:: chr1 210 211 38 4 15 56 0 1 x chr1 228 229 55 0 2 56 0 1 x chr1 230 231 46 0 11 55 0 2 x chr1 234 235 43 0 14 55 0 2 x chr1 236 237 55 0 2 13 10 34 x chr1 437 438 55 0 2 46 0 11 x chr1 439 440 56 0 1 55 0 2 x chr1 449 450 56 0 1 13 20 24 x chr1 518 519 56 0 1 38 4 15 x Here the group 1 genotype counts are in columns 4 - 6, while those for group 2 are in columns 7 - 9. Note that the "x" column has no meaning. It was added to this example to show that extra columns can be included, and to make it easier to see where the new columns are appended in the output. - output file:: chr1 210 211 38 4 15 56 0 1 x 47 2 8 47 2 8 1.50219088598917e-05 6.32501425679652e-06 chr1 228 229 55 0 2 56 0 1 x 55.5 0 1.5 55.5 0 1.5 1 0.210526315789474 chr1 230 231 46 0 11 55 0 2 x 50.5 0 6.5 50.5 0 6.5 0.0155644201009862 0.00409590002657532 chr1 234 235 43 0 14 55 0 2 x 49 0 8 49 0 8 0.00210854461554067 0.000739840215979182 chr1 236 237 55 0 2 13 10 34 x 34 5 18 34 5 18 6.14613878554783e-17 4.31307984950725e-17 chr1 437 438 55 0 2 46 0 11 x 50.5 0 6.5 50.5 0 6.5 0.0155644201009862 0.00409590002657532 chr1 439 440 56 0 1 55 0 2 x 55.5 0 1.5 55.5 0 1.5 1 0.210526315789474 chr1 449 450 56 0 1 13 20 24 x 34.5 10 12.5 34.5 10 12.5 2.25757007974134e-18 2.37638955762246e-18 chr1 518 519 56 0 1 38 4 15 x 47 2 8 47 2 8 1.50219088598917e-05 6.32501425679652e-06 </help> </tool>