Making this work for different experimental set ups #63
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Thus far normalization step is up to speed but I need to walk through the steps in crispr calculation and genetic interaction testing to make sure the changes here are carried all the way through. |
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The NAs are just partial parts of columns rather than the whole columns. I also found that they're a subset of the type of pgRNAs. Looking into the building of |
| @@ -76,14 +57,7 @@ calc_crispr <- function(.data = NULL, | |||
| # fact that single-targeting pgRNAs generate only two double-strand breaks | |||
| # (1 per allele), whereas the double-targeting pgRNAs generate four DSBs. | |||
| # To do this, we set the median (adjusted) LFC for unexpressed genes of each group to zero. | |||
| crispr_score = lfc_adj - median, | |||
| # TODO: I think this n_genes_expressed variable is never used so can we eliminate? | |||
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We don't end up using this so its deleted.
| @@ -107,32 +81,37 @@ calc_crispr <- function(.data = NULL, | |||
| target_type == "gene_ctrl" ~ gRNA1_seq, | |||
| target_type == "ctrl_gene" ~ gRNA2_seq | |||
| ), | |||
| control_gRNA_seq = case_when( | |||
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Some of these steps had to be rearranged. @kweav and I went through this together to figure it out. Needed the double control crisprs to be aligned with the single gene targets they are related to.
R/06-calculate_gi.R
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| mean_observed_crispr = mean(double_crispr_score, na.rm = TRUE) | ||
| ) %>% | ||
| group_modify(~ broom::tidy(lm(mean_observed_crispr ~ mean_expected_crispr, data = .x))) | ||
| mean_expected_double_crispr = mean(expected_crispr_double, na.rm = TRUE) |
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Some of the stats needed adjusting because the single and double crispr scores are calculated differently in their own linear models. @kweav and I pair programmed on this together, referencing the original code.
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| if (rm_ids_wo_annot){ | ||
| lfc_df <- lfc_df %>% | ||
| filter(!pg_ids %in% missing_ids$missing_ids) |
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The missing_ids weren't fully being dropped because it was a vector inside a data.frame so that is fixed here.
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Okay. Vignettes are updated and tests are passing. Going to merge this and we can continue to polish in a new PR. |
Description
Started by making fake data (added that script here)
Now running through the steps and adjusting how folks can specify the different treatment groups.
This needs more work. @kweav and I will pair program on this Wednesday