Format the dataset details into a better structure

README.md

@@ -9,11 +9,10 @@ pretty_name: >-
 ---
 
 # Mega-scale experimental analysis of protein folding stability in biology and design
-Here we present cDNA display proteolysis, a method for measuring thermodynamic folding
-stability for up to 900,000 protein domains in a one-week experiment. From 1,841,285
-measurements in total, we curated a set of 776,298 high-quality folding stabilities
-covering all single amino acid variants and selected double mutants of 331 natural and 148
-de novo designed protein domains 40–72 amino acids in length.
+The Mega-scale dataset contains 1,841,285 thermodynamic folding stability measurements using
+cDNA display proteolysis of natural and designed proteins from which 776,298 high-quality folding
+stabilities covering all single amino acid variants and selected double mutants of 331 natural
+and 148 de novo designed protein domains 40–72 amino acids in length.
 
 ## Quickstart Usage
 
@@ -61,48 +60,39 @@ which is a column oriented format that can be accessed directly, converted in to
     >>> dataset_models.to_pandas()
     >>> dataset_models.to_parquet("dataset.parquet")
 
-## Dataset Details
-
-
-1.8 million measurements in total
-
-
-curated a set of around 776,298 high-quality folding stabilities covering
+## Dataset Overview
+The curated a set of 776,298 high-quality folding stabilities covers
    * all single amino acid variants and selected double mutants of 331 natural and 148 de novo designed protein domains 40–72 amino acids in length
    * comprehensive double mutations at 559 site pairs spread across 190 domains (a total of 210,118 double mutants)
    * 36 different 3-residue networks
      * all possible single and double substitutions in both the wild-type background and the background in which the third amino acid was replaced by alanine
      * (400 mutants × 3 pairs × 2 backgrounds ≈ 2,400 mutants in total for each triplet)
 
-
-We determine ΔG using each sequence’s
-   * measured K50, a predicted sequence-specific K50 for the unfolded state (K50,U)
-   * a universal K50 for the folded state (K50,F)
-
-
-published studies using purified protein samples for 1,188 variants of 10 proteins (Fig. 1g and Supplementary Fig. 1 for more details on GB129)
-Our measurements for these sequences were all performed in libraries of 244,000–900,000 total sequences.
-
-
-stability for all single substitutions, deletions and Gly and Ala insertions in 983 natural and designed domains (wild-type sequences)
-  * natural domains
-    * nearly all the small (less than 72 amino acids) monomeric domains in the PDB that were suitable for our assay (Methods)
-    * all monomeric proteins in the PDB in the 30–100 amino acid length range in June 2021
-      * excluded structures that
-        * had only a single helix
-        * contained other molecules (for example, proteins, nucleic acids or metals)
-        * were annotated to have DNAse, RNAse or protease inhibition activity
-        * included more than four cystines
-      * removed redundant sequences (amino acid sequence distance <2)
-      * predicted the structures of these PDB sequences using AlphaFold
-        * trim amino acids from the N- and C termini that had a low number of contacts with any other residues
-      * selected domains with up to 72 amino acids after excluding N- or C-terminal flexible loops
-  * designed domains
-    (1) previous Rosetta designs with ααα, αββα, βαββ, and ββαββ topologies (40 to 43 amino acids)
-    (2) new ββαα proteins designed using Rosetta (47 amino acids)
-    (3) new domains designed by trRosetta hallucination (46 to 69 amino acids)
-  * "destabilized wild-type backgrounds": 121
-  => four giant synthetic DNA oligonucleotide libraries and obtained K50 values for 2,520,337 sequences, 1,841,285 of these measurements are included here
+### Target Selection
+Targets consist of natural, designed, and destabilized wild-type
+
+983 **natural targets** were selected from the all monomeric proteins in the protein databank having 30–100 amino
+acid length range that met the following criteria:
+  * Conisted of more than a single helix
+  * Did not contain other molecules (for example, proteins, nucleic acids or metals)
+  * Were not annotated to have DNAse, RNAse, or protease inhibition activity
+  * Had at most four cysteins
+  * Were not sequence redundant (amino acid sequence distance <2) with another selected sequence
+These were then processed by
+  * AlphaFold was used to predict the structure (including those that had solved structures in the PDB),
+    which was used to trim amino acids from the N- and C termini that had a low number of contacts with any other residues.
+  * selected domains with up to 72 amino acids after excluding N- or C-terminal flexible loops
+
+XXX **designed targets** were selected from
+  * previous Rosetta designs with ααα, αββα, βαββ, and ββαββ topologies (40 to 43 amino acids)
+  *  new ββαα proteins designed using Rosetta (47 amino acids)
+  * new domains designed by trRosetta hallucination (46 to 69 amino acids)
+
+121 **destabilized wild-type backgrounds** targets were also included.
+
+### Library construction
+The cDNA proteolysis screening was conducted as four giant synthetic DNA oligonucleotide libraries
+and obtained K50 values for 2,520,337 sequences, 1,841,285 of these measurements are included here:
     * Library 1:
       * ~250 designed proteins and ~50 natural proteins that are shorter than 45 amino acids
       * padding by Gly, Ala and Ser amino acids so that all sequences have 44 amino acids
@@ -126,16 +116,49 @@ stability for all single substitutions, deletions and Gly and Ala insertions in
       * Purchased from Twist Bioscience, length 300 nt.
 
