Data frame with data in the <code>_rc</code> format for 25 populations Each
row of the data frame is a different site. The first 9 columns contain
general information about the site, while the remaining contain the number
of reads observed at that site for each of the 25 populations.

datasets

Provides functions to simulate Pool-seq data under models of
demographic formation and to import Pool-seq data from real populations.
Implements two ABC algorithms for performing parameter estimation and
model selection using Pool-seq data. Cross-validation can also be
performed to assess the accuracy of ABC estimates and model choice.
Carvalho et al., (2022) <doi:10.1111/1755-0998.13834>.

João Carvalho

poolABC

Approximate Bayesian Computation with Pooled Sequencing Data

Vítor Sousa

rc1 function

a data frame with 5000 rows and 59 columns. Each of the columns
corresponds to :
<dl><dt>col1</dt>
<dd>reference chromosome (contig).</dd>
<dt>col2</dt>
<dd>reference position.</dd>
<dt>col3</dt>
<dd>reference character.</dd>
<dt>col4</dt>
<dd>number of alleles found in all populations.</dd>
<dt>col5</dt>
<dd>allele characters in all populations (sorted by counts in all
populations).</dd>
<dt>col6</dt>
<dd>sum of deletions in all populations (should be zero, if not the
position may not be reliable).</dd>
<dt>col7</dt>
<dd>SNP type: <code>[pop, rc, rc|pop]</code>; pop: a SNP within or
between the populations; rc: a SNP between the reference sequence character
and the consensus of at least one populaton; rc|pop: both.</dd>
<dt>col8</dt>
<dd>most frequent allele in all populations <code>[12345..]</code>.</dd>
<dt>col9</dt>
<dd>second most frequent allele in all populations
<code>[12345..]</code>.</dd>
<dt>col10 - col34</dt>
<dd>frequencies of the most frequent allele (major) in the
form "allele-count/coverage.</dd>
<dt>col35 - col59</dt>
<dd>frequencies of the second most frequent allele (minor)
in the form "allele-count/coverage".</dd>
 
</dl>

Format

Data frame with an example of observed data — rc1

a data frame with 5000 rows and 59 columns. Each of the columns
corresponds to :
<dl>

<dt>col1</dt>
<dd>reference chromosome (contig).</dd>


<dt>col2</dt>
<dd>reference position.</dd>


<dt>col3</dt>
<dd>reference character.</dd>


<dt>col4</dt>
<dd>number of alleles found in all populations.</dd>


<dt>col5</dt>
<dd>allele characters in all populations (sorted by counts in all
populations).</dd>


<dt>col6</dt>
<dd>sum of deletions in all populations (should be zero, if not the
position may not be reliable).</dd>


<dt>col7</dt>
<dd>SNP type: <code>[pop, rc, rc|pop]</code>; pop: a SNP within or
between the populations; rc: a SNP between the reference sequence character
and the consensus of at least one populaton; rc|pop: both.</dd>


<dt>col8</dt>
<dd>most frequent allele in all populations <code>[12345..]</code>.</dd>


<dt>col9</dt>
<dd>second most frequent allele in all populations
<code>[12345..]</code>.</dd>


<dt>col10 - col34</dt>
<dd>frequencies of the most frequent allele (major) in the
form "allele-count/coverage.</dd>


<dt>col35 - col59</dt>
<dd>frequencies of the second most frequent allele (minor)
in the form "allele-count/coverage".</dd>
 
</dl>

rc1: Data frame with an example of observed data

Description

Usage

Arguments

Format