diff --git a/analysis/03_process_geoff.R b/analysis/03_process_geoff.R
index f29557c..b021081 100644
--- a/analysis/03_process_geoff.R
+++ b/analysis/03_process_geoff.R
@@ -28,6 +28,11 @@ library(writexl)
 study_folders <- list.dirs(here("analysis", "data-geoff"), recursive = FALSE) |>
   basename()
 
+# skip over some folders, where STAVE format was extracted directly
+study_folders <- setdiff(study_folders, c("s231_ali_2022_v01",
+                                          "s232_wamae_2022_v01",
+                                          "s233_issa_2022_v01"))
+
 # read k13 dictionary and filter to target mutations
 k13_dictionary <- read.csv(here("analysis", "data-raw", "k13_ref_protein_codon_dictionary.csv")) |>
   filter(!is.na(WHO_TARGET))
diff --git a/analysis/11_merge_stave.R b/analysis/11_merge_stave.R
index d414164..22cde27 100644
--- a/analysis/11_merge_stave.R
+++ b/analysis/11_merge_stave.R
@@ -51,7 +51,7 @@ s$append_data(studies_dataframe = s_pf8$get_studies(),
               counts_dataframe = s_pf8$get_counts())
 
 # save combined object to file
-saveRDS(s, file = here("analysis", "data-out", "stave_data_2026.03.08.rds"))
+saveRDS(s, file = here("analysis", "data-out", "stave_data_2026.03.13.rds"))
 
 # ------------------------------------------------------------------
 # Some basic stats on the final object
diff --git a/analysis/12_plot_samples.R b/analysis/12_plot_samples.R
new file mode 100644
index 0000000..d335210
--- /dev/null
+++ b/analysis/12_plot_samples.R
@@ -0,0 +1,97 @@
+# plot_sample_collection.R
+#
+# Author: Bob Verity
+# Date: 2025-12-22
+#
+# Inputs:
+# data-out/stave_data_ ... .rds
+#
+# Outputs:
+# plots/sample_collection.pdf 
+#
+# Purpose:
+# (this is an example header)
+#
+# ------------------------------------------------------------------
+library(tidyverse)
+library(here)
+library(STAVE)
+
+# read in combined STAVE object
+s <- readRDS(here("analysis", "data-out", "stave_data_2026.03.08.rds"))
+
+# get WHO positions
+k13_dictionary <- read.csv(here("analysis", "data-raw", "k13_ref_protein_codon_dictionary.csv")) |>
+  filter(!is.na(WHO_TARGET)) |>
+  mutate(WT_variant = sprintf("k13:%s:%s", CODON, REF))
+
+# get prevalence (of WT) over all positions
+l <- list()
+for (i in 1:nrow(k13_dictionary)) {
+  message(sprintf("%s of %s", i, nrow(k13_dictionary)))
+  l[[i]] <- s$get_prevalence(k13_dictionary$WT_variant[i]) |>
+    select(study_id, survey_id, collection_day, denominator) |>
+    mutate(target_variant = k13_dictionary$WT_variant[i],
+           collection_year = year(collection_day))
+}
+
+# also get prevalence of PD
+l[[22]] <- s$get_prevalence("crt:76:T") |>
+  select(study_id, survey_id, collection_day, denominator) |>
+  mutate(target_variant = "crt:76:T",
+         collection_year = year(collection_day))