 
-T-C := trypsin vs. chymotrypsin
+### Bayesian Stability Analysis
+Each target was analyzed and given a single quality category score G0-G11, which were then sorted into one of three datasets. The quality scores are
+  * G0: Good (wild-type ΔG values below 4.75 kcal mol^−1)
+  * G1: Good but WT outside dynamic range
+  * G2: Too much missing data
+  * G3: WT dG is too low
+  * G4: WT dG is inconsistent
+  * G5: Poor trypsin vs. chymotrypsin correlation
+  * G6: Poor trypsin vs. chymotrypsin slope
+  * G7: Too many stabilizing mutants
+  * G8: Multiple cysteins (probably folded properly)
+  * G9: Multiple cysteins (probably misfolded)
+  * G10: Poor T-C intercept
+  * G11: Probably cleaved in folded state(s)
+
+The datasets 1-3 with three being the highest quality are defined by:
+  * Dataset 3 (for ddG ML) (G0: 325,132 ΔG measurements at 17,093 sites in 365 domains)
+  * Dataset 2 (for dG ML) (G0+G1: 478 domains)
+  * Dataset 1 (all data)
+
 
-Datasets
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+1.8 million measurements in total
+
+
+
+We determine ΔG using each sequence’s
+   * measured K50, a predicted sequence-specific K50 for the unfolded state (K50,U)
+   * a universal K50 for the folded state (K50,F)
+
+
+published studies using purified protein samples for 1,188 variants of 10 proteins (Fig. 1g and Supplementary Fig. 1 for more details on GB129)
+Our measurements for these sequences were all performed in libraries of 244,000–900,000 total sequences.
+
+
+
+Other Datasets for comparison
   * ProthermDB
     * Thermodynamic data
     * Thermal proteome profiling
   * Rocklin2017
-  * Dataset 3 (for ddG ML) (G0: 325,132 ΔG measurements at 17,093 sites in 365 domains)
-  * Dataset 2 (for dG ML) (G0+G1: 478 domains)
-  * Dataset 1 (all data)
+
 
 Tsuboyama2023_Dataset2_Dataset3_20230416.csv
   * All sequences in dataset 2 and dataset 3 are included
@@ -146,23 +169,5 @@ Tsuboyama2023_Dataset2_Dataset3_20230416.csv
   * low-quality data (including mutant data filtered in Stage 3) have been filtered out and
     replaced by a "–"" symbol in the columns labelled ‘_ML’ (for machine learning).
 
-Classification of mutational scanning results
-  * G0: Good (wild-type ΔG values below 4.75 kcal mol^−1)
-  * G1: Good but WT outside dynamic range
-  * G2: Too much missing data
-  * G3: WT dG is too low
-  * G4: WT dG is inconsistent
-  * G5: Poor T-C correlation
-  * G6: Poor T-C slope
-  * G7: Too many stabilizing mutants
-  * G8: Multiple cysteins (probably folded properly)
-  * G9: Multiple cysteins (probably misfolded)
-  * G10: Poor T-C intercept
-  * G11: Probably cleaved in folded state(s)
-  => All mutational scans are included in only one group 
-
-
 predicting wild-type amino acids from the folding stabilities (ΔG) of each protein variant
   * 99,156 ΔG measurements (5,214 sites in 90 non-redundant natural domains)
-
-