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+++ b/readme.md
@@ -1,6 +1,54 @@
 Process summary stats for Open Target Genetics
 ==============================================
 
+Workflows for processing summary statistics file for Open Targets Genetics.
+
+### Requirements when adding new datasets
+- Alleles should be harmonised so that ref and alt alleles are on the forward strand and the orientation matches the Ensembl VCF: https://github.com/opentargets/sumstat_harmoniser
+- Alt allele should always be the effect allele
+- For case-control studies where OR are not reported, betas should be converted to log_odds. If association test was run using a linear model (e.g. BOLT-LMM, Hail) then the correct formula to calculate log odds is:
+  ```
+  * log_OR    = β / (μ * (1 - μ))
+  * log_ORse  = se / (μ * (1 - μ))
+  * where μ   = case fraction = (n_cases / (n_cases + n_controls))
+  * OR        = exp(log_OR)
+  * OR 95% CI = exp(log_OR) ± 1.96 * exp(log_ORse)
+  * Citation: https://data.broadinstitute.org/alkesgroup/BOLT-LMM/#x1-5200010.2
+  ```
+- Chromosome must be one of `[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 'X', 'Y', 'MT']`
+- Rows should be filtered to only contain variants with sufficiently high number of minor allele counts (minorAC) to be confident in the association estimate. minorAC = 25. Steps:
+  ```
+  * maf_threshold = minorAC / (2 * n)
+  * where n       = total sample size, for quantitive traits
+                  = min(n_cases, n_controls), for case-control traits
+  * filter all rows to remove where MAF < maf_threshold
+  ```
+- If pval == 0, set to minimum float64
+- NaN and null should be represented as empty string ""
+  - TODO future versions should use 'NA' instead of empty field
+- TODO add INFO score filter ?
+- TODO If MAF is not reported by study, should it be estimated from a reference?
+
+### Columns
+```
+* variant_id_b37 (str): 'chr_pos_ref_alt' for GRCh37
+* chrom (str): chromosome [not null]
+* pos_b37 (pos): position in GRCh37 [not null]
+* ref_al (str): reference allele (non-effect allele) [not null]
+* alt_al (str): alt allele (effect allele) [not null]
+* beta (float): beta for quantitiative study, log_OR for case-control [not null]
+* se (float): standard error of beta for quantitiative study, se of log_OR for case-control [not null]
+* pval (float): p-value. If pval == 0, set to minimum float64 [not null]
+* n_samples_variant_level (int): total sample size (variant level) [nullable]
+* n_samples_study_level (int):   total sample size (study level) [not null if n_samples_variant_level is null]
+* n_cases_variant_level (int): number of cases (variant level) [nullable]
+* n_cases_study_level (int):   number of cases (study level) [not null if n_cases_variant_level is null]
+* eaf (float): effect allele frequency [nullable]
+* maf (float): minor allele frequency [nullable]
+* info (float): imputation quality [nullable]
+* is_cc (bool): 'True' if case-control, 'False' if quantitative study [not null]
+```
+
 ### Proposed summary stat folder structure
 
 https://docs.google.com/document/d/18splDAKSlboKCQdAcLogexE_Zd3odv6qlTSPoBUI4aQ/edit
@@ -62,49 +110,3 @@ sequencing
         gene_level
           {chromosome}-{study_id}-{trait_id}.tsv.gz
 ```
-
-### Requirements when adding new datasets
-- Alleles should be harmonised so that ref and alt alleles are on the forward strand and the orientation matches the Ensembl VCF: https://github.com/opentargets/sumstat_harmoniser
-- Alt allele should always be the effect allele
-- For case-control studies where OR are not reported, betas should be converted to log_odds. If association test was run using a linear model (e.g. BOLT-LMM, Hail) then the correct formula to calculate log odds is:
-  ```
-  * log_OR    = β / (μ * (1 - μ))
-  * log_ORse  = se / (μ * (1 - μ))
-  * where μ   = case fraction = (n_cases / (n_cases + n_controls))
-  * OR        = exp(log_OR)
-  * OR 95% CI = exp(log_OR) ± 1.96 * exp(log_ORse)
-  * Citation: https://data.broadinstitute.org/alkesgroup/BOLT-LMM/#x1-5200010.2
-  ```
-- Chromosome must be one of `[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 'X', 'Y', 'MT']`
-- Rows should be filtered to only contain variants with sufficiently high number of minor allele counts (minorAC) to be confident in the association estimate. minorAC = 25. Steps:
-  ```
-  * maf_threshold = minorAC / (2 * n)
-  * where n       = total sample size, for quantitive traits
-                  = min(n_cases, n_controls), for case-control traits
-  * filter all rows to remove where MAF < maf_threshold
-  ```
-- If pval == 0, set to minimum float64
-- NaN and null should be represented as empty string ""
-  - TODO future versions should use 'NA' instead of empty field
-- TODO add INFO score filter ?
-- TODO If MAF is not reported by study, should it be estimated from a reference?
-
-### Columns
-```
-* variant_id_b37 (str): 'chr_pos_ref_alt' for GRCh37
-* chrom (str): chromosome [not null]
-* pos_b37 (pos): position in GRCh37 [not null]
-* ref_al (str): reference allele (non-effect allele) [not null]
-* alt_al (str): alt allele (effect allele) [not null]
-* beta (float): beta for quantitiative study, log_OR for case-control [not null]
-* se (float): standard error of beta for quantitiative study, se of log_OR for case-control [not null]
-* pval (float): p-value. If pval == 0, set to minimum float64 [not null]
-* n_samples_variant_level (int): total sample size (variant level) [nullable]
-* n_samples_study_level (int):   total sample size (study level) [not null if n_samples_variant_level is null]
-* n_cases_variant_level (int): number of cases (variant level) [nullable]
-* n_cases_study_level (int):   number of cases (study level) [not null if n_cases_variant_level is null]
-* eaf (float): effect allele frequency [nullable]
-* maf (float): minor allele frequency [nullable]
-* info (float): imputation quality [nullable]
-* is_cc (bool): 'True' if case-control, 'False' if quantitative study [not null]
-```