+l[[23]] <- s$get_prevalence("mdr1:86:Y") |>
+  select(study_id, survey_id, collection_day, denominator) |>
+  mutate(target_variant = "crt:86:Y",
+         collection_year = year(collection_day))
+
+df_l <- bind_rows(l)
+
+# find max denominator over all markers
+df_comb <- df_l |>
+  group_by(study_id, survey_id, collection_year) |>
+  summarise(denom_max = max(denominator))
+
+sum(df_comb$denom_max)
+
+# ------------------------------------------------------------------------
+# Plot samples collected over time
+
+augmented_list <- c("s0002_ayelaw_eth2023",
+                    "s0003_gidey_eth2022",
+                    "s0006_WRAIR_kenread_ken",
+                    "s0007_connelly_2024_zim",
+                    "s0008_MSMT_TZA_22_23",
+                    "s0010_karamoko_mgem_unpub",
+                    "s0011_jacques-mari_gmms_unpub",
+                    "s0021_roh_2023",
+                    "s0063_ngasala_2024",
+                    "s0074_lepiscopia_2025",
+                    "s0075_eloff_2025")
+
+mutate(bind_rows(l[1:21]), target_variant = "k13") |>
+  bind_rows(mutate(l[[22]], target_variant = "crt 76")) |>
+  bind_rows(mutate(l[[23]], target_variant = "mdr1 86")) |>
+  group_by(study_id, survey_id, collection_year, target_variant) |>
+  summarise(denom_max = max(denominator)) |>
+  mutate(source = ifelse(grepl("^WWARN_", study_id), "WWARN",
+                  ifelse(grepl("^WHO_", study_id), "WHO MTM",
+                  ifelse(grepl("^MalariaGEN_", study_id), "MalariaGen Pf8",
+                  ifelse(study_id %in% augmented_list, "Augmented datasets", "PRISMA review")))),
+         source = factor(source, levels = c("PRISMA review", "Augmented datasets",
+                                            "WWARN", "WHO MTM", "MalariaGen Pf8"))) |>
+  group_by(collection_year, source, target_variant) |>
+  summarise(n = sum(denom_max)) |>
+  mutate(target_variant = factor(target_variant, levels = c("crt 76", "mdr1 86", "k13"))) |>
+  ggplot() + theme_bw() +
+  geom_col(aes(x = collection_year, y = n, fill = source)) +
+  labs(x = "Collection Year", y = "Samples Sequenced",
+       fill = "Data Source") +
+  facet_wrap(~target_variant) +
+  theme(legend.position = "bottom")
+
+# save to file
+ggsave(filename = here("analysis", "plots", "sample_collection.pdf"),
+       width = 8, height = 4)
+       
+
diff --git a/analysis/data-derived/geoff_to_k13_coverage.csv b/analysis/data-derived/geoff_to_k13_coverage.csv
index da57be9..6efc3cb 100644
--- a/analysis/data-derived/geoff_to_k13_coverage.csv
+++ b/analysis/data-derived/geoff_to_k13_coverage.csv
@@ -13,7 +13,6 @@
 "s0013_MSMT_TZA_21_v01",1,726,"k13:441_446_449_458_469_476_481_493_515_527_537_538_539_543_553_561_568_574_580_622_675:PFGNCMAYRPNGRIPRVPCRA"
