NestTablesXL

<code>NestTablesXL</code> reads the R lists output by the HpltFind() function
and translates them to an Excel workbook for more convenient evaluation of the
inferred haplotypes and curation of unresolved and incongruent sequences. The
workbook contains separate tabs for each nest in the data set and provides an
overview of the genotypes of the samples in each nest and the inferred
haplotypes.

Fifteen tools for bioinformatics processing and analysis of major
histocompatibility complex (MHC) data. The functions are tailored for amplicon data
sets that have been filtered using the dada2 method (for more information on
dada2, visit <https://benjjneb.github.io/dada2/> ), but even other types of data
sets can be analyzed.
The ReplMatch() function matches replicates in data sets in order to evaluate
genotyping success.
The GetReplTable() and GetReplStats() functions perform such an evaluation.
The CreateFas() function creates a fasta file with all the sequences in the data
set.
The CreateSamplesFas() function creates individual fasta files for each sample in
the data set.
The DistCalc() function calculates Grantham, Sandberg, or p-distances from pairwise
comparisons of all sequences in a data set, and mean distances of all pairwise
comparisons within each sample in a data set. The function additionally outputs five
tables with physico-chemical z-descriptor values (based on Sandberg et al. 1998) for
each amino acid position in all sequences in the data set. These tables may be useful
for further downstream analyses, such as estimation of MHC supertypes.
The BootKmeans() function is a wrapper for the kmeans() function of the 'stats'
package, which allows for bootstrapping. Bootstrapping k-estimates may be
desirable in data sets, where e.g. BIC- vs. k-values do not produce clear
inflection points ("elbows"). BootKmeans() performs multiple runs of kmeans() and
estimates optimal k-values based on a user-defined threshold of BIC reduction. The
method is an automated and bootstrapped version of visually inspecting elbow plots
of BIC- vs. k-values.
The ClusterMatch() function is a tool for evaluating whether different k-means()
clustering models identify similar clusters, and summarize bootstrap model stats as
means for different estimated values of k. It is designed to take files produced by
the BootKmeans() function as input, but other data can be analysed if the
descriptions of the required data formats are observed carefully.
The PapaDiv() function compares parent pairs in the data set and calculate their
joint MHC diversity, taking into account sequence variants that occur in both
parents.
The HpltFind() function infers putative haplotypes from families in the data
set.
The GetHpltTable() and GetHpltStats() functions evaluate the accuracy of
the haplotype inference.
The CreateHpltOccTable() function creates a binary (logical) haplotype-sequence
occurrence matrix from the output of HpltFind(), for easy overview of which
sequences are present in which haplotypes.
The HpltMatch() function compares haplotypes to help identify overlapping and
potentially identical types.
The NestTablesXL() function translates the output from HpltFind() to an Excel
workbook, that provides a convenient overview for evaluation and curating of the
inferred putative haplotypes.

Jacob Roved

MHCtools

Analysis of MHC Data in Non-Model Species

NestTablesXL function

<dl><dt>nest_table</dt>
<dd>is a table containing the sample names of parents and
offspring in each nest. This table should be organized so that the
individual names are in the first column (Sample_ID), and the nest number
is in the second column (Nest). For each nest, the first two rows should be
the parents, followed immediately by the offspring in the subsequent rows,
and then followed by the next nest, and so on. It is assumed that nests are
numbered consecutively beginning at 1. Please use the same table as was used
to generate the haplotypes using HpltFind().</dd>
<dt>seq_table</dt>
<dd>seq_table is a sequence table as output by the 'dada2'
pipeline, which has samples in rows and nucleotide sequence variants in
columns. Please use the same table as was used to generate the haplotypes
using HpltFind().</dd>
<dt>filepath</dt>
<dd>is a user defined path to the folder where the output files
from the HpltFind() function have been saved.</dd>
<dt>path_out</dt>
<dd>is a user defined path to the folder where the output file
will be saved.</dd></dl>

Arguments

NestTablesXL() function — NestTablesXL

<dl>

<dt>nest_table</dt>
<dd>is a table containing the sample names of parents and
offspring in each nest. This table should be organized so that the
individual names are in the first column (Sample_ID), and the nest number
is in the second column (Nest). For each nest, the first two rows should be
the parents, followed immediately by the offspring in the subsequent rows,
and then followed by the next nest, and so on. It is assumed that nests are
numbered consecutively beginning at 1. Please use the same table as was used
to generate the haplotypes using HpltFind().</dd>


<dt>seq_table</dt>
<dd>seq_table is a sequence table as output by the 'dada2'
pipeline, which has samples in rows and nucleotide sequence variants in
columns. Please use the same table as was used to generate the haplotypes
using HpltFind().</dd>


<dt>filepath</dt>
<dd>is a user defined path to the folder where the output files
from the HpltFind() function have been saved.</dd>


<dt>path_out</dt>
<dd>is a user defined path to the folder where the output file
will be saved.</dd>

</dl>

NestTablesXL: NestTablesXL() function

Description

Usage

Value

Arguments

Details

See Also

Examples