diff --git a/-biolpc3032.Rhistory b/-biolpc3032.Rhistory
deleted file mode 100644
index ec71367..0000000
--- a/-biolpc3032.Rhistory
+++ /dev/null
@@ -1,512 +0,0 @@
-group_by(treatment, replicate) |>
-arrange(treatment, replicate, time_day) |>
-mutate(acetate = acetate - lag(acetate),
-propanoate = propanoate - lag(propanoate),
-isobutyrate = isobutyrate - lag(isobutyrate),
-butyrate = butyrate - lag(butyrate),
-isopentanoate = isopentanoate - lag(isopentanoate),
-pentanoate = pentanoate - lag(pentanoate),
-isohexanoate = isohexanoate - lag(isohexanoate),
-hexanoate = hexanoate - lag(hexanoate),
-delta_time = time_day - lag(time_day))
-mol_wt <- read_table("data-raw/mol_wt.txt") |>
-mutate(vfa = tolower(vfa))
-vfa_cummul_protein <- vfa_cummul_protein |>
-pivot_longer(cols = -c(set_number,
-treatment,
-replicate,
-time_day),
-values_to = "conc_mM",
-names_to = "vfa")
-vfa_cummul_protein <- vfa_cummul_protein |>
-left_join(mol_wt, by = "vfa") |>
-mutate(conc_g_l = conc_mM * 0.001 * mw)
-vfa_delta_protein <- vfa_delta_protein |>
-pivot_longer(cols = -c(set_number,
-treatment,
-replicate,
-time_day),
-values_to = "conc_mM",
-names_to = "vfa")
-vfa_delta_protein <- vfa_delta_protein |>
-left_join(mol_wt, by = "vfa") |>
-mutate(conc_g_l = conc_mM * 0.001 * mw)
-vfa_cummul_protein <- vfa_cummul |>
-filter(set_number == 1) |>
-select(-set_number)
-vfa_cummul_vfa <- vfa_cummul |>
-filter(set_number == 2) |>
-select(-set_number)
-vfa_delta_protein <- vfa_cummul_protein |>
-group_by(treatment, replicate) |>
-arrange(treatment, replicate, time_day) |>
-mutate(acetate = acetate - lag(acetate),
-propanoate = propanoate - lag(propanoate),
-isobutyrate = isobutyrate - lag(isobutyrate),
-butyrate = butyrate - lag(butyrate),
-isopentanoate = isopentanoate - lag(isopentanoate),
-pentanoate = pentanoate - lag(pentanoate),
-isohexanoate = isohexanoate - lag(isohexanoate),
-hexanoate = hexanoate - lag(hexanoate),
-delta_time = time_day - lag(time_day))
-mol_wt <- read_table("data-raw/mol_wt.txt") |>
-mutate(vfa = tolower(vfa))
-vfa_cummul_protein <- vfa_cummul_protein |>
-pivot_longer(cols = -c(treatment,
-replicate,
-time_day),
-values_to = "conc_mM",
-names_to = "vfa")
-vfa_cummul_protein <- vfa_cummul_protein |>
-left_join(mol_wt, by = "vfa") |>
-mutate(conc_g_l = conc_mM * 0.001 * mw)
-vfa_delta_protein <- vfa_delta_protein |>
-pivot_longer(cols = -c(treatment,
-replicate,
-time_day),
-values_to = "conc_mM",
-names_to = "vfa")
-vfa_delta_protein <- vfa_delta_protein |>
-left_join(mol_wt, by = "vfa") |>
-mutate(conc_g_l = conc_mM * 0.001 * mw)
-vfa_cummul_protein <- vfa_cummul_protein |>
-group_by(treatment, replicate, time_day) |>
-mutate(percent_conc_g_l = conc_g_l / sum(conc_g_l) * 100,
-percent_conc_mM = conc_mM / sum(conc_mM) * 100)
-View(vfa_cummul_protein)
-vfa_cummul_protein_summary <- vfa_cummul_protein |>
-group_by(treatment, time_day, vfa) |>
-summarise(mean_g_l = mean(conc_g_l),
-se_g_l = sd(conc_g_l)/sqrt(length(conc_g_l)),
-mean_mM = mean(conc_mM),
-se_mM = sd(conc_mM)/sqrt(length(conc_mM))) |>
-ungroup()
-vfa_cummul_protein_summary <- vfa_cummul_protein |>