 "s0014_young_rwa_unpub_v01",1,726,"k13:441_446_449_458_469_476_481_493_515_527_537_538_539_543_553_561_568_574_580_622_675:PFGNCMAYRPNGRIPRVPCRA"
 "s0016_connelly_2024_elife_v01",1,726,"k13:441_446_449_458_469_476_481_493_515_527_537_538_539_543_553_561_568_574_580_622_675:PFGNCMAYRPNGRIPRVPCRA"
-"s0017_moser_mol_ecol_v01",1,726,"k13:441_446_449_458_469_476_481_493_515_527_537_538_539_543_553_561_568_574_580_622_675:PFGNCMAYRPNGRIPRVPCRA"
 "s0019a_conrad_v01",1,726,"k13:441_446_449_458_469_476_481_493_515_527_537_538_539_543_553_561_568_574_580_622_675:PFGNCMAYRPNGRIPRVPCRA"
 "s0020_some_2024_v01",1,726,"k13:441_446_449_458_469_476_481_493_515_527_537_538_539_543_553_561_568_574_580_622_675:PFGNCMAYRPNGRIPRVPCRA"
 "s0021_roh_2023_v01",1,726,"k13:441_446_449_458_469_476_481_493_515_527_537_538_539_543_553_561_568_574_580_622_675:PFGNCMAYRPNGRIPRVPCRA"
@@ -22,32 +21,18 @@
 "s0024_fola_2023_zambiamalj_v01",1,726,"k13:441_446_449_458_469_476_481_493_515_527_537_538_539_543_553_561_568_574_580_622_675:PFGNCMAYRPNGRIPRVPCRA"
 "s0025_ogwang_aac_v01",427,709,"k13:441_446_449_458_469_476_481_493_515_527_537_538_539_543_553_561_568_574_580_622_675:PFGNCMAYRPNGRIPRVPCRA"
 "s0026_verity_v01",1,726,"k13:441_446_449_458_469_476_481_493_515_527_537_538_539_543_553_561_568_574_580_622_675:PFGNCMAYRPNGRIPRVPCRA"
-"s0027_bayih_ajtmh_v01",427,709,"k13:441_446_449_458_469_476_481_493_515_527_537_538_539_543_553_561_568_574_580_622_675:PFGNCMAYRPNGRIPRVPCRA"
 "s0028_alemayehu_v01",427,709,"k13:441_446_449_458_469_476_481_493_515_527_537_538_539_543_553_561_568_574_580_622_675:PFGNCMAYRPNGRIPRVPCRA"
-"s0029_warsame_2019_v01",427,709,"k13:441_446_449_458_469_476_481_493_515_527_537_538_539_543_553_561_568_574_580_622_675:PFGNCMAYRPNGRIPRVPCRA"
-"s0030_uwimana_rwa_2014_v01",440,600,"k13:441_446_449_458_469_476_481_493_515_527_537_538_539_543_553_561_568_574_580:PFGNCMAYRPNGRIPRVPC"
-"s0031_bergmann_2021_v01",469,581,"k13:469_476_481_493_515_527_537_538_539_543_553_561_568_574_580:CMAYRPNGRIPRVPC"
-"s0032_tacoli_v01",440,726,"k13:441_446_449_458_469_476_481_493_515_527_537_538_539_543_553_561_568_574_580_622_675:PFGNCMAYRPNGRIPRVPCRA"
-"s0033_straimer_v01",440,726,"k13:441_446_449_458_469_476_481_493_515_527_537_538_539_543_553_561_568_574_580_622_675:PFGNCMAYRPNGRIPRVPCRA"
-"s0034_uwimana_v01",442,727,"k13:446_449_458_469_476_481_493_515_527_537_538_539_543_553_561_568_574_580_622_675:FGNCMAYRPNGRIPRVPCRA"
 "s0035_kirby_v01",516,572,"k13:527_537_538_539_543_553_561_568:PNGRIPRV"
 "s0036_schreidah_v01",1,726,"k13:441_446_449_458_469_476_481_493_515_527_537_538_539_543_553_561_568_574_580_622_675:PFGNCMAYRPNGRIPRVPCRA"
-"s0039_yobi_2020_plosone_v01",427,595,"k13:441_446_449_458_469_476_481_493_515_527_537_538_539_543_553_561_568_574_580:PFGNCMAYRPNGRIPRVPC"
