Merge pull request #2 from sacdallago/output_4

Add output option 4 for i/o and B/b H/h

README.md

@@ -129,11 +129,12 @@ If you run into "out of memory" issues, try reducing the batch size.
 
 ## Prediction output
 
-TMbed supports four different output formats:
+TMbed supports five different output formats:
 - `0`: 3-line format with directed segments.
 - `1`: 3-line format with undirected segments.
 - `2`: Tabular format with directed segments.
 - `3`: Tabular format with undirected segments.
+- `4`: 3-line format with directed segments and explicit inside/outside prediction (a mix of format `0` and `1`).
 
 Predicted residue classes are encoded by single letters.\
 In 3-line format, every protein is represented by three lines: header, sequence, labels.\
@@ -168,7 +169,7 @@ In tabular format, every protein is represented by a table containing sequence,
     SSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSiiiiiiiiiBBBBBBBBBBoooooooooooooooooBBBBBBBBBBBiiiiiBBBBBBBBBBoooooooooooooooooooooooooooooooBBBBBBBBBBiiiiiiiiiBBBBBBoooooooooooooooBBBBBBBBiiiiBBBBBBBBooooooooooooooooooooBBBBBBBBiiiiiiBBBBBBBBooooooooooooooooooooooooooBBBBBBBBiiiiiiiiiiBBBBBBBBBBooooooooooooooooooooooooooooBBBBBBBBBBiiiiiBBBBBBBBooooooooooooooooooooooooooooooooooooooooooooooBBBBBBBBBiiiiiBBBBBBBBooooooooooooooooooooooooooooBBBBBBBBBiiiiiiiiiiiiiiiiiiBBBBBBBBBBoooooooooooooooBBBBBBBBBi
     ```
 
-2. `--out-format=2` and `--out-format=3`
+3. `--out-format=2` and `--out-format=3`
 
     - `AA`: Amino acid
     - `PRD`: Predicted class label
@@ -195,6 +196,22 @@ In tabular format, every protein is represented by a table containing sequence,
     ...
     ```
 
+4. `--out-format=4`
+
+    - `B`: Transmembrane beta strand (IN-->OUT orientation)
+    - `b`: Transmembrane beta strand (OUT-->IN orientation)
+    - `H`: Transmembrane alpha helix (IN-->OUT orientation)
+    - `h`: Transmembrane alpha helix (OUT-->IN orientation)
+    - `S`: Signal peptide
+    - `i`: Non-Transmembrane, inside
+    - `o`: Non-Transmembrane, outside
+
+    ```
+    >7acg_A|P18895|ALGE_PSEAE
+    MNSSRSVNPRPSFAPRALSLAIALLLGAPAFAANSGEAPKNFGLDVKITGESENDRDLGTAPGGTLNDIGIDLRPWAFGQWGDWSAYFMGQAVAATDTIETDTLQSDTDDGNNSRNDGREPDKSYLAAREFWVDYAGLTAYPGEHLRFGRQRLREDSGQWQDTNIEALNWSFETTLLNAHAGVAQRFSEYRTDLDELAPEDKDRTHVFGDISTQWAPHHRIGVRIHHADDSGHLRRPGEEVDNLDKTYTGQLTWLGIEATGDAYNYRSSMPLNYWASATWLTGDRDNLTTTTVDDRRIATGKQSGDVNAFGVDLGLRWNIDEQWKAGVGYARGSGGGKDGEEQFQQTGLESNRSNFTGTRSRVHRFGEAFRGELSNLQAATLFGSWQLREDYDASLVYHKFWRVDDDSDIGTSGINAALQPGEKDIGQELDLVVTKYFKQGLLPASMSQYVDEPSALIRFRGGLFKPGDAYGPGTDSTMHRAFVDFIWRF
+    SSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSiiiiiiiiiBBBBBBBBBBooooooooooooooooobbbbbbbbbbbiiiiiBBBBBBBBBBooooooooooooooooooooooooooooooobbbbbbbbbbiiiiiiiiiBBBBBBooooooooooooooobbbbbbbbiiiiBBBBBBBBoooooooooooooooooooobbbbbbbbiiiiiiBBBBBBBBoooooooooooooooooooooooooobbbbbbbbiiiiiiiiiiBBBBBBBBBBoooooooooooooooooooooooooooobbbbbbbbbbiiiiiBBBBBBBBoooooooooooooooooooooooooooooooooooooooooooooobbbbbbbbbiiiiiBBBBBBBBoooooooooooooooooooooooooooobbbbbbbbbiiiiiiiiiiiiiiiiiiBBBBBBBBBBooooooooooooooobbbbbbbbbi
+    ```
+
 
 ## Precomputed predictions
 

tmbed/tmbed.py

@@ -232,8 +232,10 @@ def predict(fasta_file: Path = ARGS.fasta,
         pred_map = {0: 'B', 1: 'b', 2: 'H', 3: 'h', 4: 'S', 5: '.', 6: '.'}
     elif out_format in {OutFmt.F1, OutFmt.F3}:
         pred_map = {0: 'B', 1: 'B', 2: 'H', 3: 'H', 4: 'S', 5: 'i', 6: 'o'}
+    elif out_format in {OutFmt.F4}:
+        pred_map = {0: 'B', 1: 'b', 2: 'H', 3: 'h', 4: 'S', 5: 'i', 6: 'o'}
 
-    if out_format in {OutFmt.F0, OutFmt.F1}:
+    if out_format in {OutFmt.F0, OutFmt.F1, OutFmt.F4}:
         write_3_line(output_file, proteins, predictions, pred_map)
     elif out_format in {OutFmt.F2, OutFmt.F3}:
         write_tabular(output_file, proteins, predictions, pred_map)

tmbed/utils.py

@@ -33,6 +33,7 @@ class OutFmt(str, Enum):
     F1 = '1'
     F2 = '2'
     F3 = '3'
+    F4 = '4'
 
 
 @dataclass