-group_by(treatment, time_day, vfa) |>
-summarise(mean_g_l = mean(conc_g_l),
-se_g_l = sd(conc_g_l)/sqrt(length(conc_g_l)),
-mean_mM = mean(conc_mM),
-se_mM = sd(conc_mM)/sqrt(length(conc_mM))) |>
-ungroup()
-View(vfa_cummul_protein_summary)
-vfa_delta_protein_summary <- vfa_delta_protein |>
-group_by(treatment, time_day, vfa) |>
-summarise(mean_g_l = mean(conc_g_l),
-se_g_l = sd(conc_g_l)/sqrt(length(conc_g_l)),
-mean_mM = mean(conc_mM),
-se_mM = sd(conc_mM)/sqrt(length(conc_mM))) |>
-ungroup()
-vfa_cummul_protein_summary |>
-ggplot(aes(x = time_day, colour = vfa)) +
-geom_line(aes(y = mean_g_l),
-linewidth = 1) +
-geom_errorbar(aes(ymin = mean_g_l - se_g_l,
-ymax = mean_g_l + se_g_l),
-width = 0.5,
-show.legend = F,
-linewidth = 1) +
-scale_color_viridis_d(name = NULL) +
-scale_x_continuous(name = "Time (days)") +
-scale_y_continuous(name = "Mean VFA concentration (g/l)") +
-theme_bw() +
-facet_wrap(~treatment) +
-theme(strip.background = element_blank())
-vfa_delta_protein_summary |>
-ggplot(aes(x = time_day, colour = vfa)) +
-geom_line(aes(y = mean_g_l),
-linewidth = 1) +
-geom_errorbar(aes(ymin = mean_g_l - se_g_l,
-ymax = mean_g_l + se_g_l),
-width = 0.5,
-show.legend = F,
-linewidth = 1) +
-scale_color_viridis_d(name = NULL) +
-scale_x_continuous(name = "Time (days)") +
-scale_y_continuous(name = "Mean change in VFA concentration (g/l)") +
-theme_bw() +
-facet_wrap(~treatment) +
-theme(strip.background = element_blank())
-vfa_cummul_protein_summary |>
-ggplot(aes(x = time_day, y = mean_g_l, fill = vfa)) +
-geom_col(position = "fill") +
-scale_fill_viridis_d(name = NULL) +
-scale_x_continuous(name = "Time (days)") +
-scale_y_continuous(name = "Mean Proportion VFA") +
-theme_bw() +
-facet_wrap(~treatment) +
-theme(strip.background = element_blank())
-vfa_delta_vfa <- vfa_cummul_vfa |>
-group_by(treatment, replicate) |>
-arrange(treatment, replicate, time_day) |>
-mutate(acetate = acetate - lag(acetate),
-propanoate = propanoate - lag(propanoate),
-isobutyrate = isobutyrate - lag(isobutyrate),
-butyrate = butyrate - lag(butyrate),
-isopentanoate = isopentanoate - lag(isopentanoate),
-pentanoate = pentanoate - lag(pentanoate),
-isohexanoate = isohexanoate - lag(isohexanoate),
-hexanoate = hexanoate - lag(hexanoate),
-delta_time = time_day - lag(time_day))
-vfa_cummul_vfa <- vfa_cummul_vfa |>
-pivot_longer(cols = -c(treatment,
-replicate,
-time_day),
-values_to = "conc_mM",
-names_to = "vfa")
-vfa_cummul_vfa <- vfa_cummul_vfa |>
-left_join(mol_wt, by = "vfa") |>
-mutate(conc_g_l = conc_mM * 0.001 * mw)
-vfa_delta_vfa <- vfa_delta_vfa |>
-pivot_longer(cols = -c(treatment,
-replicate,
-time_day),
-values_to = "conc_mM",
-names_to = "vfa")
-vfa_delta_vfa <- vfa_delta_vfa |>
-left_join(mol_wt, by = "vfa") |>
-mutate(conc_g_l = conc_mM * 0.001 * mw)
-vfa_cummul_vfa <- vfa_cummul_vfa |>
-group_by(treatment, replicate, time_day) |>
-mutate(percent_conc_g_l = conc_g_l / sum(conc_g_l) * 100,
-percent_conc_mM = conc_mM / sum(conc_mM) * 100)
-vfa_cummul_vfa_summary <- vfa_cummul_vfa |>
-group_by(treatment, time_day, vfa) |>
-summarise(mean_g_l = mean(conc_g_l),
-se_g_l = sd(conc_g_l)/sqrt(length(conc_g_l)),