-"s0040_mvumbi_2017_plosone_v01",427,709,"k13:441_446_449_458_469_476_481_493_515_527_537_538_539_543_553_561_568_574_580_622_675:PFGNCMAYRPNGRIPRVPCRA"
-"s0041_yobi_2022_v01",427,595,"k13:441_446_449_458_469_476_481_493_515_527_537_538_539_543_553_561_568_574_580:PFGNCMAYRPNGRIPRVPC"
 "s0042_mesiakahunu_v01",396,698,"k13:441_446_449_458_469_476_481_493_515_527_537_538_539_543_553_561_568_574_580_622_675:PFGNCMAYRPNGRIPRVPCRA"
 "s0043_vanloon_v01",469,581,"k13:469_476_481_493_515_527_537_538_539_543_553_561_568_574_580:CMAYRPNGRIPRVPC"
 "s0045_bakari_v01",430,726,"k13:441_446_449_458_469_476_481_493_515_527_537_538_539_543_553_561_568_574_580_622_675:PFGNCMAYRPNGRIPRVPCRA"
-"s0046_bwire_v01",354,666,"k13:441_446_449_458_469_476_481_493_515_527_537_538_539_543_553_561_568_574_580_622:PFGNCMAYRPNGRIPRVPCR"
-"s0047_balikagala_v01",469,708,"k13:469_476_481_493_515_527_537_538_539_543_553_561_568_574_580_622_675:CMAYRPNGRIPRVPCRA"
 "s0048_vanloon_v01",469,581,"k13:469_476_481_493_515_527_537_538_539_543_553_561_568_574_580:CMAYRPNGRIPRVPC"
 "s0049_plucinski_v01",1,726,"k13:441_446_449_458_469_476_481_493_515_527_537_538_539_543_553_561_568_574_580_622_675:PFGNCMAYRPNGRIPRVPCRA"
 "s0050_davlantes_v01",440,680,"k13:441_446_449_458_469_476_481_493_515_527_537_538_539_543_553_561_568_574_580_622_675:PFGNCMAYRPNGRIPRVPCRA"
-"s0052_ljolje_v01",440,726,"k13:441_446_449_458_469_476_481_493_515_527_537_538_539_543_553_561_568_574_580_622_675:PFGNCMAYRPNGRIPRVPCRA"
 "s0053_issa_v01",430,720,"k13:441_446_449_458_469_476_481_493_515_527_537_538_539_543_553_561_568_574_580_622_675:PFGNCMAYRPNGRIPRVPCRA"
 "s0054_laminou_v01",440,720,"k13:441_446_449_458_469_476_481_493_515_527_537_538_539_543_553_561_568_574_580_622_675:PFGNCMAYRPNGRIPRVPCRA"
 "s0055_dorkenoo_v01",430,720,"k13:441_446_449_458_469_476_481_493_515_527_537_538_539_543_553_561_568_574_580_622_675:PFGNCMAYRPNGRIPRVPCRA"
-"s0057_koko_v01",440,680,"k13:441_446_449_458_469_476_481_493_515_527_537_538_539_543_553_561_568_574_580_622_675:PFGNCMAYRPNGRIPRVPCRA"
 "s0059_osborne_v01",1,726,"k13:441_446_449_458_469_476_481_493_515_527_537_538_539_543_553_561_568_574_580_622_675:PFGNCMAYRPNGRIPRVPCRA"
 "s0060_angwe_2024_v01",445,727,"k13:446_449_458_469_476_481_493_515_527_537_538_539_543_553_561_568_574_580_622_675:FGNCMAYRPNGRIPRVPCRA"
 "s0061_kamaliddin_2024_v01",434,702,"k13:441_446_449_458_469_476_481_493_515_527_537_538_539_543_553_561_568_574_580_622_675:PFGNCMAYRPNGRIPRVPCRA"
@@ -56,8 +41,6 @@
 "s0065_ndiaye_v01",578,580,"k13:580:C"
 "s0067_makenga_2022_v01",442,726,"k13:446_449_458_469_476_481_493_515_527_537_538_539_543_553_561_568_574_580_622_675:FGNCMAYRPNGRIPRVPCRA"
 "s0068_dasilva_2023_v01",412,723,"k13:441_446_449_458_469_476_481_493_515_527_537_538_539_543_553_561_568_574_580_622_675:PFGNCMAYRPNGRIPRVPCRA"
