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--- tutorials:population-diversity:snp-chips [2020/09/21 11:04] – [Data analysis workflow with Plink 1.9] bngina
+++ tutorials:population-diversity:snp-chips [2020/09/22 10:21] (current) – [Data analysis workflow with Plink 1.9] bngina
@@ Line 165: / Line 165: @@
 <code>
+######### summary statistics ########
 #missingness
@@ Line 174: / Line 178: @@
 </code>
+This creates two files.
+  *//bin_caprin_60k.imiss// - for the individuals
+  *//bin_caprin_60k.lmiss// - for the loci
+#The missing information found in the ''bin_caprin_60k.imiss'' for the individuals looks like below;
+<code>
+FID                               IID MISS_PHENO   N_MISS   N_GENO   F_MISS
+          WG6694108-DNA_A01_110kin          Y     1325    53347  0.02484
+         WG6694108-DNA_A02_105kin1          Y     1346    53347  0.02523
+           WG6694108-DNA_A03_55kin          Y     1313    53347  0.02461
+           WG6694108-DNA_A04_50kin          Y     1360    53347  0.02549
+          WG6694108-DNA_A05_104kin          Y     1350    53347  0.02531
+           WG6694108-DNA_A06_82kin          Y     1412    53347  0.02647
+          WG6694108-DNA_A07_75kin1          Y     1387    53347    0.026
+         WG6694108-DNA_A08_110kin1          Y     1312    53347  0.02459
+           WG6694108-DNA_A09_77kin          Y     1356    53347  0.02542
+           WG6694108-DNA_A10_Zkin2          Y     1349    53347  0.02529
+</code>
+The information in each header is as follows;
+<code>
+FID                Family ID
+IID                Individual ID
+MISS_PHENO         Missing phenotype? (Y/N)
+N_MISS             Number of missing SNPs
+N_GENO             Number of non-obligatory missing genotypes i.e total number of SNPs used
+F_MISS             Proportion of missing SNPs (in percentage)
+</code>
+The information found in the ''bin_caprin_60k.lmiss'' for the SNPs is as below;
+<code>
+ CHR                           SNP   N_MISS   N_GENO   F_MISS
+           snp1-scaffold1-2170        4      648 0.006173
+      snp1-scaffold708-1421224        8      648  0.01235
+        snp10-scaffold1-352655        2      648 0.003086
+   snp1000-scaffold1026-533890        0      648        0
+  snp10000-scaffold1356-652219        4      648 0.006173
+  snp10001-scaffold1356-703514        9      648  0.01389
+  snp10002-scaffold1356-766996       10      648  0.01543
+  snp10003-scaffold1356-808120        5      648 0.007716
+  snp10004-scaffold1356-853276        3      648  0.00463
+  snp10005-scaffold1356-907019        2      648 0.003086
+</code>
+The information in each column is as follows;
+<code>
+SNP                SNP identifier
+CHR                Chromosome number
+N_MISS             Number of individuals missing this SNP
+N_GENO             Number of non-obligatory missing genotypes i.e total number of genotypes in the population
+F_MISS             Proportion of sample missing for this SNP (in percentage)
+</code>
+We can generate a file with filters added for the rate missing data in individuals ''--mind'' and call rate for the SNPs ''--geno'' and also for the minor allele frequency //(MAF)// , with flag ''--maf''.
+The thresholds for these filters should be adjusted accordingly to the different data sets.
+<code>
+#### filter data ###
+plink --file ${file} \
+ --geno 0.05 \   #95% call rate of SNPs
+ --maf 0.01\     #SNPs with less than 1% minor allele frequencies
+ --mind 0.25 \   #individuals with more than 25% missing data
+ --out ${out}/bin_caprin_60k_fltrd \
+ --make-bed
+</code>
 ===== Data analysis workflow with R and adegenet =====