-mean_mM = mean(conc_mM),
-se_mM = sd(conc_mM)/sqrt(length(conc_mM))) |>
-ungroup()
-vfa_delta_vfa_summary <- vfa_delta_vfa |>
-group_by(treatment, time_day, vfa) |>
-summarise(mean_g_l = mean(conc_g_l),
-se_g_l = sd(conc_g_l)/sqrt(length(conc_g_l)),
-mean_mM = mean(conc_mM),
-se_mM = sd(conc_mM)/sqrt(length(conc_mM))) |>
-ungroup()
-vfa_cummul_vfa_summary |>
-ggplot(aes(x = time_day, colour = vfa)) +
-geom_line(aes(y = mean_g_l),
-linewidth = 1) +
-geom_errorbar(aes(ymin = mean_g_l - se_g_l,
-ymax = mean_g_l + se_g_l),
-width = 0.5,
-show.legend = F,
-linewidth = 1) +
-scale_color_viridis_d(name = NULL) +
-scale_x_continuous(name = "Time (days)") +
-scale_y_continuous(name = "Mean VFA concentration (g/l)") +
-theme_bw() +
-facet_wrap(~treatment) +
-theme(strip.background = element_blank())
-vfa_delta_vfa_summary |>
-ggplot(aes(x = time_day, colour = vfa)) +
-geom_line(aes(y = mean_g_l),
-linewidth = 1) +
-geom_errorbar(aes(ymin = mean_g_l - se_g_l,
-ymax = mean_g_l + se_g_l),
-width = 0.5,
-show.legend = F,
-linewidth = 1) +
-scale_color_viridis_d(name = NULL) +
-scale_x_continuous(name = "Time (days)") +
-scale_y_continuous(name = "Mean change in VFA concentration (g/l)") +
-theme_bw() +
-facet_wrap(~treatment) +
-theme(strip.background = element_blank())
-vfa_cummul_vfa_summary |>
-ggplot(aes(x = time_day, y = mean_g_l, fill = vfa)) +
-geom_col(position = "fill") +
-scale_fill_viridis_d(name = NULL) +
-scale_x_continuous(name = "Time (days)") +
-scale_y_continuous(name = "Mean Proportion VFA") +
-theme_bw() +
-facet_wrap(~treatment) +
-theme(strip.background = element_blank())
-sludge_volume <- 30 # ml
-vfa_delta_protein <- vfa_delta_protein |>
-mutate(flux = conc_g_l / delta_time / sludge_volume)
-vfa_delta_protein <- vfa_cummul_protein |>
-group_by(treatment, replicate) |>
-arrange(treatment, replicate, time_day) |>
-mutate(acetate = acetate - lag(acetate),
-propanoate = propanoate - lag(propanoate),
-isobutyrate = isobutyrate - lag(isobutyrate),
-butyrate = butyrate - lag(butyrate),
-isopentanoate = isopentanoate - lag(isopentanoate),
-pentanoate = pentanoate - lag(pentanoate),
-isohexanoate = isohexanoate - lag(isohexanoate),
-hexanoate = hexanoate - lag(hexanoate),
-delta_time = time_day - lag(time_day))
-vfa_cummul <- read_csv("data-raw/vfa2.csv") |> janitor::clean_names()
-vfa_cummul_protein <- vfa_cummul |>
-filter(set_number == 1) |>
-select(-set_number)
-vfa_cummul_vfa <- vfa_cummul |>
-filter(set_number == 2) |>
-select(-set_number)
-mol_wt <- read_table("data-raw/mol_wt.txt") |>
-mutate(vfa = tolower(vfa))
-vfa_delta_protein <- vfa_cummul_protein |>
-group_by(treatment, replicate) |>
-arrange(treatment, replicate, time_day) |>
-mutate(acetate = acetate - lag(acetate),
-propanoate = propanoate - lag(propanoate),
-isobutyrate = isobutyrate - lag(isobutyrate),
-butyrate = butyrate - lag(butyrate),
-isopentanoate = isopentanoate - lag(isopentanoate),
-pentanoate = pentanoate - lag(pentanoate),
-isohexanoate = isohexanoate - lag(isohexanoate),
-hexanoate = hexanoate - lag(hexanoate),
-delta_time = time_day - lag(time_day))
