%0 Figure %A Li, Hong %A Glusman, Gustavo %A Hu, Hao %A Shankaracharya %A Caballero, Juan %A Hubley, Robert %A Witherspoon, David %A L. Guthery, Stephen %A E. Mauldin, Denise %A B. Jorde, Lynn %A Hood, Leroy %A C. Roach, Jared %A D. Huff, Chad %D 2014 %T Performance of relationship estimation in 30 sequenced families using (A) GERMLINE-ERSA2.0, (B) fastIBD-ERSA2.0, and (C) ISCA-ERSA2.0. %U https://plos.figshare.com/articles/figure/_Performance_of_relationship_estimation_in_30_sequenced_families_using_A_GERMLINE_ERSA2_0_B_fastIBD_ERSA2_0_and_C_ISCA_ERSA2_0_/918790 %R 10.1371/journal.pgen.1004144.g002 %2 https://plos.figshare.com/ndownloader/files/1367429 %K genetics %K Heredity %K Linkage (genetics) %K population genetics %K haplotypes %K genomics %K Genome analysis tools %K Genome complexity %K Genome sequencing %K estimation %K 30 %K sequenced %X

Area of the circles indicates the percentage of individual pairs whose estimated degrees of relationship are exactly the same as reported relationship. FS: full sibling. PO: parent offspring. UN: unrelated individuals. All ERSA analyses employed IBD masking. Histograms represent the number of pairs in each relationship category. Most of the pedigrees were ascertained on the basis of common, complex or rare, Mendelian diseases. As we have previously reported, this ascertainment can produce a downward bias in distant relationship estimates [10], which may account for the differences in relationship estimates between sequenced and simulated pedigrees for 10th through 12th degree relationships (see Figure S5).

%I PLOS Genetics