-"s0069_matrevi_2019_v01",430,699,"k13:441_446_449_458_469_476_481_493_515_527_537_538_539_543_553_561_568_574_580_622_675:PFGNCMAYRPNGRIPRVPCRA"
-"s0070_hamid_2019_v01",427,709,"k13:441_446_449_458_469_476_481_493_515_527_537_538_539_543_553_561_568_574_580_622_675:PFGNCMAYRPNGRIPRVPCRA"
 "s0071_mohammed_sdn_2018_v01",NA,NA,NA
 "s0072_makau_ken_2024_v01",441,726,"k13:441_446_449_458_469_476_481_493_515_527_537_538_539_543_553_561_568_574_580_622_675:PFGNCMAYRPNGRIPRVPCRA"
 "s0073_agaba_uga_2024_v01",427,709,"k13:441_446_449_458_469_476_481_493_515_527_537_538_539_543_553_561_568_574_580_622_675:PFGNCMAYRPNGRIPRVPCRA"
@@ -126,7 +109,6 @@
 "s0184_mulenga_2021_v01",NA,NA,NA
 "s0186_holzschuh_2023_v01",481,543,"k13:481_493_515_527_537_538_539_543:AYRPNGRI"
 "s0189_kagoro_2022_v01",430,729,"k13:441_446_449_458_469_476_481_493_515_527_537_538_539_543_553_561_568_574_580_622_675:PFGNCMAYRPNGRIPRVPCRA"
-"s0191_mbacham_2010_v01",NA,NA,NA
 "s0192_coonahan_2023_v01",440,726,"k13:441_446_449_458_469_476_481_493_515_527_537_538_539_543_553_561_568_574_580_622_675:PFGNCMAYRPNGRIPRVPCRA"
 "s0193_awor_2024_v01",1,726,"k13:441_446_449_458_469_476_481_493_515_527_537_538_539_543_553_561_568_574_580_622_675:PFGNCMAYRPNGRIPRVPCRA"
 "s0194_kassaza_2021_v01",NA,NA,NA
@@ -138,7 +120,6 @@
 "s216_milongmelong_2025_v01",427,709,"k13:441_446_449_458_469_476_481_493_515_527_537_538_539_543_553_561_568_574_580_622_675:PFGNCMAYRPNGRIPRVPCRA"
 "s219_amusan_2024_v01",NA,NA,NA
 "s220_onyamboko_2025_v01",440,727,"k13:441_446_449_458_469_476_481_493_515_527_537_538_539_543_553_561_568_574_580_622_675:PFGNCMAYRPNGRIPRVPCRA"
-"s221_joao_2025_v01",11,691,"k13:441_446_449_458_469_476_481_493_515_527_537_538_539_543_553_561_568_574_580_622_675:PFGNCMAYRPNGRIPRVPCRA"
 "s222_nuwa_2025_v01",469,675,"k13:469_476_481_493_515_527_537_538_539_543_553_561_568_574_580_622_675:CMAYRPNGRIPRVPCRA"
 "s223_kimani_2025_v01",432,702,"k13:441_446_449_458_469_476_481_493_515_527_537_538_539_543_553_561_568_574_580_622_675:PFGNCMAYRPNGRIPRVPCRA"
 "s224_nyamngee_2025_v01",NA,NA,NA
@@ -147,3 +128,6 @@
 "s228_vanloon_2025_v01",426,709,"k13:441_446_449_458_469_476_481_493_515_527_537_538_539_543_553_561_568_574_580_622_675:PFGNCMAYRPNGRIPRVPCRA"
 "s229_adika_2025_v01",440,680,"k13:441_446_449_458_469_476_481_493_515_527_537_538_539_543_553_561_568_574_580_622_675:PFGNCMAYRPNGRIPRVPCRA"
 "s230_mihreteab_2025_v01",435,680,"k13:441_446_449_458_469_476_481_493_515_527_537_538_539_543_553_561_568_574_580_622_675:PFGNCMAYRPNGRIPRVPCRA"
+"s231_ali_2022_v01",NA,NA,NA
+"s232_wamae_2022_v01",NA,NA,NA
+"s233_issa_2022_v01",NA,NA,NA
diff --git a/analysis/data-geoff/s0002_ayelaw_eth2023_v01/s0002_ayelaw_eth2023_v01_STAVE_imputed.xlsx b/analysis/data-geoff/s0002_ayelaw_eth2023_v01/s0002_ayelaw_eth2023_v01_STAVE_imputed.xlsx