-vfa_cummul_protein <- vfa_cummul_protein |>
-pivot_longer(cols = -c(treatment,
-replicate,
-time_day),
-values_to = "conc_mM",
-names_to = "vfa")
-vfa_cummul_protein <- vfa_cummul_protein |>
-left_join(mol_wt, by = "vfa") |>
-mutate(conc_g_l = conc_mM * 0.001 * mw)
-vfa_delta_protein <- vfa_delta_protein |>
-pivot_longer(cols = -c(treatment,
-replicate,
-time_day,
-delta_time),
-values_to = "conc_mM",
-names_to = "vfa")
-vfa_delta_protein <- vfa_delta_protein |>
-left_join(mol_wt, by = "vfa") |>
-mutate(conc_g_l = conc_mM * 0.001 * mw)
-vfa_cummul_protein <- vfa_cummul_protein |>
-group_by(treatment, replicate, time_day) |>
-mutate(percent_conc_g_l = conc_g_l / sum(conc_g_l) * 100,
-percent_conc_mM = conc_mM / sum(conc_mM) * 100)
-vfa_cummul_protein_summary <- vfa_cummul_protein |>
-group_by(treatment, time_day, vfa) |>
-summarise(mean_g_l = mean(conc_g_l),
-se_g_l = sd(conc_g_l)/sqrt(length(conc_g_l)),
-mean_mM = mean(conc_mM),
-se_mM = sd(conc_mM)/sqrt(length(conc_mM))) |>
-ungroup()
-vfa_delta_protein_summary <- vfa_delta_protein |>
-group_by(treatment, time_day, vfa) |>
-summarise(mean_g_l = mean(conc_g_l),
-se_g_l = sd(conc_g_l)/sqrt(length(conc_g_l)),
-mean_mM = mean(conc_mM),
-se_mM = sd(conc_mM)/sqrt(length(conc_mM))) |>
-ungroup()
-vfa_cummul_protein_summary |>
-ggplot(aes(x = time_day, colour = vfa)) +
-geom_line(aes(y = mean_g_l),
-linewidth = 1) +
-geom_errorbar(aes(ymin = mean_g_l - se_g_l,
-ymax = mean_g_l + se_g_l),
-width = 0.5,
-show.legend = F,
-linewidth = 1) +
-scale_color_viridis_d(name = NULL) +
-scale_x_continuous(name = "Time (days)") +
-scale_y_continuous(name = "Mean VFA concentration (g/l)") +
-theme_bw() +
-facet_wrap(~treatment) +
-theme(strip.background = element_blank())
-vfa_delta_protein_summary |>
-ggplot(aes(x = time_day, colour = vfa)) +
-geom_line(aes(y = mean_g_l),
-linewidth = 1) +
-geom_errorbar(aes(ymin = mean_g_l - se_g_l,
-ymax = mean_g_l + se_g_l),
-width = 0.5,
-show.legend = F,
-linewidth = 1) +
-scale_color_viridis_d(name = NULL) +
-scale_x_continuous(name = "Time (days)") +
-scale_y_continuous(name = "Mean change in VFA concentration (g/l)") +
-theme_bw() +
-facet_wrap(~treatment) +
-theme(strip.background = element_blank())
-vfa_cummul_protein_summary |>
-ggplot(aes(x = time_day, y = mean_g_l, fill = vfa)) +
-geom_col(position = "fill") +
-scale_fill_viridis_d(name = NULL) +
-scale_x_continuous(name = "Time (days)") +
-scale_y_continuous(name = "Mean Proportion VFA") +
-theme_bw() +
-facet_wrap(~treatment) +
-theme(strip.background = element_blank())
-sludge_volume <- 30 # ml
-vfa_delta_protein <- vfa_delta_protein |>
-mutate(flux = conc_g_l / delta_time / sludge_volume)
-View(vfa_delta_protein)
-vfa_delta_protein_summary <- vfa_delta_protein |>
-group_by(treatment, time_day, vfa) |>
-summarise(mean_flux = mean(flux),
-se_flux = sd(flux)/sqrt(length(flux))) |>
-ungroup()
-ggplot(data = vfa_delta_protein, aes(x = time_day, colour = vfa)) +
-geom_point(aes(y = flux), alpha = 0.6) +
-geom_errorbar(data = vfa_delta_protein_summary,
-aes(ymin = mean_flux - se_flux,
-ymax = mean_flux + se_flux),
-width = 1) +
