Analysis of sieve effects in the RTS,S malaria vaccine trial

Endpoints

1. Clinical malaria at 14 months
2. Severe clinical malaria at 14 months
3. Parasite infection at 20 months

Loci

CSP regions

1. TEP
2. CST3
3. Th2R (17 residues in length, starts at site 311)
4. Th3R (12 residues in length, starts at site 352)
5. Unnamed (12 residues in length, starts at site 294)
6. Th2R+Th3R Linkage

CSP repeats

7. BEP

Control regions

8. SERA2
9. TRAP

Study sites

Major sites

1. Agogo, Gabon, West Africa (41092)
2. Kintampo, Ghana, West Africa (41089)
3. Kombewa, Kenya, East Africa (41108)
4. Nanoro, Burkina Faso, West Africa (53530)
5. Siaya, Kenya, East Africa (53598)

Minor sites

6. Bagamoyo, Tanzania, East Africa (41106)
7. Kilifi, Kenya, East Africa (41104)
8. Korogwe, Tanzania, East Africa (41107)
9. Lambarene, Gabon, West Africa (41087)
10. Lilongwe, Malawi, East Africa (53597)
11. Manhica, Mozambique, East Africa (41105)

Data prep

Marks data

The haplotype data files from the Broad are:

qdata/sequences/BEP.tsv
qdata/sequences/CST3.tsv
qdata/sequences/SERA2.tsv
qdata/sequences/TEP.tsv
qdata/sequences/Th2R_Th3R.tsv
qdata/sequences/Th2R.tsv
qdata/sequences/Th3R.tsv
qdata/sequences/TRAP.tsv
qdata/sequences/Unnamed.tsv

Necessary clinical data is at:

qdata/clinical/sample_data.tsv
adata/RTSSclinicalData.csv

Together, these are compiled to:

adata/marks_data_c.tsv
adata/marks_data_x.tsv

with

python scripts/prep-genotype-data.py C > adata/marks_data_c.tsv
python scripts/prep-genotype-data.py X > adata/marks_data_x.tsv

Site-specific marks data

Amended sequence data files are generated with:

python scripts/append-site-specific-match.py TEP > qdata/sequences/TEP_sites.tsv
python scripts/append-site-specific-match.py SERA2 > qdata/sequences/SERA2_sites.tsv

And site-specific mark files are then generated with:

python scripts/prep-genotype-data-sites.py C > adata/marks_data_c_sites.tsv
python scripts/prep-genotype-data-sites.py X > adata/marks_data_x_sites.tsv

Descriptive statistics of genotype data

• Code for genotype analysis

Compile to Markdown in R with:

library(knitr)
knit("descriptive-analysis.Rmd")

• Results of genotype analysis

Compile to LaTeX with:

pandoc -s descriptive-analysis.md -o descriptive-analysis.tex

And add \usepackage{morefloats} to the LaTeX header and grep for .png to .pdf.

Compile to PDF with:

pdflatex descriptive-analysis