Day 1 Session Recordings of Introduction To Bioinformatics: Analysis Of Plasmodium Falciparum Genome Data Training 2022

Recordings of sessions that took place on DAY 1 (28th November 2022) of Introduction To Bioinformatics Analysis Of Plasmodium Falciparum Genome Data Training 2022 held at Institut Pasteur de Côte d'Ivoire (IPCI, Cote d'Ivore). Both French and English are used during the training sessions. Day_1_session_1 - Introduction Day_1_session_2 - General Malaria Pathogen Theories Day_1_session_3 - General Malaria Pathogen Theories cont... Day_1_session_4 - Biology and Bioinformatics Day_1_session_5 - Workflows Day_1_session_6 - NGS Technologies and Malaria Data Day_1_session_7 - The Command Line This item also contains files, guides and presentations that were used during the training sessions</p

Day 4 Session Recordings of Introduction To Bioinformatics: Analysis Of Plasmodium Falciparum Genome Data Training 2022

Recordings of sessions that took place on DAY 4 (01 December 2022) of Introduction To Bioinformatics Analysis Of Plasmodium Falciparum Genome Data Training 2022 held at Institut Pasteur de Côte d'Ivoire (IPCI, Cote d'Ivore).Both French and English are used during the training sessions. Day_4_session_1 - Working with R Day_4_session_2 - Working with R cont ... Day_4_session_3 - Working with R cont ... Day_4_session_4 - Working with R cont ... Day_4_session_5 - Working with R looking at the tree Day_4_session_6 - Working with R Day_4_session_7 - Codes Day_4_session_8 - R issues Day_4_session_9 - Troubleshooting Day_4_session_10 - Coding in R Day_4_session_11 - Plotting in R Day_4_session_12 - Coding Day_4_session_13 - Coding Day_4_session_14 - Coding The zip archive contains files, guides and presentations that were used during the training sessions.</p

Number of strains by F-statistic.

<p>Boxplot of the inbreeding coefficient (1 − <i>F</i>_<i>is</i>) for each sample grouped by the MAP number of inferred strains.</p

Example samples.

Four representative samples with WSAF for each SNP plotted against the PLAF, showing an absence of mixture (a), a partially panmixed sample (b), a simple mixture (c), and a complex mixture (d).</p

Model diagram.

The structure of the model can be understood in terms of four related states connecting the WSAF to the PLAF: no mixture (upper left); simple mixture (lower left); panmixture (upper right); and complex mixture (lower right).α is exaggerated for explanation; realistic values are less than 0.05.</p

Table of simulated parameter values. <i>C</i> is the number of read counts while <i>M</i>, <i>K</i> and <i>α</i> are as in Table 1.

<p>Table of simulated parameter values. <i>C</i> is the number of read counts while <i>M</i>, <i>K</i> and <i>α</i> are as in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004824#pcbi.1004824.t001" target="_blank">Table 1</a>.</p

Performance for parameter inference.

<p>Upper row: mean squared deviation for strain frequencies by number of read counts (left) and by number of SNPs (right). Lower row: absolute normalized deviation for panmixia coefficient by number of read counts (left) and by number of SNPs.</p

Examples of real and model-simulated data.

<p>For three samples (rows), we present the observed data WSAF plotted against the PLAF (first column), a diagram of the inferred model indicating the bands, proportions, and panmixia coefficient (second column), and data simulated under the inferred model. Panmixia coefficient and strain proportions are the MAP values. In the second column, the model’s PLAF-varying mixture densities are shown in grey scale, with black equal to one.</p

Component inference.

<p><i>Maximum a posteriori</i> (MAP) inferred number of components by number of read counts across 10 simulations, with dotted line at the true number of components.</p

Ghanian sample summary.

<p>The frequency of inferred number of strains per sample (left) and and the panmixia coefficient by number of strains (right). MAP estimates used.</p