-geom_errorbar(data = vfa_delta_protein_summary,
-aes(ymin = mean_flux,
-ymax = mean_flux),
-width = 0.8) +
-scale_color_viridis_d(name = NULL) +
-scale_x_continuous(name = "Time (days)") +
-scale_y_continuous(name = "VFA Flux mg/ml/day") +
-theme_bw() +
-facet_wrap(~treatment) +
-theme(strip.background = element_blank())
-ggplot(data = vfa_delta_protein, aes(x = time_day, colour = treatment)) +
-geom_point(aes(y = flux), alpha = 0.6) +
-geom_errorbar(data = vfa_delta_protein_summary,
-aes(ymin = mean_flux - se_flux,
-ymax = mean_flux + se_flux),
-width = 1) +
-geom_errorbar(data = vfa_delta_protein_summary,
-aes(ymin = mean_flux,
-ymax = mean_flux),
-width = 0.8) +
-scale_color_viridis_d(name = NULL, begin = 0.2, end = 0.7) +
-scale_x_continuous(name = "Time (days)") +
-scale_y_continuous(name = "VFA Flux mg/ml/day") +
-theme_bw() +
-facet_wrap(~ vfa, nrow = 2) +
-theme(strip.background = element_blank(),
-legend.position = "top")
-vfa_delta_vfa <- vfa_cummul_vfa |>
-group_by(treatment, replicate) |>
-arrange(treatment, replicate, time_day) |>
-mutate(acetate = acetate - lag(acetate),
-propanoate = propanoate - lag(propanoate),
-isobutyrate = isobutyrate - lag(isobutyrate),
-butyrate = butyrate - lag(butyrate),
-isopentanoate = isopentanoate - lag(isopentanoate),
-pentanoate = pentanoate - lag(pentanoate),
-isohexanoate = isohexanoate - lag(isohexanoate),
-hexanoate = hexanoate - lag(hexanoate),
-delta_time = time_day - lag(time_day))
-vfa_cummul_vfa <- vfa_cummul_vfa |>
-pivot_longer(cols = -c(treatment,
-replicate,
-time_day),
-values_to = "conc_mM",
-names_to = "vfa")
-vfa_cummul_vfa <- vfa_cummul_vfa |>
-left_join(mol_wt, by = "vfa") |>
-mutate(conc_g_l = conc_mM * 0.001 * mw)
-vfa_delta_vfa <- vfa_delta_vfa |>
-pivot_longer(cols = -c(treatment,
-replicate,
-time_day,
-delta_time),
-values_to = "conc_mM",
-names_to = "vfa")
-vfa_delta_vfa <- vfa_delta_vfa |>
-left_join(mol_wt, by = "vfa") |>
-mutate(conc_g_l = conc_mM * 0.001 * mw)
-vfa_cummul_vfa <- vfa_cummul_vfa |>
-group_by(treatment, replicate, time_day) |>
-mutate(percent_conc_g_l = conc_g_l / sum(conc_g_l) * 100,
-percent_conc_mM = conc_mM / sum(conc_mM) * 100)
-vfa_cummul_vfa_summary <- vfa_cummul_vfa |>
-group_by(treatment, time_day, vfa) |>
-summarise(mean_g_l = mean(conc_g_l),
-se_g_l = sd(conc_g_l)/sqrt(length(conc_g_l)),
-mean_mM = mean(conc_mM),
-se_mM = sd(conc_mM)/sqrt(length(conc_mM))) |>
-ungroup()
-vfa_delta_vfa_summary <- vfa_delta_vfa |>
-group_by(treatment, time_day, vfa) |>
-summarise(mean_g_l = mean(conc_g_l),
-se_g_l = sd(conc_g_l)/sqrt(length(conc_g_l)),
-mean_mM = mean(conc_mM),
-se_mM = sd(conc_mM)/sqrt(length(conc_mM))) |>
-ungroup()
-vfa_cummul_vfa_summary |>
-ggplot(aes(x = time_day, colour = vfa)) +
-geom_line(aes(y = mean_g_l),
-linewidth = 1) +
-geom_errorbar(aes(ymin = mean_g_l - se_g_l,
-ymax = mean_g_l + se_g_l),
-width = 0.5,
-show.legend = F,
-linewidth = 1) +
-scale_color_viridis_d(name = NULL) +
-scale_x_continuous(name = "Time (days)") +
-scale_y_continuous(name = "Mean VFA concentration (g/l)") +
-theme_bw() +
-facet_wrap(~treatment) +
-theme(strip.background = element_blank())