index d7d1d3b..6c2e9de 100644
Binary files a/analysis/data-geoff/s0002_ayelaw_eth2023_v01/s0002_ayelaw_eth2023_v01_STAVE_imputed.xlsx and b/analysis/data-geoff/s0002_ayelaw_eth2023_v01/s0002_ayelaw_eth2023_v01_STAVE_imputed.xlsx differ
diff --git a/analysis/data-geoff/s0003_gidey_eth2022_v01/s0003_gidey_eth2022_v01_STAVE_imputed.xlsx b/analysis/data-geoff/s0003_gidey_eth2022_v01/s0003_gidey_eth2022_v01_STAVE_imputed.xlsx
index c115759..20b2456 100644
Binary files a/analysis/data-geoff/s0003_gidey_eth2022_v01/s0003_gidey_eth2022_v01_STAVE_imputed.xlsx and b/analysis/data-geoff/s0003_gidey_eth2022_v01/s0003_gidey_eth2022_v01_STAVE_imputed.xlsx differ
diff --git a/analysis/data-geoff/s0004_fola_eth_622i_v01/s0004_fola_eth_622i_v01_STAVE_imputed.xlsx b/analysis/data-geoff/s0004_fola_eth_622i_v01/s0004_fola_eth_622i_v01_STAVE_imputed.xlsx
index a3909c2..10cbf68 100644
Binary files a/analysis/data-geoff/s0004_fola_eth_622i_v01/s0004_fola_eth_622i_v01_STAVE_imputed.xlsx and b/analysis/data-geoff/s0004_fola_eth_622i_v01/s0004_fola_eth_622i_v01_STAVE_imputed.xlsx differ
diff --git a/analysis/data-geoff/s0005_mihreteab_eritrea_622i_v01/s0005_mihreteab_eritrea_622i_v01_STAVE_imputed.xlsx b/analysis/data-geoff/s0005_mihreteab_eritrea_622i_v01/s0005_mihreteab_eritrea_622i_v01_STAVE_imputed.xlsx
index 73f0227..5d33e46 100644
Binary files a/analysis/data-geoff/s0005_mihreteab_eritrea_622i_v01/s0005_mihreteab_eritrea_622i_v01_STAVE_imputed.xlsx and b/analysis/data-geoff/s0005_mihreteab_eritrea_622i_v01/s0005_mihreteab_eritrea_622i_v01_STAVE_imputed.xlsx differ
diff --git a/analysis/data-geoff/s0006_WRAIR_kenread_ken_v01/s0006_WRAIR_kenread_ken_v01_STAVE_imputed.xlsx b/analysis/data-geoff/s0006_WRAIR_kenread_ken_v01/s0006_WRAIR_kenread_ken_v01_STAVE_imputed.xlsx
index 00bb56a..adcc52d 100644
Binary files a/analysis/data-geoff/s0006_WRAIR_kenread_ken_v01/s0006_WRAIR_kenread_ken_v01_STAVE_imputed.xlsx and b/analysis/data-geoff/s0006_WRAIR_kenread_ken_v01/s0006_WRAIR_kenread_ken_v01_STAVE_imputed.xlsx differ
diff --git a/analysis/data-geoff/s0007_connelly_2024_zim_v01/s0007_connelly_2024_zim_v01_STAVE_imputed.xlsx b/analysis/data-geoff/s0007_connelly_2024_zim_v01/s0007_connelly_2024_zim_v01_STAVE_imputed.xlsx
index a7c49e3..c7e8193 100644
Binary files a/analysis/data-geoff/s0007_connelly_2024_zim_v01/s0007_connelly_2024_zim_v01_STAVE_imputed.xlsx and b/analysis/data-geoff/s0007_connelly_2024_zim_v01/s0007_connelly_2024_zim_v01_STAVE_imputed.xlsx differ
diff --git a/analysis/data-geoff/s0008a_MSMT_TZA_22_v01/s0008a_MSMT_TZA_22_v01_STAVE_imputed.xlsx b/analysis/data-geoff/s0008a_MSMT_TZA_22_v01/s0008a_MSMT_TZA_22_v01_STAVE_imputed.xlsx
index 79e81d6..218abf3 100644
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