Merge pull request #43 from bigbio/dev

Technical replicate included

.gitignore

@@ -1,4 +1,5 @@
 quantmsio.egg-info
 dist
 build
-.idea
+.idea
+data

README.md

@@ -1,5 +1,10 @@
 # quantms.io
 [![Python application](https://github.com/bigbio/quantms.io/actions/workflows/python-app.yml/badge.svg?branch=dev)](https://github.com/bigbio/quantms.io/actions/workflows/python-app.yml)
+[![Upload Python Package](https://github.com/bigbio/quantms.io/actions/workflows/python-publish.yml/badge.svg)](https://github.com/bigbio/quantms.io/actions/workflows/python-publish.yml)
+[![Codacy Badge](https://app.codacy.com/project/badge/Grade/e71a662e8d4f483094576c1d8f8888c3)](https://app.codacy.com/gh/bigbio/quantms.io/dashboard?utm_source=gh&utm_medium=referral&utm_content=&utm_campaign=Badge_grade)
+[![Codacy Badge](https://app.codacy.com/project/badge/Coverage/e71a662e8d4f483094576c1d8f8888c3)](https://app.codacy.com/gh/bigbio/quantms.io/dashboard?utm_source=gh&utm_medium=referral&utm_content=&utm_campaign=Badge_Coverage)
+[![Documentation Status](https://readthedocs.org/projects/quantmsio/badge/?version=latest)](https://quantmsio.readthedocs.io/en/latest/?badge=latest)
+[![PyPI version](https://badge.fury.io/py/quantmsio.svg)](https://badge.fury.io/py/quantmsio)
 
 [quantms](https://docs.quantms.org) is a nf-core pipeline for the analysis of quantitative proteomics data. The pipeline is based on the [OpenMS](https://www.openms.de/) framework and [DIA-NN](https://github.com/vdemichev/DiaNN); and it is designed to analyze large scale experiments. the main outputs of quantms tools are the following: 
 

quantmsio/core/feature_in_memory.py

@@ -786,6 +786,7 @@ def _merge_sdrf_to_msstats_in(self, sdrf_path, msstats_in):
                 factor,
                 "comment[fraction identifier]",
                 "comment[label]",
+                "comment[technical replicate]",
             ]
         ]
         sdrf["comment[data file]"] = sdrf["comment[data file]"].swifter.apply(lambda x: x.split(".")[0])
@@ -797,7 +798,7 @@ def _merge_sdrf_to_msstats_in(self, sdrf_path, msstats_in):
                 right_on=["comment[data file]", "comment[label]"],
                 how="left",
             )
-            res.drop(["comment[data file]", "comment[label]"], axis=1, inplace=True)
+            res.drop(["comment[data file]", "comment[label]", "comment[technical replicate]"], axis=1, inplace=True)
             res.rename(columns=self._map_tmt, inplace=True)
             res.rename(columns={factor: "condition"}, inplace=True)
             return res
@@ -809,7 +810,19 @@ def _merge_sdrf_to_msstats_in(self, sdrf_path, msstats_in):
                 right_on=["comment[data file]"],
                 how="left",
             )
-            res.drop(["comment[data file]", "comment[label]"], axis=1, inplace=True)
+            samples = sdrf["source name"].unique()
+            mixed_map = dict(zip(samples, range(1, len(samples) + 1)))
+            res.loc[:, "Run"] = res[
+                ["source name", "comment[technical replicate]", "comment[fraction identifier]"]
+            ].swifter.apply(
+                lambda row: str(mixed_map[row["source name"]])
+                + "-"
+                + str(row["comment[technical replicate]"])
+                + "-"
+                + str(row["comment[fraction identifier]"]),
+                axis=1,
+            )
+            res.drop(["comment[data file]", "comment[label]", "comment[technical replicate]"], axis=1, inplace=True)
             res.rename(columns=self._map_lfq, inplace=True)
             res.rename(columns={factor: "condition"}, inplace=True)
             return res