-vfa_delta_vfa_summary |>
-ggplot(aes(x = time_day, colour = vfa)) +
-geom_line(aes(y = mean_g_l),
-linewidth = 1) +
-geom_errorbar(aes(ymin = mean_g_l - se_g_l,
-ymax = mean_g_l + se_g_l),
-width = 0.5,
-show.legend = F,
-linewidth = 1) +
-scale_color_viridis_d(name = NULL) +
-scale_x_continuous(name = "Time (days)") +
-scale_y_continuous(name = "Mean change in VFA concentration (g/l)") +
-theme_bw() +
-facet_wrap(~treatment) +
-theme(strip.background = element_blank())
-vfa_cummul_vfa_summary |>
-ggplot(aes(x = time_day, y = mean_g_l, fill = vfa)) +
-geom_col(position = "fill") +
-scale_fill_viridis_d(name = NULL) +
-scale_x_continuous(name = "Time (days)") +
-scale_y_continuous(name = "Mean Proportion VFA") +
-theme_bw() +
-facet_wrap(~treatment) +
-theme(strip.background = element_blank())
-sludge_volume <- 30 # ml
-vfa_delta_vfa <- vfa_delta_vfa |>
-mutate(flux = conc_g_l / delta_time / sludge_volume)
-vfa_delta_vfa_summary <- vfa_delta_vfa |>
-group_by(treatment, time_day, vfa) |>
-summarise(mean_flux = mean(flux),
-se_flux = sd(flux)/sqrt(length(flux))) |>
-ungroup()
-ggplot(data = vfa_delta_vfa, aes(x = time_day, colour = vfa)) +
-geom_point(aes(y = flux), alpha = 0.6) +
-geom_errorbar(data = vfa_delta_vfa_summary,
-aes(ymin = mean_flux - se_flux,
-ymax = mean_flux + se_flux),
-width = 1) +
-geom_errorbar(data = vfa_delta_vfa_summary,
-aes(ymin = mean_flux,
-ymax = mean_flux),
-width = 0.8) +
-scale_color_viridis_d(name = NULL) +
-scale_x_continuous(name = "Time (days)") +
-scale_y_continuous(name = "VFA Flux mg/ml/day") +
-theme_bw() +
-facet_wrap(~treatment) +
-theme(strip.background = element_blank())
-ggplot(data = vfa_delta_vfa, aes(x = time_day, colour = treatment)) +
-geom_point(aes(y = flux), alpha = 0.6) +
-geom_errorbar(data = vfa_delta_vfa_summary,
-aes(ymin = mean_flux - se_flux,
-ymax = mean_flux + se_flux),
-width = 1) +
-geom_errorbar(data = vfa_delta_vfa_summary,
-aes(ymin = mean_flux,
-ymax = mean_flux),
-width = 0.8) +
-scale_color_viridis_d(name = NULL, begin = 0.2, end = 0.7) +
-scale_x_continuous(name = "Time (days)") +
-scale_y_continuous(name = "VFA Flux mg/ml/day") +
-theme_bw() +
-facet_wrap(~ vfa, nrow = 2) +
-theme(strip.background = element_blank(),
-legend.position = "top")
-renv::status()
-?heatmapply::heatmapply
-?heatmaply::heatmaply
-?biomaRt::useMart
-?biomaRt::useMart
diff --git a/_quarto.yml b/_quarto.yml
index 5846d31..0dece1a 100644
--- a/_quarto.yml
+++ b/_quarto.yml
@@ -7,10 +7,6 @@ date-format: D MMMM, YYYY
website:
title: "Data Analysis for Group Project"
- cookie-consent:
- type: implied
- style: simple
- palette: light
google-analytics: "G-TVF95J593T"
page-footer:
diff --git a/update-notes.txt b/update-notes.txt
index af6d891..06bcfe5 100644
--- a/update-notes.txt
+++ b/update-notes.txt
@@ -2,15 +2,22 @@ ADD WEBSITE LINK TO ALL SLIDES /MATERAILS
VLE iframe
-
+
+
-
-
+Read an Overview of Transcriptomics 1: 👋 Hello data! (below or open page on external site)
+
-
+Do the independent study to prepare for the workshop (below or open page on external site)
+
-
+
+
+
+
+
+
Independent Study to do before the workshop
Workshop material